WO2011134020A1

WO2011134020A1 - Determining a geographical location relevant to a digital content object

Info

Publication number: WO2011134020A1
Application number: PCT/AU2011/000496
Authority: WO
Inventors: Nicholas William Holmes A Court
Original assignee: Buzznumbers Pty Ltd
Priority date: 2010-04-30
Filing date: 2011-05-02
Publication date: 2011-11-03
Also published as: NZ603316A; AU2011245075A1

Abstract

A method, processing system, and computer program product for determining a degree of relevancy of one or more geographical locations to a digital content object. In one aspect, the method includes, in a processing system: identifying, for a digital content object, a plurality of geographical indicators to a plurality of geographical locations; obtaining, from a data store, a plurality of geographical hierarchies for the plurality of geographical locations; and calculating, for each geographical location and using a relevancy rule, a relevancy score indicative of the degree of relevancy of the respective geographical location to the digital content object, wherein each relevancy score is calculated based at least partially upon a degree of commonality between the respective geographical hierarchy with a remainder of the geographical hierarchies.

Description

DETERMINING A GEOGRAPHICAL LOCATION RELEVANT TO A DIGITAL

CONTENT OBJECT

Technical Field

The present invention relates to a method, processing system, and/or computer program product for determining a geographical location relevant to a digital content object.

Background

There are a number of techniques available for determining the geographical relevance of a digital content object. For example, a number of Internet search engines that are currently available allow for a search to be performed based on a geographical criteria. A specific example is the search engine Google, wherein the Australian portal (www.google.com.au) allows for an executed search to return "pages from Australia". Generally, the results that are returned are based upon the domain name extension (i.e. only webpages which include an "au" suffix are returned as part of the search results) and/or some other reference to the geographical location in the IP address of the hosting server processing system and/or the URL of the webpage.

However, the results returned using such techniques are problematic For example, in the event that a webpage includes content specifically about Australia is hosted on a processing system located in the US and is associated with a URL which makes no reference to Australia in the domain name, it is likely the above techniques will fail to return such a website in the search results as being relevant to Australia. Whilst the above example for determining the geographical relevance of a digital content object has been exemplified in relation to Internet search engines, this problem is relevant to many other fields of technology. Currently, it is difficult to determine one or more .geographical locations which have some degree of relevance for a digital content object such as a website. Therefore, there is a need for a method, system, and/or computer program product which can overcome or at least alleviate one or more of the above-mentioned problems, or at least provide a useful commercial alternative. The reference in this specification to any prior publication (or information derived from it), or to any matter which is known, is not, and should not be taken as, an acknowledgement or admission or any form of suggestion that that prior publication (or information derived from it) or known matter forms part of the common general knowledge in the field of endeavour to which this specification relates.

Summary

In one broad aspect there is provided a method for determining a degree of relevancy of one or more geographical locations to a digital content object, wherein the method includes, in a processing system: ^'

identifying, for a digital content object, a plurality of geographical indicators to a plurality of geographical locations;

obtaining, from a data store, a plurality of geographical hierarchies for the plurality of geographical location's; and

calculating, for each geographical location and using a relevancy rule, a relevancy score indicative of the degree of relevancy of the respective geographical location to the digital content object, wherein each relevancy score is calculated based at least partially upon a degree of commonality between the respective geographical hierarchy with a remainder of the geographical hierarchies. In one form, the method includes- identifying at least one .of the geographical indicators from textual content of the digital content object.

In another form, the method includes identifying at least one of the geographical indicators from one or more links to other digital content objects.

In one embodiment, the method includes identifying at least one of the geographical indicators from a country code of a URL associated with the digital content object.

In another embodiment, the method includes identifying at least one of the geographical indicators by obtaining an address of an author of the digital content object.

In an optional form, the method includes;

classifying each geographical location according to a geographical location type; and

using a set of weight data to further calculate the relevancy score for each geographical location further according to a geographical location type of the respective geographical location.

In another optional form, the digital content object is a social media object. In an optional embodiment, the method is performed upon a plurality of digital content objects for indexation within a data store.

In another optional embodiment, the method includes indexing the pluralit of digital content objects by storing a corresponding plurality of records in the data store, wherein each record is indicative of the respective digital content object, the geographical locations for the respective digital content object and the respective relevancy scores for the geographical locations.

