CN102184204A - Auto fill method and system of intelligent Web form - Google Patents
Auto fill method and system of intelligent Web form Download PDFInfo
- Publication number
- CN102184204A CN102184204A CN 201110107333 CN201110107333A CN102184204A CN 102184204 A CN102184204 A CN 102184204A CN 201110107333 CN201110107333 CN 201110107333 CN 201110107333 A CN201110107333 A CN 201110107333A CN 102184204 A CN102184204 A CN 102184204A
- Authority
- CN
- China
- Prior art keywords
- candidate value
- name
- standard name
- resources bank
- filling
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Abstract
The invention discloses an auto fill method and a system of an intelligent Web form. The method comprises the steps of 1) extracting the tag names in the form and normalizing the tag names into the standardized names of a semantic library; 2) searching a resource library according to the standardized names and selecting a candidate value for filling the form; and 3) selecting the candidate value for filling the form. The system comprises the semantic library used for storing the mapping collection from tag names to the standardized names, the resource library used for storing the collection of 'tag name- candidate value', a normalizing module used for extracting the tag names in the form and normalizing the tag names to the standardized names of the semantic library, a retrieval module used for searching the resource library according to the standardized names and selecting the candidate value, and a form filling module used for filling the form according to the candidate value selected. The method and system can reduce the work load on information input in the form filling process for the user, relieve the user load and promote the user experience.
Description
Technical field
The present invention relates to a kind of list fill method and system, particularly the content of filling in does not in the past need the Research on Automatic Filling and the system of typing once more in new table.
Background technology
Along with popularizing of internet, E-Government, ecommerce and various office automation have obtained vigorous growth, and a lot of users need to carry out all kinds of issued transaction by filling in a large amount of lists, as making a report on plan, report business, data acquisition etc.
The content of list is made up of the form fields that prompting will be imported the label of content and need the user to import following closely usually.As text box, check box, radio box, drop-down choice box etc.The user the data entry form single domain after, submit server process again to.And these lists often comprise a lot of repeated content, and the user need fill in unit information and the duplicate contents such as personal information of oneself repeatedly.For example, although the job applicant has had the resume of form such as Word document, need carry out when recruitment website is filled in personal information a large amount of duplicating, manual operations such as stickup, fill name, sex, home address, tens of contents such as education experience.The user need repeat same work at different recruitment websites, waste time and energy, and makes mistakes easily.
There are some products and technology to reduce and make a report on the middle work that repeats on the internet.For example, Autoformer can collect essential informations such as user name, address, phone in registration, the simple list of login, and the user fills when run into similar list next time automatically.When wherein new table was identical with the historical form label, the data of label correspondence of the same name were remembered and are reused.When label not simultaneously, for example, " postcode " and " postcode " need to fill identical, this situation can't be filled automatically.In the transacter based on the reality of internet, list is very universal, and the data complexity, and these simple filling techniques automatically can't solve.
Summary of the invention
The purpose of this invention is to provide and a kind ofly can automatically identify semantic identical repeating part, solve duplicate contents problem intelligent web list Research on Automatic Filling and the system in the list of filling in.
Technical scheme of the present invention is:
A kind of intelligent web list Research on Automatic Filling comprises semantic base and resources bank, and this method may further comprise the steps:
1) extracts tag name in the list, be normalized to the standard name of described semantic base;
2) search described resources bank according to described standard name, select described candidate value to fill in a form;
3) select described candidate value to fill in a form.
Further, the described tag name of described semantic base file probability is to the mapping probability of described standard name.
Further, the establishment step of described resources bank is:
21) extraction " tag name-candidate value " is right from reference documents or historical form padding data;
22) according to described semantic base that " tag name-candidate value " is right to being normalized to " standard name-candidate value ";
23) with described " standard name-candidate value " to being stored in described resources bank.
Further, the establishment step of described resources bank is:
201) extraction " tag name-candidate value " is right from reference documents or historical form padding data;
202) according to described semantic base that " tag name-candidate value " is right to being normalized to " standard name-candidate value-confidence level ";
203) with described " standard name-candidate value-confidence level " to being stored in described resources bank.
Further, described step 202) and step 203) between be provided with step 204), it is right less than " standard name-candidate value-confidence level " that filter threshold value to be used to delete confidence level.
