CN102521239A - Question-answering information matching system and method based on OWL (web ontology language) for Internet - Google Patents
Question-answering information matching system and method based on OWL (web ontology language) for Internet Download PDFInfo
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Abstract
The invention discloses a question-answering information matching system and a question-answering information matching method based on an OWL (web ontology language) for Internet. The question-answering information matching method comprises the following steps of: carrying out pretreatment after a user inputs a question or an answer; converting an inquiry statement into an OWL ontological example by an OWL ontological example converting module; carrying out ontological element treatment on core and extensional inquiry condition ontological examples by an OWL inquiry condition pre-treating module; matching each ontological element in an inquiry condition set with all items in an ontological element inverted list by an OWL ontological searching and matching module; extracting and outputting a corresponding primary document set as a result by a primary document managing system; sequencing a plurality of results by a matching result sequencing module; outputting a sequencing result to a user interface to display the result; and repeating the steps until all questions or answers are traversed. By using the question-answering information matching system and the question-answering information matching method, the automatic matching of the massive question-answering information of the Internet is achieved by adopting a searching method based on the OWL, and the accuracy for matching the information is improved greatly.
Description
Technical field
The present invention relates to a kind of internet question and answer information matches system, belong to field of computer technology based on OWL.
Background technology
A variety of paired interactive informations are arranged on the internet, such as: question and answer information, employment information, or the like.The coupling of most of so paired information is an artificial treatment, that is: the pairing that realizes nature of question and answer district or the follow-up post district through software setting itself.If keyword coupling, coupling poor accuracy are then often still leaned in pairing automatically in the internet information of magnanimity.
OWL (Web Ontology Language) is a kind of network ontology language of W3C exploitation, is used for body is carried out semantic description.OWL is designed to handle the content of information rather than only to the application of human presentation information.Create the internet if press OWL, internet itself just becomes the computing machine structure of knowledge of " understanding " to a certain extent.Software engineers can be a series of inference rules of Computer Design and engine on this basis, on the OWL semantic network, let computing machine oneself " understanding " internet information content, and make right judgement and operation.
Summary of the invention
Technical matters to be solved by this invention provides a kind of internet question and answer information matches system based on OWL, adopts the automatic pairing that realizes internet mass question and answer information based on the search method of OWL, and the information matches accuracy is high.
For solving the problems of the technologies described above, the present invention provides a kind of internet question and answer information matches system based on OWL, it is characterized in that, comprises
Preserve the original document database of interactive problem of internet mass or answer,
OWL instances of ontology modular converter converts problem or answer into the OWL instances of ontology and deposits OWL instances of ontology database in,
The inverted index database, with this volume elements inverted index,
OWL rule searching storehouse is proofreaded inverted index by the OWL knowledge model, and the generation rule searching deposits OWL rule searching storehouse in.
Also comprise
OWL body dictionary is used for from the conversion of text formatting querying condition to the OWL instances of ontology;
OWL ontology model storehouse is used for from the conversion of text formatting querying condition to the OWL instances of ontology;
OWL instances of ontology modular converter is responsible for from the conversion of text formatting querying condition to the OWL instances of ontology;
OWL querying condition pre-processing module is responsible for the extension reasoning of OWL querying condition, obtains more heterogeneous pass querying condition, simultaneously all querying conditions carry out this volume elementsization, from all querying conditions, extracts this volume elements;
OWL body search matched module is responsible for accomplishing search and the coupling in this volume elements of querying condition and this volume elements of the OWL inverted index table;
Question and answer condition to be matched and analysis module thereof are responsible for man-machine interaction, comprise the input of querying condition and pairing result's demonstration; Be responsible for simultaneously the querying condition of quasi-natural language is done preliminary analysis, so that do the conversion of OWL body.