Optionally, the method includes;

receiving a search query for conducting a search of the digital content objects indexed in the data store, wherein the search query at least partially includes a geographical location;

conducting^ using_, the search query, the search of the plurality of digital content objects indexed in the data store; and

returning, to the user, one or more digital content objects indexed in the data store which at least partially satisfy the search query, wherein the digital content objects of the search results are at least partially ranked according to the respective relevancy scores relative to the geographical location of the search query,

In another broad aspect there is provided a processing system for determining a degree of relevancy of one or more geographical locations to a digital content object, wherein the processing system is configured to:

identify, for a digital content object, a plurality of geographical indicators to a plurality of geographical locations;

obtain, from a data store, a plurality of geographical hierarchies for the plurality of geographical locations; and

calculate, for each geographical location and using a relevancy rule, a relevancy score indicative of the degree of relevancy of the respective geographical location to the digital content object, wherein each relevancy score is calculated based at least partially upon a degree of commonality between the respective geographical hierarchy with a remainder of the geographical hierarchies.

In one form, the processing system is configured to identify at least one of the geographical indicators from textual content of the digital content object. In another form, the processing system is configured to identify at least one of the geographical indicators from one or more links to other digital content objects.

In one embodiment, the processing system is configured to identify at least one of the geographical indicators from a country code of a URL associated with the digital content object,

In another embodiment, the processing system is configured to identify at least one of the geographical indicators by obtaining an address of an author of the digital content object. In an optional form, the processing system is configured to:

classify each geographical location according to a geographical location type; and use a set of weight data to further calculate the relevancy score for each geographical location further according to a geographical location type of the respective geographical location. In another optional form, the digital content object is a social media object.

In an optional embodiment, the processing system is configured to determine a degree of relevancy of one or more geographical locations for a plurality digital content objects for indexation in the data store.

In another optional embodiment, the processing system is configured to index the plurality of digital content objects by storing a corresponding plurality of records in the data store, wherein each record is indicative of the respective digital content object, the geographical locations for the respective digital content object and the respective relevancy scores for the geographical locations.

Optionally, the processing system is configured to:

receive, from a user, a search query for conducting a search of the digital content objects indexed in the data store, wherein the search query at least partially includes a geographical location;

conduct, using the search query, the search of the plurality of digital content objects indexed in the data store; and

return, to the user, one or more digital content objects indexed in the data store which at least partially satisfy the search query, wherein the digital content objects of the search results are at least partially ranked according to the respective relevancy scores relative to the geographical location of the search query, In another broad aspect there is provided a computer program product for determining a degree of relevancy of one or more geographical locations to a digital content object, wherein the computer program product includes executable instructions configuring a processing system to: identify, for a digital content object, a plurality of geographical indicators to a plurality of geographical locations;

In one form, the executable instructions of the computer program product configure the processing system to identify at least one of the geographical indicators from textual content of the digital content object. In another form, the executable instructions of the computer program product configure the

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processing system to identify at least one of the geographical indicators from one or more links to other digital content objects.

In one embodiment, the executable instructions of the computer program product configure the processing system to identify at least one of the geographical indicators from a country code of a URL associated with the digital content object.

In another embodiment, the executable instructions of the computer program product configure the processing system to identify at least one of the geographical indicators by obtaining an address of an author of the digital content object.

In an optional form, the executable instructions of the computer program product configure the processing system to:

classify each geographical location according to a geographical location type; and use a set of weight data to further calculate the relevancy score for each geographical location further according to a geographical location type of the respective geographical location,

In another optional form, the digital content object is a social media object, In an optional embodiment, the executable instructions of the computer program product configure the processing system to determine a degree of relevancy of one or more geographical locations for a plurality digital content objects for indexation in the data store . In another optional embodiment, the executable instructions of the computer program product configure the processing system to index the plurality of digital content objects by storing a corresponding plurality of records in the data store, wherein each record is indicative of the respective digital content object, the geographical locations for the respective digital content object and the respective relevancy scores for the geographical locations.