A kind of intelligent web list auto-filling system is characterized in that, comprising:
Semantic base, the tag name that is used to store is to the mapping set of standard name;
Resources bank is used for storage " standard name-candidate value " right set;
The normalization module is used for extracting the tag name of list, is normalized to the standard name of described semantic base;
Retrieval module is used for searching resources bank according to described standard name, chooses candidate value;
The module of filling in a form is used for filling in a form according to the described candidate value of selecting.
Further, described semantic base is stored the mapping probability of described tag name to described standard name.
Further, described resources bank is stored " standard name-candidate value-confidence level " right set, is provided with the filtration threshold value of confidence level.
The invention has the beneficial effects as follows: by the mapping relations of semantic base, tag name in the form is carried out normalized, and from resources bank, choose candidate value and fill in a form automatically, by this system and method, user's input is minimized, alleviate the burden that the user repeats to import, strengthened the user experience effect.The setting of the confidence level of resources bank also makes this system can learn user's preference, makes the result who fills in a form automatically more meet user's demand.
Description of drawings
Fig. 1 is list intelligence Research on Automatic Filling synoptic diagram of the present invention;
Fig. 2 is the implementing procedure figure of the embodiment of the invention;
Fig. 3 is a invention process case new table master drawing;
Fig. 4 is the automatic filling effect figure of the invention process case new table.
Embodiment
Below in conjunction with accompanying drawing the specific embodiment of the present invention is described in detail.
As shown in Figure 1, a kind of intelligent web list Research on Automatic Filling comprises semantic base and resources bank, and this method may further comprise the steps:
1) extracts tag name in the list, be normalized to the standard name of described semantic base;
2) search described resources bank according to described standard name, select described candidate value to fill in a form;
3) select described candidate value to fill in a form.
A kind of intelligent web list auto-filling system is characterized in that, comprising:
Semantic base, the tag name that is used to store is to the mapping set of standard name;
Resources bank is used for storage " standard name-candidate value " right set;
The normalization module is used for extracting the tag name of list, is normalized to the standard name of described semantic base;
Retrieval module is used for searching resources bank according to described standard name, chooses candidate value;
The module of filling in a form is used for filling in a form according to the described candidate value of selecting.
Fig. 2 is the implementing procedure figure of the embodiment of the invention, specifies as follows:
Definition semantic base S0, identical with solving in the list content, but the different problems that produce of the used vocabulary of tag name, for example: new table requires to fill in the form fields of label " postcode " by name, and history is made a report in the record data of having only " postcode ", semantic base is used for realizing both normalizings, is about to tag name " postcode " and is mapped on the standard name " postcode ".The present invention adopts semantic base to come the set of storage tags name to the mapping of standard name.Semantic base possesses following feature:
1) tag name can be " standard name tag name 1| tag name 2| ... " to the mapping structure of standard name, as: " phone number " " mobile phone | mobile phone | Mobile Phone "; Also can be " standard name tag name 1 ", " standard name tag name 2 ", the set of " standard name ... ".
2) tag name can be with probability to the mapping of standard name.For example: " office telephone telephone number-[40%] ", " mobile phone telephone number-[30%] " expression history is made a report in the record, and " telephone number " has 40%, 30% situation respectively is " office telephone " and " mobile phone ".
3) tag name is to support the regular expression form.For example: 1-3 space can occur between " posting * [1-3] compiles " expression postcode.
4) tag name can manual mode be set up and is safeguarded to the mapping of standard name in the semantic base, the method that also can use machine learning such as decision tree, Bayes, SVM, hidden Markov model from history fill record middle school acquistion to.
The net result of resources bank structure S1 is resources bank S3, its objective is to filling in new table S2 to do the data preparation.Be not to fill in new table S2 all will carry out resources bank structure S1 before at every turn.Have only and add fashionable when new reference documents or the new data of making a report on, just be necessary to re-construct resources bank, be used for constructing resources bank reference documents and historical make a report on record must be about the active user, because other people data do not have reference value to the active user.The concrete implementation step of S1 is:
Select reference documents S11 or historical form padding data S12.The multiplex data source can be that history is made a report on list record S12, also can be the reference documents S11 of forms such as Word, Excel, Text.For example, during recruitment website registration personal information, the resume document that just can use oneself is as the multiplex data source, so that realize filling in automatically, this module of the present invention will ask the user to upload resume as the multiplex data source.And for example: in transacters such as monthly magazine, historical monthly magazine data are exactly the multiplex data source, wherein, repeating parts such as unit information will be filled in making a report on from now on automatically, and module of the present invention will select active user's history to make a report on record as the multiplex data source.