A kind of question and answer information matching method of the internet question and answer information matches system based on OWL is characterized in that, comprises following steps:
1) user is through the problem or the answer of user interface input quasi-natural language;
2) question and answer condition to be matched and analysis module thereof carry out pre-service to user's problem or answer;
3) OWL instances of ontology modular converter converts query statement into the OWL instances of ontology under the help of OWL dictionary and OWL knowledge model;
4) OWL querying condition pre-processing module utilizes the OWL inference engine that querying condition is done knowledge extension expansion, obtains extra relevant inquiring instances of ontology;
5) OWL querying condition pre-processing module is carried out this volume elementsization processing with querying condition instances of ontology core and extension, extracts this all volume elements, as final querying condition collection;
6) OWL body search matched module each this volume elements of concentrating querying condition and this volume elements fall in the permutation table all mate, and will obtain all Query Results and export to original document management system and original document sort result system;
7) the original document management system is mapped to corresponding file in the original document database according to the corresponding relation of Query Result and OWL instances of ontology database, extracts corresponding original document collection as output;
8) when corresponding problem of a plurality of results or answer, match sort result module basis, and the result is sorted according to this goodness of fit based on the rule searching of knowledge and the knowledge goodness of fit of knowledge comparison algorithm judged result and condition;
9) ranking results outputs to user interface and does result's demonstration;
Select another one problem or answer, repeating step 1) to 9), move in circles, up to traversal all problem or answer.
Quasi-natural language described in the step 1) is for adopting the form of natural language, and employed grammer and vocabulary are in a scope limited or that provide in advance.
Step 2) pre-service described in comprises identification, validity detection, part-of-speech tagging at least.
In the step 6)
The step that OWL body search matched module is mated is:
A) utilize ergodic algorithm to locate the position of this volume elements in tabulation fast;
B) utilize the knowledge comparison algorithm to judge that this volume elements in the querying condition is whether same or similar with this volume elements of falling in the permutation table;
Reciprocation cycle up to each this volume elements querying condition of traversal, and obtains all Query Results, exports to original document management system and original document sort result system.
The beneficial effect that the present invention reached:
Internet question and answer information matches system and information matching method thereof based on OWL of the present invention; Employing realizes the automatic pairing of internet mass question and answer information based on the search method of OWL; Both can go in the answer of magnanimity, to seek suitable answer by a problem; Also can the problem of magnanimity, seek corresponding with it problem, improve the accuracy of information matches greatly from an answer.
Description of drawings
Fig. 1 is based on the interactive question and answer information matches system schematic of OWL.
Embodiment
Below in conjunction with accompanying drawing the present invention is further described.Following examples only are used for technical scheme of the present invention more clearly is described, and can not limit protection scope of the present invention with this.
Utilization both can go in the answer of magnanimity, to seek suitable answer by a problem based on the pairing of the internet content of OWL retrieval, also can the problem of magnanimity, seek corresponding with it problem from an answer.To be looked for answer by problem is example, and interactive matching system is as shown in Figure 1.
Wherein, Suppose the answer that has obtained magnanimity, this answer exists in the original document database, and converts it into the OWL instances of ontology by OWL instances of ontology conversion and deposit the instances of ontology database in; The instances of ontology database has been carried out this volume elements inverted index; And through the OWL knowledge model inverted index is proofreaded, produced rule searching, deposit OWL rule searching storehouse in.Except that above-mentioned basic module, this system also comprises:
1, OWL body dictionary is used for from the conversion of text formatting querying condition to the OWL instances of ontology;
2, OWL ontology model storehouse is used for from the conversion of text formatting querying condition to the OWL instances of ontology;
3, OWL instances of ontology modular converter is responsible for from the conversion of text formatting querying condition to the OWL instances of ontology;
4, OWL querying condition pre-processing module is responsible for the extension reasoning of OWL querying condition, obtains more heterogeneous pass querying condition, simultaneously all querying conditions carry out this volume elementsization, from all querying conditions, extracts this volume elements that is:;
5, OWL body search matched module, that is: nucleus module of the present invention is responsible for accomplishing search and the coupling in this volume elements of querying condition (collection) and this volume elements of the OWL inverted index table.Its gordian technique is:
A) how efficiently, apace the ergodic algorithm of this volume elements inverted index table that is: searches the method for each node of inverted index table;
B) how knowledge comparison algorithm that is: judges two same or analogous methods of the described knowledge of this volume elements, is not simple string matching, and the OWL body rule searching based on knowledge model plays an important role here;
6, question and answer condition to be matched and analysis module thereof are responsible for man-machine interaction, comprise the input of querying condition and pairing result's demonstration.Be responsible for simultaneously the querying condition of quasi-natural language is done preliminary analysis, so that do the conversion of OWL body.