Optionally, the executable instructions of the computer program product configure the processing system to

return, to the user, one or more digital content objects indexed in the data store which at least partially satisfy the search query, wherein the digital content objects of the search results are at least partially ranked according to the respective relevancy scores relative to the geographical location of the search query,

.Other embodiments will be described throughout the description of the example embodiments,

Brief Description of the Figures Example embodiments should become apparent from the following description, which is given by way of example only, of at least one preferred but non-limiting embodiment, described in connection with the accompanying figures. Figure Ϊ illustrates a functional block diagram of an example processing system that can be utilised to embody or give effect to a particular embodiment;

Figure 2 illustrates a flowchart representing an example method for determining the geographical relevance of a digital content object;

Figure 3 illustrates a flowchart representing a more detailed example method for detennining the geographical relevance of a digital content object;

Figure 4 illustrates an example of a digital content object;

Figure 5 illustrates an example of a first table of records indicative of geographic indicators within the digital content object;

Figure 6 illustrates an example of the first table of Figure 5 including corresponding geographical hierarchies and additional data fields;

Figure 7 illustrates an example table representing a set of weight data for geographical location types; Figure 8 illustrates an example of a second table of records indicative of geographic indicators for other linked digital content objects to the digital content object;

Figure 9 illustrates an example of a third table of records indicative of a plurality of geographical hierarchies and associated relevancy scores; and Figure 10 illustrates the third table of Figure 9 indicating a simplified view of the plurality of geographical hierarchies for the one or more geographical locations relevant to the digital content object and the respective relevancy scores.

5 Description of Embodiments

The following modes, given by way of example only, are described in order to provide a more precise understanding of the subject matter of a preferred embodiment or embodiments. In the figures, incorporated to Illustrate features of an example embodiment, like reference numerals are used to identify like parts throughout the figures.

10

A particular embodiment can be realised using a processing system, an example of which is shown in Fig. 1 . In particular, the processing system 100 generally includes at least one processor 102, or processing, unit or plurality of processors, memory 104, at least one input device 106 and at least one output device 108, coupled together via a bus or group of buses

1 5 1 1 0. In certain embodiments, input device 106 and output device 3 08 could be the same device. An interface 1 12 also can be provided for coupling the processing system 1 00 to one or more peripheral devices, for example interface 1 12 could be a PCI card or PC card. At least one storage device 1 14 which houses at least one database 1 16 can also be provided. The memory 104 can be any form of memory device, for example, volatile or

20 non- volatile memory, solid state storage devices, magnetic devices, etc. The processor 102 could include more than one distinct processing device, for example to handle different functions within the processing system 100.

Input device 106 receives input data 1 18 and can include, for example, a keyboard, a 5 pointer device such as a pen-like device or a mouse, audio receiving device for voice controlled activation such as a microphone, data receiver or antenna such as a modem or wireless data adaptor, data acquisition card, etc.. Input data 1 1 8 could come from different sources, for example keyboard instructions in conjunction with data received via a network. Output device 108 produces or generates output data 120 and can include, for 30 example, a display device or monitor in which case output data 120 is visual, a printer in which case output data 120 is printed, a port for example a USB port, a peripheral componcnt adaptor, a data transmitter or antenna such as a modem or wireless network adaptor, etc.. Output data 120 could be distinct and derived from different output devices, for example a visual display on a monitor in conjunction with data transmitted to a network. A user could view data output, or an interpretation of the data output, on, for example, a monitor, or using a printer. The storage device 1 1 can be any form of data or information storage means, for example, volatile or non-volatile memory, solid state storage devices, magnetic devices, etc..

In use, the processing system 100 is adapted to allow data or information to be stored in and/or retrieved from, via wired or wireless communication means, the at least one database 1 16 and/Or the memory 104. The interface 1 1 2 may allow wired and/or wireless communication between the processing unit 102 and peripheral components that may serve ^' a specialised purpose, The processor 102 receives instructions as input data 1 1 8 via input device 1 06 and can display processed results or other output to a user by utilising output device 108. More than one input device 106 and/or output device 1 08 can be provided. It should be appreciated that the processing system 100 may be any form of terminal, server, specialised hardware, or the like.

Referring to Figure 2, there is shown a flowchart representing an example method of determining a degree of relevance of one or more geographical locations to a digital · content object. It will be appreciated that the method described herein can be performed by a processing system 100 described in relation to Figure 1.

In particular, at step 21 , the method 200 includes the processing system identifying, for a digital content object, a plurality of geographical indicators to a plurality of geographical locations. At step 220, the method includes obtaining, from a data store, a plurality of geographical hierarchies for the plurality of geographical locations. At step 230, the method includes calculating, for each geogra hical location and using a relevancy rule, a relevancy score indicative of the degree of relevancy of the respective geographical location to the digital content object, wherein each relevancy score is calculated based at least partially upon a degree of commonality between the respective geographical hierarchy with a remainder of the geographical hierarchies.