The extraction S13 that " tag name-data value " is right; Its concrete steps are:
When the multiplex data source of selecting is that history is when making a report on list, according to active user's identity information or the project label under the current list, handle the background data base of list correspondence, field name and the field value of selecting the active user to fill in a form, right as " tag name-data value ".
When the multiplex data source of selecting is Word document list data or Excel document list data, at first, detect the position that tag name occurs in the reference documents according to the tag name in the semantic base, judge the distribution situation of label in form.Secondly, summarizing that label distributes is to embark on journey or becomes column distribution, and embarking on journey distribution is meant that the content of full line in the form is tag name more than 50%; Become column distribution to be meant that the content of a permutation in the form is tag name more than 50%.Once more, the data of the next line correspondence of the tag name that will embark on journey are as value.As: lastrow is " name | sex | age " in the form, next behavior " Zhang San | the man | 25 " (wherein " | " is cell separator in the table), then three " tag name-data values " of structure " name-Zhang San ", " sex-man ", " age-25 " are right.To becoming the label of row, the data of next column are as value.As: in the form lastrow be " name | Zhang San | sex | the man ", the situation of next behavior " age | 25| nationality | the Chinese ", find that wherein first row and the 3rd are classified tag name as, four " tag name-data values " of then constructing " name-Zhang San ", " sex-man ", " age-25 ", " nationality-Han " are right.If the multiplex data source is the word document or the text document of free text, it is right then to utilize in the natural language processing information extraction technique to obtain one group " tag name-data value ".
Semantic label normalization S14.According to semantic base S0, the tag name of " tag name-data value " centering that step S13 is obtained is normalized into standard name, and with the probability propagation in the semantic base to " standard name-candidate value " centering.For example, establishing has Semantic mapping " office telephone telephone number-[40%] " in the semantic base, " mobile phone telephone number-[20%] ", " mobile phone mobile phone-[30%] " three semantic knowledges." tag name-data value " learnt by step S13 is to there being " mobile phone-1111 ", " telephone number-2222 ", " mobile phone-1111 ", carry out normalized " mobile phone-1111-[1.0] " arranged, " office telephone-2222-[0.4] ", " mobile phone-2222-[0.2] ", " mobile phone-1111-[0.3] " four " standard name-candidate value-[probability] " are right.
By normalization label statistics " standard value-candidate value " S15.All " standard name-candidate value-[probability] " after the statistics implementation step S14 are right, add up by " standard name " and candidate value grouping.After the statistics with " standard name-candidate value-[probability] " to being reassembled as " standard name-candidate value-confidence level " (confidence level is described as current " standard name-candidate value " to accounting for all " standard name-candidate values " of the same name number percent to sum, and wherein confidence level is defined as the logarithm value of weighted frequency).For example: establishing " standard name-candidate value-[probability] " tlv triple that step S103 obtains has " mobile phone-1111-[1.0] ", and " office telephone-2222-[0.4] ", " mobile phone-2222-[0.2] ", " mobile phone-1111-[0.3] ".Then the weighted frequency of " mobile phone-1111 " is 1.3, and the weighted frequency of " office telephone-2222 " is 0.4, and the weighted frequency of " mobile phone-2222 " is 0.2.Therefore, their confidence level is respectively ln (1+1.3), ln (1+0.4), ln (1+0.2).
Screening part " standard value-candidate value ", structure resources bank S16.The result screens according to confidence level with implementation step S15 gained, constitutes data bank of the present invention.The screening principle is: to the standard name after each normalization, get confidence level greater than user-defined part, perhaps the N of confidence level maximum (is 1-3 as the N value).For fear of noise and contingency, the suggestion many mistakes of frequency candidate value once just deposits resources bank in.The tlv triple of above-mentioned " label-value-confidence level " is stored in the resources bank for future referencely, for improving retrieval rate, can consider to set up Hash table and so on index.