Main flow based on said system is following:
1, the user is through the problem of user interface input quasi-natural language.Quasi-natural language that is: adopt the form of natural language, but employed grammer and vocabulary is all in a scope limited or that provide in advance;
2, question and answer condition to be matched and analysis module thereof to user's problem discern, pre-service such as validity detection, part-of-speech tagging;
3, OWL body modular converter converts query statement into the OWL instances of ontology under the help of OWL dictionary and OWL knowledge model;
4, OWL querying condition pre-processing module utilizes the OWL inference engine that querying condition is done knowledge extension expansion, obtains extra relevant inquiring instances of ontology;
5, OWL querying condition pre-processing module is carried out this volume elementsization processing with querying condition instances of ontology core and extension, extracts this all volume elements that is:, as final querying condition collection;
6, OWL body search matched module each this volume elements of concentrating querying condition and this volume elements fall in the permutation table all mate:
A) utilize ergodic algorithm to locate the position of this volume elements in tabulation fast;
B) utilize the knowledge comparison algorithm to judge that this volume elements in the querying condition is whether same or similar with this volume elements of falling in the permutation table;
Reciprocation cycle up to each this volume elements querying condition of traversal, and obtains all Query Results, exports to original document management system and original document sort result system;
7, the original document management system is mapped to corresponding file in the original document database according to the corresponding relation of Query Result and OWL instances of ontology database, extracts corresponding original document collection as output;
8, when problem of a plurality of results' correspondences, match sort result module meeting basis, and the result is sorted according to this goodness of fit based on the rule searching of knowledge and the knowledge goodness of fit of knowledge comparison algorithm judged result and condition;
9, ranking results outputs to user interface and does result's demonstration.
Select the another one problem, repeating step 1 to 9 moves in circles, up to all problems of traversal.
The above only is a preferred implementation of the present invention; Should be pointed out that for those skilled in the art, under the prerequisite that does not break away from know-why of the present invention; Can also make some improvement and distortion, these improvement and distortion also should be regarded as protection scope of the present invention.
Claims (6)
1. the internet question and answer information matches system based on OWL is characterized in that, comprises with lower module:
Preserve the original document database of interactive problem of internet mass or answer,
OWL instances of ontology modular converter converts problem or answer into the OWL instances of ontology and deposits OWL instances of ontology database in,
The inverted index database, with this volume elements inverted index,
OWL rule searching storehouse is proofreaded inverted index by the OWL knowledge model, and the generation rule searching deposits OWL rule searching storehouse in.
2. a kind of internet question and answer information matches system based on OWL according to claim 1 is characterized in that, also comprises following modules:
OWL body dictionary is used for from the conversion of text formatting querying condition to the OWL instances of ontology;
OWL ontology model storehouse is used for from the conversion of text formatting querying condition to the OWL instances of ontology;
OWL instances of ontology modular converter is responsible for from the conversion of text formatting querying condition to the OWL instances of ontology;
OWL querying condition pre-processing module is responsible for the extension reasoning of OWL querying condition, obtains more heterogeneous pass querying condition, simultaneously all querying conditions carry out this volume elementsization, from all querying conditions, extracts this volume elements;
OWL body search matched module is responsible for accomplishing search and the coupling in this volume elements of querying condition and this volume elements of the OWL inverted index table;
Question and answer condition to be matched and analysis module thereof are responsible for man-machine interaction, comprise the input of querying condition and pairing result's demonstration; Be responsible for simultaneously the querying condition of quasi-natural language is done preliminary analysis, so that do the conversion of OWL body.
