CN102521240B - 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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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 based on OWL, belong to field of computer technology.
Background technology
A variety of paired interactive informations are arranged on the internet, such as: supply-demand information, employment information, etc.The coupling of most of so paired information is artificial treatment, that is: the supply and demand district by software setting itself or follow-up post district realize the pairing of nature.If in the internet information of magnanimity automatic matching, often or by keyword coupling, the coupling poor accuracy.
OWL(Web Ontology Language) be a kind of network ontology language of W3C exploitation, be 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, allow computing machine oneself " understanding " internet information content on the OWL semantic network, and make correct judgement and operation.OWL can be used for processing the content of information rather than only to the application of mankind's presentation information.
Summary of the invention
Technical matters to be solved by this invention is to provide a kind of internet supply-demand information matching system based on OWL, adopts the automatic matching of realizing 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 invention provides a kind of internet supply-demand information matching system based on OWL, it is characterized in that, comprise
Preserve the original document database of internet mass demand or information provision,
OWL instances of ontology modular converter is converted to the OWL instances of ontology with demand or information provision 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 produces rule searching and deposit OWL rule searching storehouse in.
Also comprise
OWL body dictionary is used for the conversion from the text formatting querying condition to the OWL instances of ontology;
OWL ontology model storehouse is used for the conversion from the text formatting querying condition to the OWL instances of ontology;
OWL instances of ontology modular converter is responsible for the conversion from the text formatting querying condition to the OWL instances of ontology;
OWL querying condition pretreatment 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, extracts this volume elements from all querying conditions;
OWL Ontology Searching matching module is responsible for completing search and coupling in this volume elements of querying condition and this volume elements of 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 the demonstration of pairing result; Be responsible for simultaneously the querying condition of quasi-natural language is done preliminary analysis, in order to 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 inputs supply or the demand information of quasi-natural language by user interface;
2) supply and demand condition to be matched and analysis module thereof carry out pre-service to user's input message;
3) OWL instances of ontology modular converter is converted to the OWL instances of ontology with query statement under the help of OWL dictionary and OWL knowledge model;
4) OWL querying condition pretreatment module utilizes the OWL inference engine to do the knowledge extending expansion to querying condition, obtains extra relevant inquiring instances of ontology;
5) OWL querying condition pretreatment module is carried out this volume elementsization processing with core and querying condition instances of ontology extension, extracts this all volume elements, as final querying condition collection;
6) all in OWL Ontology Searching matching module each this volume elements that querying condition is concentrated and this volume elements Inverted List are mated, 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 according to the corresponding relation of Query Result and OWL instances of ontology database, is mapped to corresponding file in the original document database, extracts corresponding original document collection as output;
8) when the corresponding supply of a plurality of results or needs of problems are arranged, 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 according to this goodness of fit, result is sorted;
9) ranking results outputs to user interface and does the result demonstration;
Select another one supply or demand information, repeating step 1) to 9), move in circles, until travel through all supplies or demand.
Quasi-natural language described in step 1) is for adopting the form of natural language, and the grammer that uses and vocabulary are in a limited or scope that provide in advance.
Step 2) pre-service described in comprises identification, validation checking, part-of-speech tagging at least.
The step that in step 6), OWL Ontology Searching matching module mates is:
A) utilize ergodic algorithm to locate fast the position of this volume elements in list;
B) utilize the knowledge comparison algorithm judge in querying condition this volume elements whether with Inverted List in this volume elements same or similar;
Reciprocation cycle until travel through each this volume elements querying condition, and obtains all Query Results, exports to original document management system and original document sort result system.
The beneficial effect that the present invention reaches:
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 to seek suitable demand in the demand information of magnanimity by an information provision, also can seek from a demand information corresponding with it supply the information provision of magnanimity, greatly improve the accuracy of information matches.
Description of drawings
Fig. 1 is based on the interactive supply-demand information matching system schematic diagram of OWL.
Embodiment
The invention will be further described below in conjunction with accompanying drawing.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 be gone to seek suitable demand in the demand information of magnanimity by an information provision based on the pairing of the internet content of OWL retrieval, also can seek from a demand information corresponding with it supply the information provision of magnanimity.To be looked for demand information as example by information provision, interactive matching system is as shown in figure one.This example is to go the searching demand from supply, if look for supply from demand, whole process need conversely.
Wherein, suppose the demand information that has obtained magnanimity, this information exists in the original document database, and by OWL instances of ontology conversion, it is converted to the OWL instances of ontology and deposits the instances of ontology database in, the instances of ontology database has been carried out this volume elements inverted index, and by the OWL knowledge model, inverted index is proofreaded, produced rule searching, deposit OWL rule searching storehouse in.Except above-mentioned basic module, this system also comprises:
1, OWL body dictionary is used for the conversion from the text formatting querying condition to the OWL instances of ontology;
2, OWL ontology model storehouse is used for the conversion from the text formatting querying condition to the OWL instances of ontology;
3, OWL instances of ontology modular converter is responsible for the conversion from the text formatting querying condition to the OWL instances of ontology;
4, OWL querying condition pretreatment 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, extracts this volume elements from all querying conditions that is:;
5, OWL Ontology Searching matching module, that is: nucleus module of the present invention, be responsible for completing search and coupling in this volume elements of querying condition (collection) and this volume elements of OWL inverted index table.Its gordian technique is:
A) ergodic algorithm of this volume elements inverted index table, that is: how efficiently, search rapidly 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 Ontology Query rule 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 the demonstration of pairing result.Be responsible for simultaneously the querying condition of quasi-natural language is done preliminary analysis, in order to do the conversion of OWL body.