The ultimate principle of filling in new table S2 as Fig. 2 is retrieve resources storehouse S3, obtains the candidate value of each tag name in the new table, if such value exists, then selects the value of confidence level maximum to fill out corresponding form fields in advance, finishes intelligence and fills in a form automatically.Concrete implementation step is described as:
Extract the tag name S22 of new table one by one; Fig. 3 is a invention process case new table master drawing, and the tag name that can extract has " name ", " sex ", " personal preference ".
Be new table tag name normalization S23, obtain the standard name of each tag name correspondence.According to semantic resources bank S0, with the label normalization of new table, its purpose is exactly to make " tag name " name in the new table consistent with " standard name-candidate value " right " standard name " in the S3 data bank.During for next step S24 retrieve resources storehouse S3, key word can accurately mate, and this has guaranteed that also the present invention is in the accuracy of discerning automatically on " tag name ".For example: suppose that label in the semantic resources bank " hobby " is tag name a " personal preference's " standard name, so, " personal preference " in the new table is normalized to standard name " hobby ".
Utilize standard name retrieve resources storehouse S24, for new table obtains one group of candidate value.With the new table standard name after the normalization as key word, retrieve resources storehouse S3 finds the operational candidate value of this standard name, at this, the user can set the number of the selecting candidate value list of filling in a form in advance once more, and " standard name-candidate value " that guarantees only to get higher confidence level is to as candidate value.For example: threshold value is set gets the highest 3 of confidence level,, also have only confidence level the highest 3 as with reference to values even when certain label has a plurality of candidate value in S3.
With the candidate value of confidence level maximum, the S25 that fills in a form in advance automatically, other candidate values can be listed in the back with text mode, form fields of filling out in advance for reference, and replenish those parts of not filling out.The candidate value of the new table that obtains according to step S24, the list of filling in a form in advance automatically.As Fig. 4, when selecting candidate value to fill in list automatically, divide following situation to handle:
As form fields is text box, and with directly inserting of confidence level maximum, other candidate values are presented at the back with text label;
If form fields is radio box or drop-down list, the confidence level ordering that then Total Options is provided according to resources bank S3, select confidence level maximum wherein as selected value;
If form fields is the multiselect frame, then the Total Options that will appear in the candidate value are all chosen.
The user revises new table S26; The user revises single label field of filling in a form in advance automatically, and replenishes those and can not realize automatic part of filling out in advance.
Submit to new table S27 and common fill in list similarly submission form handle to server program.The new table data can be used as new data and deposit resources bank in, can be used as the multiplex data source that follow-up intelligence is filled.
Claims (9)
1. an intelligent web list Research on Automatic Filling comprises semantic base and resources bank; It is characterized in that, may further comprise the steps:
1) extracts tag name in the list, be normalized to the standard name of described semantic base;
2) search described resources bank according to described standard name, select described candidate value to fill in a form;
3) select described candidate value to fill in a form.
2. a kind of intelligent web list Research on Automatic Filling according to claim 1 is characterized in that: the described tag name of described semantic base file probability is to the mapping set of described standard name.
3. a kind of intelligent web list Research on Automatic Filling according to claim 1, it is characterized in that: the establishment step of described resources bank is:
21) extraction " tag name-candidate value " is right from reference documents or historical form padding data;
22) according to described semantic base that " tag name-candidate value " is right to being normalized to " standard name-candidate value ";
23) with described " standard name-candidate value " to being stored in described resources bank.
4. a kind of intelligent web list Research on Automatic Filling according to claim 2, it is characterized in that: the establishment step of described resources bank is:
201) extraction " tag name-candidate value " is right from reference documents or historical form padding data;
202) according to described semantic base that " tag name-candidate value " is right to being normalized to " standard name-candidate value-confidence level ";
203) with described " standard name-candidate value-confidence level " to being stored in described resources bank.
5. a kind of intelligent web list Research on Automatic Filling according to claim 4 is characterized in that: described step 202) and step 203) between be provided with step 204), it is right less than " standard name-candidate value-confidence level " that filter threshold value to be used to delete confidence level.
