CN102521240A - Internet supply and demand information matching system and matching method thereof on basis of OWL (Web Ontology Language) - Google Patents
Internet supply and demand information matching system and matching method thereof on basis of OWL (Web Ontology Language) Download PDFInfo
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- CN102521240A CN102521240A CN2011103576067A CN201110357606A CN102521240A CN 102521240 A CN102521240 A CN 102521240A CN 2011103576067 A CN2011103576067 A CN 2011103576067A CN 201110357606 A CN201110357606 A CN 201110357606A CN 102521240 A CN102521240 A CN 102521240A
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Abstract
The invention discloses an Internet supply and demand information matching system and a supply and demand information matching method on the basis of an OWL (Web Ontology Language). The supply and demand information matching method comprises the following steps that: after a user inputs supplies or demands, preprocessing is carried out; an OWL ontology example conversion module converts query sentences into an OWL ontology example; an OWL query condition preprocessing module carries out ontology meta processing on core and epitaxial query condition ontology examples, an OWL ontology searching and matching module matches each ontology meta in a query condition set with all items in an ontology meta inverted list, and an original document management system extracts corresponding original document sets serving as results to output; a matching result sorting module sorts a plurality of results; a sorting result is output to a user interface to be displayed; and the steps are circulated until all the supplies or demands are traversed. According to the invention, the automatic matching of massive Internet supply and demand information is realized by adopting a search method on the basis of the OWL and the accuracy of the information matching is greatly improved.
Description
Technical field
The present invention relates to a kind of internet supply-demand information matching 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: supply-demand 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 supply and demand 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.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.OWL can be used for handling the content of information rather than only to the application of human presentation information.
Summary of the invention
Technical matters to be solved by this invention provides a kind of internet supply-demand information matching system based on OWL, adopts the automatic pairing that realizes the internet mass supply-demand 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 supply-demand information matching system based on OWL, it is characterized in that, comprises
Preserve the original document database of internet mass demand or information provision,
OWL instances of ontology modular converter converts demand or information provision 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;
Supply and demand 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 supply-demand information matching process of the internet supply-demand information matching system based on OWL is characterized in that, comprises following steps:
1) user is through the supply or the demand information of user interface input quasi-natural language;
2) supply and demand condition to be matched and analysis module thereof carry out pre-service to user's input information;
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 supply of a plurality of results or needs of problems, match sort result module basis based on the rule searching of knowledge and the knowledge goodness of fit of knowledge comparison algorithm judged result and condition, and the result is sorted according to this goodness of fit;
9) ranking results outputs to user interface and does result's demonstration;
Select another one supply or demand information, repeating step 1) to 9), move in circles, up to traversal all supply or demand.
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.
The step that OWL body search matched module is mated in the step 6) 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 supply-demand information matching system and information matching method thereof based on OWL of the present invention; Utilization is based on the pairing of the internet content of OWL retrieval; Both can go in the demand information of magnanimity, to seek suitable demand by an information provision; Also can the information provision of magnanimity, seek corresponding with it supply, improve the accuracy of information matches greatly from a demand information.
Description of drawings
Fig. 1 is based on the interactive supply-demand information matching system synoptic diagram 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 demand information of magnanimity, to seek suitable demand by an information provision based on the pairing of the internet content of OWL retrieval, also can the information provision of magnanimity, seek corresponding with it supply from a demand information.To be looked for demand information by information provision is example, and interactive matching system is shown in figure one.This example is to go the searching demand from supply, if look for supply from demand, then whole process need conversely.
Wherein, Suppose the demand information that has obtained magnanimity, this information 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, supply and demand 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 information provision 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, supply and demand condition to be matched and analysis module thereof to user's problem discern, pre-service such as validity detection, part-of-speech tagging; Be the pre-service to querying condition, at this moment the querying condition of input is " supply " information.
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 supply problem of a plurality of demand 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 supplies 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 supply-demand information matching system based on OWL is characterized in that, comprises with lower module:
Preserve the original document database of internet mass demand or information provision,
OWL instances of ontology modular converter converts demand or information provision 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 supply-demand information matching 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;
Supply and demand 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 supply-demand information matching process based on the internet supply-demand information matching system of OWL is characterized in that, comprises following steps:
1) user is through the supply or the demand information of user interface input quasi-natural language;
2) supply and demand condition to be matched and analysis module thereof carry out pre-service to user's input information;
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 supply of a plurality of results or needs of problems, match sort result module basis based on the rule searching of knowledge and the knowledge goodness of fit of knowledge comparison algorithm judged result and condition, and the result is sorted according to this goodness of fit;
9) ranking results outputs to user interface and does result's demonstration;
Select another one supply or demand information, repeating step 1) to 9), move in circles, up to traversal all supply or demand.
4. the supply-demand information matching process of the internet supply-demand information matching 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 supply-demand information matching process of the internet supply-demand information matching 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 supply-demand information matching process of the internet supply-demand information matching system based on OWL according to claim 3 is characterized in that the step that OWL body search matched module is mated in the step 6) 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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Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN101393565A (en) * | 2008-11-07 | 2009-03-25 | 北京航空航天大学 | Facing virtual museum searching method based on noumenon |
| CN101582073A (en) * | 2008-12-31 | 2009-11-18 | 北京中机科海科技发展有限公司 | Intelligent retrieval system and method based on domain ontology |
| US20090287678A1 (en) * | 2008-05-14 | 2009-11-19 | International Business Machines Corporation | System and method for providing answers to questions |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| 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 |
| CN101582073A (en) * | 2008-12-31 | 2009-11-18 | 北京中机科海科技发展有限公司 | Intelligent retrieval system and method based on domain ontology |
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