By calculating the degree of commonality between the geographical hierarchies, it is possible to determine the context which the geographical indicator is being used in order to reduce false positives (i.e. noise), and also it is possible to determine the degree of relevance of one or more geographical location to the digital content object.

It will be appreciated that a system can be provided including a processing system, such as processing system 100, which is configured to perform the method exemplified in Figure 2 and/or described herein. It will also be appreciated that a computer-program product may be provided including executable instructions which configure a processing system, such as processing system 100, to perform the method exemplified in Figure 2 and/or described herein. The computer program product is generally provided in the form of a non- transitory computer readable medium. The term "computer program product" as used herein refers to any storage or transmission medium that participates in providing instructions and/or data to the processing system 100 for execution and/or processing. Examples of storage media include floppy disks, magnetic tape, CD-ROM, a hard disk drive, a ROM or integrated circuit, a magneto-optical disk, or a computer readable card such as a PCMCIA card and the like, whether or not such devices are internal or external of the processing system 1 00, Examples of transmission media include radio or infra-red transmission channels as well as a network connection to another computer or networked device, and the Internet or Intranets including e-mail transmissions and information recorded on Websites and the like. Referring to Figure 3, there is shown a flowchart in relation to an example of a more detailed method of determining a level of relevance of one or more geographical locations to a digital content object.

In particular, at step 305, the method 300 includes the processing system extracting content from a digital content object. In one exemplary form, the digital content object may be a webpage available via the Internet. In this example, the source code of the webpage may be obtained and then filtered in order to remove XHTML tags and the like which do not relate to the textual content of the webpage. However, as will be discussed in more detail in further examples, links, such as hyperlinks, to other digital content objects are generally left unftltered.

At step 3 10, the method 300 includes the processing system identifying textual portions in the content which are geographical locations. A geographical location may include a suburb, a city, a region, a state/province/territory, or a country. The processing system may have stored in a first data store a list of geographical locations which can be used to search the content of the digital content object to identify one or more geographical locations. Once the processing system identifies a textual portion indicative of a geographical location, the processing system adds a record into a geographical location list for the digital content object, The processing system can also store a position that the textual portion was found in the content, such as being the 20th word found in the content or the like. Once the entire content has been searched and processed, a list of geographical location records is likely to have been generated and the method proceeds to step 31 5.

At step 3 1 5, the method includes the processing system obtaining, for each textual portion indicative of a geographical location, a geographical location hierarchy for the respective geographical location. The processing system may use a second data store including data indicative of a plurality of geographical location hierarchies, However, it ill be appreciated that the first and second data stores may be the same data store, or portions of the same data store. Each data store may be provided in the form of a database, or parts of a database.

An example of a geographical location hierarchy may be indicated by the following for a suburb called 'Bondi':

Suburb: Bondi

City; Sydney

Region: Eastern Suburbs

State: Mew South Wales Country: Australia

It will be appreciated that the geographical hierarchy may be of various depth depending on the geographical location type. For example, in the event that a geographical indicator for the digital content object is 'Eastern Suburbs', then the geographical hierarchy obtained by the processing system may be in accordance with the following:

Region: Eastern Suburbs

State: New South Wales

Country: Australia

Each geographical hierarchy is stored in a geographical hierarchy list for use in later steps . At step 320, the method includes weighting the list of geographical location records. In one form, weighting the geographical location records can include applying a weighting indicative of a potential false positive identification in the geographical location record. The processing system can filter the list of geographical location records,- for example, according to a list of nouns from a dictionary file to identify one or more homonyms. For example, a geographical indicator identified may be indicative of "Page" which is both a noun and also a suburb located in the Australian Capital Territory (ACT). In this instance, a weighting is applied to this geographical location record indicative of a potential false positive. For example, this record may receive a weighting of one.