6. an intelligent web list auto-filling system is characterized in that, comprising:
Semantic base, the tag name that is used to store is to the mapping set of standard name;
Resources bank is used for storage " standard name-candidate value " right set;
The normalization module is used for extracting the tag name of list, is normalized to the standard name of described semantic base;
Retrieval module is used for searching resources bank according to described standard name, chooses candidate value;
The module of filling in a form is used for filling in a form according to the described candidate value of selecting.
7. according to a kind of intelligent web list auto-filling system of claim 5, it is characterized in that: described semantic base is stored the mapping probability of described tag name to described standard name.
8. according to a kind of intelligent web list auto-filling system of claim 5 or 6, it is characterized in that: described resources bank storage " standard name-candidate value-confidence level " right set.
9. according to a kind of intelligent web list auto-filling system of claim 7, it is characterized in that: described resources bank is set with the filtration threshold value of confidence level.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN 201110107333 CN102184204B (en) | 2011-04-28 | 2011-04-28 | Auto fill method and system of intelligent Web form |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN 201110107333 CN102184204B (en) | 2011-04-28 | 2011-04-28 | Auto fill method and system of intelligent Web form |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN102184204A true CN102184204A (en) | 2011-09-14 |
| CN102184204B CN102184204B (en) | 2013-03-13 |
Family
ID=44570381
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN 201110107333 Active CN102184204B (en) | 2011-04-28 | 2011-04-28 | Auto fill method and system of intelligent Web form |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN102184204B (en) |
Cited By (25)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103324661A (en) * | 2013-04-10 | 2013-09-25 | 广东全通教育股份有限公司 | Data search and automatic filling method and system based on user habits |
| CN103559216A (en) * | 2013-10-16 | 2014-02-05 | 华为技术有限公司 | Method and device for inputting personal information |
| CN103581212A (en) * | 2012-07-18 | 2014-02-12 | 百度在线网络技术（北京）有限公司 | Automatic form filling method, system and device based on cloud analysis |
| CN103745339A (en) * | 2013-12-08 | 2014-04-23 | 王美金 | Method and system for rapidly generating banking service application |
| CN104267804A (en) * | 2014-09-15 | 2015-01-07 | 联想(北京)有限公司 | Information input method and electronic device |
| CN105205132A (en) * | 2015-09-15 | 2015-12-30 | 小米科技有限责任公司 | Card handling data processing method and device |
| CN105243265A (en) * | 2015-09-16 | 2016-01-13 | 西部天使（北京）健康科技有限公司 | Automatic follow-up method and system |
| CN105577681A (en) * | 2016-01-18 | 2016-05-11 | 郑海友 | Personal information filling method through fingerprint, face and eyeball identification |
| CN106844319A (en) * | 2016-12-21 | 2017-06-13 | 泰康保险集团股份有限公司 | Report form generation method and device |
| CN106933783A (en) * | 2015-12-31 | 2017-07-07 | 远光软件股份有限公司 | A kind of method and device on the intelligent extraction date from text |
| CN107145481A (en) * | 2017-05-05 | 2017-09-08 | 恒生电子股份有限公司 | Electronic equipment, storage medium, web form fill method and device |
| CN107526678A (en) * | 2016-06-22 | 2017-12-29 | 平安科技（深圳）有限公司 | The method of testing and device of web application |
| CN107798082A (en) * | 2017-10-16 | 2018-03-13 | 广东欧珀移动通信有限公司 | A kind of processing method and processing device of file label |
| CN108595393A (en) * | 2018-01-11 | 2018-09-28 | 太原理工大学 | A kind of automatic form filling method and device |
| CN108921460A (en) * | 2018-09-20 | 2018-11-30 | 郑州云海信息技术有限公司 | The management method and device of Network Traffic journey |
| TWI645351B (en) * | 2015-03-27 | 2018-12-21 | 日商日本精工股份有限公司 | Product replacement support system |