3. the question and answer information matching method based on the internet question and answer information matches system of OWL is characterized in that, comprises following steps:
1) user is through the problem or the answer of user interface input quasi-natural language;
2) question and answer condition to be matched and analysis module thereof carry out pre-service to user's problem or answer;
3) OWL instances of ontology modular converter converts query statement into the OWL instances of ontology under the help of OWL dictionary and OWL knowledge model;
4) OWL querying condition pre-processing module utilizes the OWL inference engine that querying condition is done knowledge extension expansion, obtains extra relevant inquiring instances of ontology;
5) OWL querying condition pre-processing module is carried out this volume elementsization processing with querying condition instances of ontology core and extension, extracts this all volume elements, as final querying condition collection;
6) OWL body search matched module each this volume elements of concentrating querying condition and this volume elements fall in the permutation table all mate, and will obtain all Query Results and export to original document management system and original document sort result system;
7) the original document management system is mapped to corresponding file in the original document database according to the corresponding relation of Query Result and OWL instances of ontology database, extracts corresponding original document collection as output;
8) when corresponding problem of a plurality of results or answer, match sort result module basis, and the result is sorted according to this goodness of fit based on the rule searching of knowledge and the knowledge goodness of fit of knowledge comparison algorithm judged result and condition;
9) ranking results outputs to user interface and does result's demonstration;
Select another one problem or answer, repeating step 1) to 9), move in circles, up to traversal all problem or answer.
4. the question and answer information matching method of the internet question and answer information matches system based on OWL according to claim 3; It is characterized in that; Quasi-natural language described in the step 1) is for adopting the form of natural language, and employed grammer and vocabulary are in a scope limited or that provide in advance.
5. the question and answer information matching method of the internet question and answer information matches system based on OWL according to claim 3 is characterized in that step 2) described in pre-service comprise at least that identification, validity detect, part-of-speech tagging.
6. the question and answer information matching method of the internet question and answer information matches system based on OWL according to claim 3 is characterized in that, in the step 6)
The step that OWL body search matched module is mated is:
A) utilize ergodic algorithm to locate the position of this volume elements in tabulation fast;
B) utilize the knowledge comparison algorithm to judge that this volume elements in the querying condition is whether same or similar with this volume elements of falling in the permutation table;
Reciprocation cycle up to each this volume elements querying condition of traversal, and obtains all Query Results, exports to original document management system and original document sort result system.
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| CN103870440A (en) * | 2012-12-12 | 2014-06-18 | 中国移动通信集团广西有限公司 | Text data processing method and device |
| CN105224683A (en) * | 2015-10-28 | 2016-01-06 | 北京护航科技有限公司 | A kind of natural language analysis intelligent interactive method and device |
| CN103870440B (en) * | 2012-12-12 | 2016-11-30 | 中国移动通信集团广西有限公司 | A kind of text data processing method and device |
| WO2021053457A1 (en) * | 2019-09-18 | 2021-03-25 | International Business Machines Corporation | Language statement processing in computing system |
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| US20090287678A1 (en) * | 2008-05-14 | 2009-11-19 | International Business Machines Corporation | System and method for providing answers to questions |
| CN101393565A (en) * | 2008-11-07 | 2009-03-25 | 北京航空航天大学 | Facing virtual museum searching method based on noumenon |
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| CN103870440A (en) * | 2012-12-12 | 2014-06-18 | 中国移动通信集团广西有限公司 | Text data processing method and device |
| CN103870440B (en) * | 2012-12-12 | 2016-11-30 | 中国移动通信集团广西有限公司 | A kind of text data processing method and device |
| CN105224683A (en) * | 2015-10-28 | 2016-01-06 | 北京护航科技有限公司 | A kind of natural language analysis intelligent interactive method and device |
| WO2021053457A1 (en) * | 2019-09-18 | 2021-03-25 | International Business Machines Corporation | Language statement processing in computing system |
| GB2602238A (en) * | 2019-09-18 | 2022-06-22 | Ibm | Language statement processing in computing system |
| US11379738B2 (en) | 2019-09-18 | 2022-07-05 | International Business Machines Corporation | Using higher order actions to annotate a syntax tree with real data for concepts used to generate an answer to a question |
| US11842290B2 (en) | 2019-09-18 | 2023-12-12 | International Business Machines Corporation | Using functions to annotate a syntax tree with real data used to generate an answer to a question |
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Address after: 210006, 12 floor, Tong Tong Building, 501 South Zhongshan Road, Nanjing, Jiangsu Patentee after: Jiangsu United Industrial Limited by Share Ltd Address before: 210006, 12 floor, Tong Tong Building, 501 South Zhongshan Road, Nanjing, Jiangsu Patentee before: Jiangsu Lianzhu Industrial Co.,Ltd. |