In an additional or alternative form, the each geographical location record may be weighted according to the type of geographical location (i.e. Suburb, City, Region, Eastern Suburbs, State, New South Wales, Country) which the textual portion is indicative thereof. In one form, the more generalised the geographical location, the greater the weighting applied by the processin system to the geographical location record, and thus the more specific the geographical location, a lesser weighting can be applied by the processing system to the respective geographical location record, For example, a geographical location record indicatis e of the geographical indicator "Sydney" may receive a smaller weighting compared to "Australia",

At step 325, the method includes comparing the geographical hierarchies for at least some of the geographical indicators identified in the content for the digital content object to determine a degree of commonality between respective geographical hierarchies, For example, two geographical location hierarchies may include:

Geographical Location Ul = "Surry Hills"

■ Suburb: Surry Hills

City: Sydney

Region: Eastern Suburbs

State: New South Wales

Country: Australia

Geographical Location #2 = "Sydney"

City: Sydney

Region: Eastern Suburbs

State: New South Wales

Country: Australia

The processing system can compare the geographical hierarchies for these two geographical indicators and identify that the second geographical hierarchy overlaps the first geographical hierarchy, specifically in relation to the geographical location types of city, region, state and country^'. Therefore, the processing system can Increase the weighting for the first geographical location record due to this level of commonality between the hierarchies.

Additionally or alternatively, the processing system may compare the position of each geographical indicator in the content against a threshold to determine if there i s a positional relationship as well as a logical geographical relationship, For example, the threshold may be set to 20 textual characters, wherein in the event that two textual portions were located relative to each other in the content within this threshold, a positive weighting is applied to the respective geographical location records. At step 330, the method includes the processing system grouping duplicate geographical locations. The processing system may combine the weightings of the geographical locations to form a merged geographical location record.

At step 335, the method includes the processing system storing data indicative of the one or more geographical hierarchies associated with the digital object in a data store. For example, the processing system may determine that the geographical hierarchies for Sydney and the United Kingdom are considered relevant to the particular digital content object The weightings associated with the geographical locations may also be stored in the data store indicative of the relevance of the geographical hierarchy to the digital content object.

At step 340, the method includes the processing system outputting data indicative of the one or more geographical hierarchies indicative of one or more geographical locations associated with the digital content object. For example, the processing system may output an ordered list of geographical hierarchies, wherein the list is ordered according to the weighting determined by the processing system above. In one form, a request may be received, via an API call, to the processing system, wherein the processing system processes the request and outputs the relevant data in response to the request. It will be appreciated that only a portion of the geographical hierarchies may be output.

Referring to Figure 4 there is shown a more specific example of determining a degree of relevance of one or more geographic locations to a digital content object.

In particular, Figure 4 shows an example of a digital content object which is retrieved by the processing system 100 from a webhost processing system via network such as the Internet. The digital content object 400 can be provided in the form of a website including a number of lines of source code in the form of XHTML, although other computer programming languages may be present in the source code. In one form, the digital content object 400 is a social media object such as a blog or an entry in a blog; Upon obtaining the source code for the digital content object 400, the processing system 1 00 extracts geographical indicators 510 in the form of textual portions present in the source code and generates a first table 500, as shown in Figure 5. The first table 500 includes a number of records 520 for the corresponding geographical indicators 510 indicative of the geographical locations.

The processing system 100 then classifies each geographical location in each record in the first table 500 according to the geographical location type 600 (i.e, suburb, city, country, etc). The processing system 100 may use the first, data store to classify each geographic indicator 510 according to a geographical location type 600.

The processing system 100 then retrieves the geographical hierarchy 610, from the second data store, for each geographical indicator and inserts the corresponding geographical liierarchy into each record in the first table. Each geographical hierarchy is indicative of the respective geographical location for the respective geographical indicator. For example, for the geographical indicator of "Bondi" which was . extracted from the source code results in the geographical hierarchy of "Bondi, Sydney, New South Wales, Australia" being retrieved from the second data store by the processing system 100 and then being associated with the respective record in the first table 500, The processing system also determines if the geographical indicator is an exact match to the geographical location based upon the geographical hierarchy, an alias of a geographical hierarchy (i.e. UK is an alias of United Kingdom), or a homonym. The processing system stores match tyj e data 520 for each record in the first table 500. The processing system 100 then begins to assign a weight for each geographical indicator based upon the geographical location type 520 of the geographical location. In particular, the processing system 100 may have stored in memory a set of weight data 700 which includes a set of weights for geographical location types, The weight data weights the geographical indicator according to the position which the geographical location appears in the geographic hierarchy . Specifically, as shown in Figure 7 there is shown an example of a set of weight data 700 which is used to weight each geographical indicator according to the geographical location type 520. For example, the geographical indicator of "Bondi" is a suburb and is therefore assigned a weighting of 2. In an alternate example, the geographical indicator of "UK" which the processing determines is an alias for "United Kingdom", wherein "United Kingdom" is a country and therefore the respective record is assigned, by the processing system, a weighting of 5 according to the set of weight data 700 illustrated in Figure 7. If a geographic location indicated by a geographic indicator has been identified as a homonym, the processing system 100 assigns the lowest weight to the respective geographic location based on the set of weight data 700. The processing system 100 then generates a second table 800 indicative of other geographic indicators associated with the digital content object 400. In particular, it will be appreciated that only textual content contained in the textual portion of the digital content object has been analysed thus far. In one form, the processing system extracts links (i.e. hyperlinks) to other digital content objects from the source code of the digital content object 400, wherein each link is assigned a record in the second table 800 as shown in Figure 8. The processing system 100 then retrieves from memory, if possible, the most relevant geographic hierarchy associated with each linked digital content object. Each record in the second table 800 is also weighted according to the set of weight data 700 exemplified in Figure 7.