| CN109145092A (en) * | 2017-06-15 | 2019-01-04 | 阿里巴巴集团控股有限公司 | A kind of database update, intelligent answer management method, device and its equipment |
| CN109739864A (en) * | 2019-01-24 | 2019-05-10 | 易保互联医疗信息科技（北京）有限公司 | The acquisition of people society data and sharing method, computer storage medium and computer equipment |
| CN109800410A (en) * | 2017-11-17 | 2019-05-24 | 百度在线网络技术（北京）有限公司 | A kind of list generation method and system based on online chatting record |
| CN110046942A (en) * | 2019-04-25 | 2019-07-23 | 秒针信息技术有限公司 | A kind of method and device for launching data processing |
| CN111177236A (en) * | 2019-12-03 | 2020-05-19 | 泰康保险集团股份有限公司 | Medical care scene-based scale generation method, system, device and medium |
| CN111292820A (en) * | 2020-05-08 | 2020-06-16 | 成都金盘电子科大多媒体技术有限公司 | Medical informatization data standard system rapid construction system, method and server |
| US11494551B1 (en) * | 2021-07-23 | 2022-11-08 | Esker, S.A. | Form field prediction service |
| CN117010349A (en) * | 2023-09-28 | 2023-11-07 | 杭州今元标矩科技有限公司 | Form filling method, system and storage medium based on neural network model |
| CN117391456A (en) * | 2023-11-27 | 2024-01-12 | 浙江南斗数智科技有限公司 | Village management method and service platform system based on artificial intelligence |
Families Citing this family (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US9461983B2 (en) | 2014-08-12 | 2016-10-04 | Danal Inc. | Multi-dimensional framework for defining criteria that indicate when authentication should be revoked |
| US9454773B2 (en) | 2014-08-12 | 2016-09-27 | Danal Inc. | Aggregator system having a platform for engaging mobile device users |
| US10154082B2 (en) | 2014-08-12 | 2018-12-11 | Danal Inc. | Providing customer information obtained from a carrier system to a client device |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2001006416A2 (en) * | 1999-07-19 | 2001-01-25 | Infospace, Inc. | Intelligent mapping of field names in an electronic form with standard field names |
| US6490601B1 (en) * | 1999-01-15 | 2002-12-03 | Infospace, Inc. | Server for enabling the automatic insertion of data into electronic forms on a user computer |
| CN1439133A (en) * | 2000-04-28 | 2003-08-27 | 美国联机股份有限公司 | Method and system for automating internet interactions using recorded data |
| CN1696937A (en) * | 2004-05-12 | 2005-11-16 | 微软公司 | Intelligent autofill |
| EP1777629A1 (en) * | 2005-10-19 | 2007-04-25 | NTT DoCoMo, Inc. | Method and apparatus for automatic form filling |
-
2011
- 2011-04-28 CN CN 201110107333 patent/CN102184204B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6490601B1 (en) * | 1999-01-15 | 2002-12-03 | Infospace, Inc. | Server for enabling the automatic insertion of data into electronic forms on a user computer |
| WO2001006416A2 (en) * | 1999-07-19 | 2001-01-25 | Infospace, Inc. | Intelligent mapping of field names in an electronic form with standard field names |
| CN1439133A (en) * | 2000-04-28 | 2003-08-27 | 美国联机股份有限公司 | Method and system for automating internet interactions using recorded data |
| CN1696937A (en) * | 2004-05-12 | 2005-11-16 | 微软公司 | Intelligent autofill |
| EP1777629A1 (en) * | 2005-10-19 | 2007-04-25 | NTT DoCoMo, Inc. | Method and apparatus for automatic form filling |
Cited By (34)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103581212B (en) * | 2012-07-18 | 2017-03-15 | 百度在线网络技术（北京）有限公司 | Based on the Auto Filling Forms method, system and device that high in the clouds is analyzed |
| CN103581212A (en) * | 2012-07-18 | 2014-02-12 | 百度在线网络技术（北京）有限公司 | Automatic form filling method, system and device based on cloud analysis |
| CN103324661A (en) * | 2013-04-10 | 2013-09-25 | 广东全通教育股份有限公司 | Data search and automatic filling method and system based on user habits |
| CN103559216A (en) * | 2013-10-16 | 2014-02-05 | 华为技术有限公司 | Method and device for inputting personal information |
| CN103745339A (en) * | 2013-12-08 | 2014-04-23 | 王美金 | Method and system for rapidly generating banking service application |