Main flow based on said system is as follows:
1, the user inputs the information provision of quasi-natural language by user interface.Quasi-natural language that is: adopts the form of natural language, but the grammer that uses and vocabulary are all in a limited or scope that provide in advance;
2, supply and demand condition to be matched and analysis module thereof to user's problem identify, the pre-service such as validation checking, 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 is converted to the OWL instances of ontology with query statement under the help of OWL dictionary and OWL knowledge model;
4, OWL querying condition pretreatment module utilizes the OWL inference engine to do the knowledge extending expansion to querying condition, obtains extra relevant inquiring instances of ontology;
5, OWL querying condition pretreatment module is carried out this volume elementsization processing with core and querying condition instances of ontology extension, extracts this all volume elements that is:, as final querying condition collection;
6, all in OWL Ontology Searching matching module each this volume elements that querying condition is concentrated and this volume elements Inverted List are mated:
A) utilize ergodic algorithm to locate fast the position of this volume elements in list;
B) utilize the knowledge comparison algorithm judge in querying condition this volume elements whether with Inverted List in this volume elements same or similar;
Reciprocation cycle until travel through each this volume elements querying condition, and obtains all Query Results, exports to original document management system and original document sort result system;
7, the original document management system according to the corresponding relation of Query Result and OWL instances of ontology database, is mapped to corresponding file in the original document database, extracts corresponding original document collection as output;
8, when the corresponding supply problem of a plurality of demand results is arranged, match sort result module meeting basis based on the rule searching of knowledge and the knowledge goodness of fit of knowledge comparison algorithm judged result and condition, and according to this goodness of fit, result is sorted;
9, ranking results outputs to user interface and does the result demonstration.
Select the another one problem, repeating step 1 to 9 moves in circles, until travel through all supplies.
The above is only the preferred embodiment of the present invention; should be pointed out that for those skilled in the art, under the prerequisite that does not break away from the technology of the present invention principle; can also make some improvement and distortion, these improvement and distortion also should be considered as protection scope of the present invention.
Claims (5)
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 is converted to the OWL instances of ontology with demand or information provision 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 produces rule searching and deposit OWL rule searching storehouse in;
Also comprise following modules:
OWL body dictionary is used for the conversion from the text formatting querying condition to the OWL instances of ontology;
OWL ontology model storehouse is used for the conversion from the text formatting querying condition to the OWL instances of ontology;
OWL instances of ontology modular converter is responsible for the conversion from the text formatting querying condition to the OWL instances of ontology;
OWL querying condition pretreatment 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, extracts this volume elements from all querying conditions;
OWL Ontology Searching matching module is responsible for completing search and coupling in this volume elements of querying condition and this volume elements of 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 the demonstration of pairing result; Be responsible for simultaneously the querying condition of quasi-natural language is done preliminary analysis, in order to do the conversion of OWL body.
2. 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 inputs supply or the demand information of quasi-natural language by user interface;
2) supply and demand condition to be matched and analysis module thereof carry out pre-service to user's input message;
3) OWL instances of ontology modular converter is converted to the OWL instances of ontology with query statement under the help of OWL dictionary and OWL knowledge model;
4) OWL querying condition pretreatment module utilizes the OWL inference engine to do the knowledge extending expansion to querying condition, obtains extra relevant inquiring instances of ontology;
5) OWL querying condition pretreatment module is carried out this volume elementsization processing with core and querying condition instances of ontology extension, extracts this all volume elements, as final querying condition collection;
6) all in OWL Ontology Searching matching module each this volume elements that querying condition is concentrated and this volume elements Inverted List are mated, 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 according to the corresponding relation of Query Result and OWL instances of ontology database, is mapped to corresponding file in the original document database, extracts corresponding original document collection as output;
8) when the corresponding supply of a plurality of results or needs of problems are arranged, 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 according to this goodness of fit, result is sorted;
9) ranking results outputs to user interface and does the result demonstration;
Select another one supply or demand information, repeating step 1) to 9), move in circles, until travel through all supplies or demand.
3. the supply-demand information matching process of the internet supply-demand information matching system based on OWL according to claim 2, it is characterized in that, quasi-natural language described in step 1) is for adopting the form of natural language, and the grammer that uses and vocabulary are in a limited or scope that provide in advance.
4. the supply-demand information matching process of the internet supply-demand information matching system based on OWL according to claim 2, is characterized in that step 2) described in pre-service comprise at least identification, validation checking, part-of-speech tagging.
5. the supply-demand information matching process of the internet supply-demand information matching system based on OWL according to claim 2, is characterized in that, the step that in step 6), OWL Ontology Searching matching module mates is:
A) utilize ergodic algorithm to locate fast the position of this volume elements in list;
B) utilize the knowledge comparison algorithm judge in querying condition this volume elements whether with Inverted List in this volume elements same or similar;
Reciprocation cycle until travel through each this volume elements querying condition, and obtains all Query Results, exports to original document management system and original document sort result system.
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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 |
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| 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 |
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