The processing system then merges the first table 500 with the second table 800 based upon the geographic hierarchies of the respective geographic locations, as shown in Figure 9, to form a third table 900. In particular, each unique geographical hierarchy is extracted from the first and second table to form a unique record in the third table as shown in Figure 9. Specifically, a number of duplicate references are contained for the same geographical location in the first and second table, therefore the records of the first and second tables arc combined so that only unique geographical hierarchies indicative of unique geographical locations are present in the third table. Each geographical hierarchy in either the first or second table which share a degree of commonality with a unique geographical hierarchy in the third table is assigned to the respective record.

For example, the geographical hierarchy "Bondi, Sydney, New South Wales, Australia" is extracted from multiple entries in the first and second table 500, 800 and forms a record in the third table. Each record in the first or second table which shares a degree of commonality with the geographical hierarchy of "Bondi, Sydney, New South Wales, Australia" is assigned to the respective record in the third table. Each weight associated with each record from the first and second table. 500, 800 is assigned to the respective record in the third table 900 in the event that a degree of commonality existed, For example, geographic locations having geographic hierarchies containing "Sydney, New South Wales, Australia", "New South Wales, Australia" or "Australia" can be associated with the geographical hierarchy for "Bondi" in the third table 900.

The processing system 100 then calculates using a relevancy rule stored in memory a relevancy score for each record in the third table 900 based upon the weights for each geographical location assigned to the respective record. In one form, the weights of each assigned geographical location for a geographical hierarch record in the third table can be multiplied together to generate the relevancy score. For example, the record for "Bondi, Sydney, New South Wales, Australia" in the third table 900 has associated therewith a plurality of geographical locations which have assigned weights of 2, 2, 2, 1 , 2, 2, 3, 4 based upon the set of weight data earlier applied. These weights can be multiplied together (i.e. 2 x 2 x 2 x 1 x 2 x 2 x 3 x 4 = 384) to form a relevancy score for the geographical hierarchy record in the third table. This process is repeated for each geographical hierarchy record in the third table 900. It will be appreciated that many different forms of relevancy rule can be used to calculate the relevancy score, however the above example lias been used for clarity. The processing system 100 can then rank and store the records of the geographical hierarchy records in the third table 900 according to the associated relevancy score as shown in Figure 10. The' one or more geographical hierarchies associated with one or more corresponding geographic locations having a degree of relevance to the digital content object can then be output via an output device of the processing system 100 or transferred to another processing system upon request. As can be seen from Figure 9, the geographical location of "Bondi, Sydney, New South Wales, Australia" is considered the most relevant geographical location for the digital content object of Figure 4. It will be appreciated that only a portion of the geographical hierarchies which are relevant to digital content object may be output by the processing system 100. For example, a predefined threshold may be Stored in the processing system 100 which causes the processing system 100 to filter any geographical hierarchy record from the third table which fails to satisfy the predefined threshold, Whilst geographical indicators for a digital content object can be identified based upon textual portions within textual content of the digital content object and based upon one or more links to other digital content objects (i.e. hyperlinks to other websites) for the digital content object, it will be appreciated that other geographical indicators may also be used by the processing system to identify one or more geographical locations which are relevant to a digital content object.

In particular, the processing system may identify at least one of the geographical indicators from a country or region code of a URL associated with the digital content object. For example, if the digital content object was accessible at www,. YYZ.com , au then the '.au' portion of the URL for the digital content object can be used by the processing system to identify. Australia as a geographical indicator for the digital content object.