| CN104267804A (en) * | 2014-09-15 | 2015-01-07 | 联想(北京)有限公司 | Information input method and electronic device |
| TWI645351B (en) * | 2015-03-27 | 2018-12-21 | 日商日本精工股份有限公司 | Product replacement support system |
| CN105205132A (en) * | 2015-09-15 | 2015-12-30 | 小米科技有限责任公司 | Card handling data processing method and device |
| CN105243265A (en) * | 2015-09-16 | 2016-01-13 | 西部天使（北京）健康科技有限公司 | Automatic follow-up method and system |
| CN106933783A (en) * | 2015-12-31 | 2017-07-07 | 远光软件股份有限公司 | A kind of method and device on the intelligent extraction date from text |
| CN105577681A (en) * | 2016-01-18 | 2016-05-11 | 郑海友 | Personal information filling method through fingerprint, face and eyeball identification |
| CN107526678A (en) * | 2016-06-22 | 2017-12-29 | 平安科技（深圳）有限公司 | The method of testing and device of web application |
| CN107526678B (en) * | 2016-06-22 | 2020-08-25 | 平安科技（深圳）有限公司 | Web application program testing method and device |
| CN106844319A (en) * | 2016-12-21 | 2017-06-13 | 泰康保险集团股份有限公司 | Report form generation method and device |
| CN107145481B (en) * | 2017-05-05 | 2020-06-09 | 恒生电子股份有限公司 | Electronic equipment, storage medium, and method and device for filling webpage form |
| CN107145481A (en) * | 2017-05-05 | 2017-09-08 | 恒生电子股份有限公司 | Electronic equipment, storage medium, web form fill method and device |
| CN109145092B (en) * | 2017-06-15 | 2022-05-17 | 阿里巴巴集团控股有限公司 | Database updating and intelligent question and answer management method, device and equipment |
| CN109145092A (en) * | 2017-06-15 | 2019-01-04 | 阿里巴巴集团控股有限公司 | A kind of database update, intelligent answer management method, device and its equipment |
| CN107798082A (en) * | 2017-10-16 | 2018-03-13 | 广东欧珀移动通信有限公司 | A kind of processing method and processing device of file label |
| CN107798082B (en) * | 2017-10-16 | 2020-07-17 | Oppo广东移动通信有限公司 | File label processing method and device |
| CN109800410A (en) * | 2017-11-17 | 2019-05-24 | 百度在线网络技术（北京）有限公司 | A kind of list generation method and system based on online chatting record |
| CN108595393A (en) * | 2018-01-11 | 2018-09-28 | 太原理工大学 | A kind of automatic form filling method and device |
| CN108921460A (en) * | 2018-09-20 | 2018-11-30 | 郑州云海信息技术有限公司 | The management method and device of Network Traffic journey |
| CN109739864B (en) * | 2019-01-24 | 2021-03-23 | 易保互联医疗信息科技（北京）有限公司 | Human-social data acquisition and sharing method, computer storage medium and computer equipment |
| CN109739864A (en) * | 2019-01-24 | 2019-05-10 | 易保互联医疗信息科技（北京）有限公司 | The acquisition of people society data and sharing method, computer storage medium and computer equipment |
| CN110046942A (en) * | 2019-04-25 | 2019-07-23 | 秒针信息技术有限公司 | A kind of method and device for launching data processing |
| CN111177236A (en) * | 2019-12-03 | 2020-05-19 | 泰康保险集团股份有限公司 | Medical care scene-based scale generation method, system, device and medium |
| CN111292820B (en) * | 2020-05-08 | 2020-08-21 | 成都金盘电子科大多媒体技术有限公司 | Medical informatization data standard system rapid construction system, method and server |
| CN111292820A (en) * | 2020-05-08 | 2020-06-16 | 成都金盘电子科大多媒体技术有限公司 | Medical informatization data standard system rapid construction system, method and server |
| US11494551B1 (en) * | 2021-07-23 | 2022-11-08 | Esker, S.A. | Form field prediction service |
| CN117010349A (en) * | 2023-09-28 | 2023-11-07 | 杭州今元标矩科技有限公司 | Form filling method, system and storage medium based on neural network model |
| CN117010349B (en) * | 2023-09-28 | 2023-12-19 | 杭州今元标矩科技有限公司 | Form filling method, system and storage medium based on neural network model |
| CN117391456A (en) * | 2023-11-27 | 2024-01-12 | 浙江南斗数智科技有限公司 | Village management method and service platform system based on artificial intelligence |
| CN117391456B (en) * | 2023-11-27 | 2024-04-05 | 浙江南斗数智科技有限公司 | Village management method and service platform system based on artificial intelligence |
Also Published As
| Publication number | Publication date |