Additionally or alternatively, the processing system 100 can identify at least one of the geographical indicators by obtaining an address of an author of the digital content object. For example, if the digital content object is a blog which indicates a name for the author, the processing system 100 may be configured to query one οτ more other processing systcms in data communication with the processing system 100 to identify the address of the author. For example, a social media server processing system may be queried by the processing system 100 to retrieve an address of the author of the author. The address of the author can then be used by the processing system 100 as a geographical indicator for processing as described ab^'ove.

It will be appreciated that the above described method can be performed for a plurality of digital content objects for indexation within a data store. For example, the processing system 100 may be configured to index each blog on a social media processing system. The processing system 1 00 can be configured to index the plurality of digital content objects by storing a corresponding plurality of records in memory of the processing system 100, wherein each record is indicative of an identity of the respective digital content object (such as the URL of the digital content object), the geographical locations for the respective digital content object and the respective relevancy scores for the geographical locations. Additionally, keywords that are present in each digital content object may be extracted by the processing system and stored the respective record. It will be appreciated that alternate storage of records can be achieved.

Due to a plurality of digital content objects being Indexed in a data store, it is possible to then allow for a user to request a search of the indexed digital content objects. In particular, the processing system may be configured to receive a search query for conducting a search of the digital content objects indexed in the data store, wherein the search er at least partially includes a geographical location. The processing system can then conduct, using the search query, the search of the plurality of digital content objects indexed in the data store. The processing system then returns, to the user, one or more digital content objects indexed in the data store which at least partially satisfy the search query. The digital content objects of the search results are at least partially ranked according to the respective relevancy scores relative to the geographical location of the search query.

The relevancy rule that is applied by the processing system can optionally be configured according to population data associated with geographical locations, In particular, the relevancy rule can be configured to more heavily weight geographical hierarchy records based upon the population of the associated geographical location. It will be appreciated that the above method, processing system and computer program product has relevance to a number of technologies such as search engines, Another particular field of application relates is market research, wherein the geographical location for digital content which includes textual portions indicative of a brand name can be identified, thereby identifying geographical strength, or weakness, of the brand recognition. In one form, graphic may be generated for brand recognition, wherein the graphic includes a map indicative of the geographic locations associated with digital content considered relevant to the respective brand. The graphic may be generated using the data stored by the processing system at step 345 and executing requests to output data as discussed at step 350. In one form, the map may an computer interactable map having geographical locations plotted associated with the brand.

The above embodiments may take the form of an entirely hardware embodiment, an entirely software embodiment, firmware, or an embodiment combining software and hardware aspects.

Many modifications will be apparent to those skilled in the art without departing from the scope of the present invention.

Claims

1 , A method for determining a degree of relevancy of one or more geographical locations to a digital content object, wherein the method includes, in a processing system: identifying, for a digital content object, a plurality of geographical indicators to a plurality of geographical locations;

obtaining, from a data store, a plurality of geographical hierarchies for the plurality of geographical locations; and

calculating, for each geographical location and using a relevancy rule, a relevancy score indicative of the degree of relevancy of the respective geographical location to the digital content object, wherein each relevancy score is calculated based at least partially upon a degree of commonaJity between the respective geographical hierarchy with a remainder of the geographical hierarchies.

2, The method according to claim 1 , wherein the method includes identifying at least one of the geographical indicators from textual content of the digital contenr object.

3. The method according to claim 1 or 2, wherein the method includes identifying at least one of the geographical indicators from one or more links to other digital content objects.

4. The method according to any one of claims 1 to 3, wherein the method includes identifying at least one of the geographical indicators from a country code of a URL associated with the digital content object.

5. The method according to any one of claims 1 to 4, wherein the method includes identifying at least one of the geographical indicators by obtaining an address of an author of the digital content object.

6. The method according to any one of claims 1 to 5, wherein the method includes:

7. The method according to any one of claims 1 to 6, wherein the digital content object is a social media object.

8. The method according to any one of claims 1 to 7 , wherein the method is performed upon a plurality of digital content objects for indexation within a data store.

9. The method according to claim 8, wherein the method includes indexing the plurality of digital content objects by storing a corresponding plurality of records in the data store, wherein each record is indicative of the respective digital content object, the geographical locations for the respective digital content object and the respective relevancy scores for the geographical locations.