|---|---|
| CN102184204B (en) | 2013-03-13 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN102184204B (en) | Auto fill method and system of intelligent Web form | |
| US11580104B2 (en) | Method, apparatus, device, and storage medium for intention recommendation | |
| US11562129B2 (en) | Adding machine understanding on spreadsheets data | |
| US9449271B2 (en) | Classifying resources using a deep network | |
| CN109543086A (en) | A kind of network data acquisition and methods of exhibiting towards multi-data source | |
| CN1936893B (en) | Method and system for generating input-method word frequency base based on internet information | |
| US10776885B2 (en) | Mutually reinforcing ranking of social media accounts and contents | |
| US10713306B2 (en) | Content pattern based automatic document classification | |
| CN104376406A (en) | Enterprise innovation resource management and analysis system and method based on big data | |
| US8140533B1 (en) | Harvesting relational tables from lists on the web | |
| CN107291840B (en) | User attribute prediction model construction method and device | |
| CN103049440A (en) | Recommendation processing method and processing system for related articles | |
| CN102955810B (en) | A kind of Web page classification method and equipment | |
| CN111339277A (en) | Question-answer interaction method and device based on machine learning | |
| US11249993B2 (en) | Answer facts from structured content | |
| CN104899231A (en) | Sentiment analysis engine based on fine-granularity attributive classification | |
| CN104021125A (en) | Search engine sorting method and system and search engine | |
| US20220107980A1 (en) | Providing an object-based response to a natural language query | |
| Kiu et al. | TaxoFolk: a hybrid taxonomy–folksonomy classification for enhanced knowledge navigation | |
| CN104133913A (en) | System and method for automatically establishing city shop information library based on video analysis, searching and aggregation | |
| CN113806537A (en) | Commodity category classification method and device, equipment, medium and product thereof | |
| Christy et al. | An enhanced method for topic modeling using concept-latent | |
| CN102982017B (en) | The method and apparatus that content judges | |
| CN115829301B (en) | Auxiliary management method, device and medium based on organization team configuration | |
| CN111488506B (en) | Method, device, equipment and storage medium for processing resource information |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| C14 | Grant of patent or utility model | ||
| GR01 | Patent grant | ||
| C41 | Transfer of patent application or patent right or utility model | ||
| TR01 | Transfer of patent right |
Effective date of registration: 20151014 Address after: Daitou town of Liyang City Ferry Street 213311 Jiangsu city of Changzhou province 8-2 No. 7 Patentee after: Liyang Chang Technology Transfer Center Co.,Ltd. Address before: Gehu Lake Road Wujin District 213164 Jiangsu city of Changzhou province No. 1 Patentee before: Changzhou University |
|
| TR01 | Transfer of patent right |
Effective date of registration: 20220718 Address after: 226000 floor 3, building 1, No. 33, Shibei Road, Xingfu street, Chongchuan District, Nantong City, Jiangsu Province Patentee after: Nantong Haotong Network Technology Co.,Ltd. Address before: 213311 7 7, tou tou street, Dai tou Town, Liyang, Changzhou, Jiangsu Patentee before: Liyang Chang Technology Transfer Center Co.,Ltd. |
|
| TR01 | Transfer of patent right | ||
| TR01 | Transfer of patent right |
Effective date of registration: 20221229 Address after: Building 41, No. 33, Xinkang Road, Nantong City, Jiangsu Province, 226000 Patentee after: Jiangsu xinbeco Network Technology Co.,Ltd. Address before: 226000 floor 3, building 1, No. 33, Shibei Road, Xingfu street, Chongchuan District, Nantong City, Jiangsu Province Patentee before: Nantong Haotong Network Technology Co.,Ltd. |
|
| TR01 | Transfer of patent right |