10. The method according to claim 9, wherein the method includes:

conducting, using the search query, the search of the plurality of digital content objects indexed in the data store; and

returning, to the user, one or more digital content objects indexed in the data store which at least partially satisfy the search query, wherein the digital content objects of the search results are at least partially ranked according to the respective relevancy scores relative to the geographical location of the search query.

^"

1 1 . A processing system for determining a degree of relevancy of one or more geographical locations to a digital content object, wherein the processing system is configured to: idemify, for a digital content object, a plurality of geographical indicators to a plurality of geographical locations;

12. The processing system according to claim 1 1 , wherein the processing system is configured to identify at least one of the geographical indicators from textual content of the digital content object.

13. The processing system according to claim 1 1 or 1 2, wherein the processing system is configured to identify at least one of the geographical indicators from one or more links to other digital content objects.

14. The processing system according to any one of claims 1 1 to 13, wherein the processing system is configured to identify at least one of the geographical indicators from a country code of a URL associated with the digital content object.

15. The processing system according to any one of claims 1 1 to 14, wherein the processing system is configured to identify at least one of the geographical indicators by obtaining an address of an author of the digital content object.

16.. The processing system according to any one of claims U to 15, wherein the processing system is configured to:

classify each geographical location according to a geographical location type; and use a set of weight data to further calculate the relevancy score tor each geographical location further according to a geographical location type of the respective geographical location,

17. The processing system according to any one of claims 1 1 to 16, wherein the digital content object is a social media object .

18. The processing system according (o any one of claims Π to 17, wherein the processing system is configured to determine a degree of relevancy of one or more geographical locations for a plurality digital content objects for indexation in the data store.

19. The processing system according to claim 18, wherein the processing system is configured to index the plurality of digital content objects by storing a corresponding plurality of records in the data store, wherein each record is indicative of the respective digital content object, the geographical locations for the respective digital content object and the respective relevancy scores for the geographical locations.

20. The processing system according to claim 19, wherein the processing system is configured to:

return, to the user, one or more digital content objects indexed in the data store which at least partially satisfy the search query, wherein the digital content objects of the search results are at least partially ranked according to the respective relevancy scores relative to the geographical location of the search query.

21 . A computer program product for determining a degree of relevancy of one or moTe geographical locations to a digital content object, wherein the computer program product includes executable instructions configuring a processing system to: identify, for a digital content object, a plurality of geographical indicators to a plurality of geographical locations;

22. The computer program product according to claim 21 , wherein the executable instructions of the computer program product configure the processing system to identify at least one of the geographical indicators from textual content of the digital content object.

23. The computer program product according to claim 1 1 or 12, wherein the executable instructions of the computer program product configure the processing system to identify at least one of the geographical indicators from one or more links to other digital content objects.

24. The computer program product according to any one of claims 1 1 to 13, wherein the executable instructions of the computer program product configure the processing system to identify at least one of the geographical indicators from a country code of a URL associated with the digital content object.

25. The computer program product according to any one of claims 1 1 to 14, wherein the executable instructions of the computer program product configure the processing system to identify at least one of the geographical indicators by obtaining an address of an author of the digital content object.

26. The computer program product according to any one of claims 1 1 to 1 5, wherein the executable instructions of the computer program product configure the processing sysiem lb:

classify each geographical location according to a geographical location type; and use a set of weight data to further calculate the relevancy score for each geographical location further according to a geographical location type of the respective 5 geographical location.

27. The computer program product according to any one of claims 1 1 to 16, wherein the digital content object is a social media object.

1 0 28. The computer program product according to any one of claims 1 1 to 1 7, wherein the executable instructions of the computer program product configure the processing system to determine a degree of relevancy of one or more geographical locations for a plurality digital content objects for indexation in the data store.

15 29. The computer pro ram product according to claim 18, wherein the executable instructions of the computer program product configure the processing system to index the plxirality of digital content objects by storing a corresponding plurality of records in the data store, wherein each record is indicative of the respective digital content object, the geographical locations for the respective digital content object and the respective relevancy

20 scores for the geographical locations.

30. The computer program product according to claim 19, wherein the executable instructions of the computer program product configure the processing system to:

receive, from a user, a search query for conducting a search of the digital content 25. objects indexed in the data store, wherein the search query at least partially includes a geographical location;

return, to the user, one or more digital content objects indexed in the data store 30 which at least partially satisfy the search query, wherein the digital content objects of the search results are at least partially ranked according to the respective relevancy scores relative to the geographical location of the search query.