CN102436497B - Mainstream media report hot-spot analyzing system based on studying type web ontology language (OWL) modeling - Google Patents
Mainstream media report hot-spot analyzing system based on studying type web ontology language (OWL) modeling Download PDFInfo
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Abstract
The invention discloses a mainstream media report hot-spot analyzing system based on studying type web ontology language (OWL) modeling. The system is characterized by comprising the following functional modules: 1), an OWL ontology instance transforming module; 2), an invert index module; 3), an ontology element frequency counting module, which is used for performing the ontology element frequency counting on the OWL ontology invert index table and sequencing according to the size of the frequency; 4), an OWL seed model generating module; 5), a knowledge ontology model polymerizing module; 6), an OWL hot model counting module; 7), a news hot frequency counting module. For utilizing the method of the OWL ontology model analysis, the invention promotes the internet news hot-spot analysis to the concept hierarchy; some related hot-spot concepts are polymerized by using the relationship between the concepts to form the news hot, thereby overcoming the shortcoming due to partial hot-spot analyzing in traditional method.
Description
Technical field
The present invention relates to a kind of mainstream media social focus analytic system, belong to network computer technology field.
Background technology
Traditional internet news analysis of central issue is quoted (reprinting) with crucial phrase or article by other websites, estimated by the frequency that user inquires about.Recently, utilize some short essays to be forwarded in microblogging, be concerned and also can be found out by the frequency statistics commented on " temperature " of this short essay.Effective to the estimation of the temperature of the news report being carrier with these crucial phrases, short essay, article, such as: Guo Mei good job part, two years old child are hit to many people by car and pass by and do not sue and labour, etc.But this analysis of central issue method cannot accomplish extension and the association analysis of concept, such as: Guo Meimei and the Red Cross Society of China? Ka Zhafei's is dead favourable to whom? Europe debt and world financial crisis, the economy of the U.S. on the impact of China, etc.Although some article does not directly occur certain keyword, what it was still said is the same same thing, uses traditional analysis of central issue method will omit such article.
Summary of the invention
Technical matters to be solved by this invention is mainstream media's social focus analytic system, by relevant focus concept polymerization composition hot news, thus makes retrieved relevant focus article more comprehensive.
For solving the problems of the technologies described above, the invention provides a kind of mainstream media's social focus analytic system based on learning type OWL modeling, it is characterized in that, comprise following functional module:
1) OWL instances of ontology modular converter: the conversion of OWL instances of ontology is done to the magnanimity news information text that search engine obtains;
2) inverted index module: this volume elements inverted index is done to OWL instances of ontology storehouse, described volume elements is undecomposable body minimum in OWL instances of ontology storehouse;
3) this volume elements frequency statistics module: this volume elements frequency statistics is done to this volume elements of OWL inverted index table, and sort according to the size of the frequency;
4) OWL Seed model generation module: using this volume elements of specified quantity of coming above as focus Seed model candidate, and in the mode of knowledge model stored in internet news OWL model bank; Seed model be the most original, be often also minimum knowledge model;
5) Ontology Model aggregation module: each Seed model in internet news OWL model bank is taken out respectively, do concept with other this volume elements in inverted index table to be polymerized, and amended hot news knowledge model is deposited back internet news OWL model bank, move in circles, until all Seed models are all complete by polymerization;
6) OWL hot spot model statistical module: traversal internet news OWL model bank, the knowledge model that statistical correlation concept is many also sorts, and the knowledge model coming specified quantity is above taken out as hot news knowledge model;
7) hot news frequency statistics module: find the instances of ontology corresponding with hot news knowledge model by inverted index table, the original article corresponding with these instances of ontology is found again by original document management system, and the frequency that original article is propagated, pays close attention to and commented on is added up, form hot news analysis result and export.
The beneficial effect that the present invention reaches:
The method that the present invention adopts OWL ontology model to analyze, internet news analysis of central issue is risen to concept hierarchy, utilizes the relation between concept and concept, by some relevant focus concept polymerizations, and form hot news, incomplete deficiency in traditional analysis of central issue method can be made up with this.
Accompanying drawing explanation
Fig. 1 is the structural representation of the report focal point analysis system of the mainstream media based on learning type OWL modeling in the present invention.
Embodiment
The present invention is the same with traditional news media analysis of central issue method, first hot news analytic system based on OWL (network ontology language Ontology of Web Language) knowledge model also will obtain the news information of magnanimity by search engine, be also propagate, pay close attention to, Main Basis that the frequency statistics commented on is estimated for temperature.Difference is, traditional is crucial phrase, short essay or article by objects of statistics, and this patent adopts based on OWL (being correlated with) conceptual combinations, that is: OWL knowledge model.
In order to obtain OWL knowledge model accurately, first the conversion of OWL instances of ontology to be carried out to the magnanimity news information text that search engine obtains, see patent " internet text this analysis and OWL converter based on OWL ", then, this volume elements inverted index table is done to the OWL instances of ontology storehouse representing magnanimity news information, see patent " a kind of inverted index method based on OWL ", just lie in this this volume elements inverted index table about the knowledge model of hot news.
The key of this patent is, does this volume elements frequency statistics to this volume elements inverted index table, and sets one group of OWL focus seed knowledge model according to statistics.Here basic assumption is, this volume elements (that is: key concept) that frequency of occurrence is higher in magnanimity news, and it is that the possibility of hot news carrier is larger.
Use this group seed knowledge model to do concept polymerization to whole volume elements inverted index table, that is: this relevant volume elements is aggregated in a knowledge model, each Seed model just " expansion ".Finally, the OWL knowledge model that frequency of occurrence is maximum, related notion is maximum is just defined as hot news model.
Pass through inverted index table, find out corresponding to the instances of ontology of each this volume elements and the original document of binding thereof in hot news model, re-use the frequency statistics method of traditional propagation, concern, comment, obtained original article is added up, the net result that its result is analyzed as hot news.As shown in Figure 1, each functional module and main flow are concrete function logic:
1) the magnanimity news information text obtained search engine does the conversion of OWL instances of ontology, and be 2011102707850 see patent " internet text this analysis and OWL converter based on OWL " application number, the applying date is on September 14th, 2011;
2) this volume elements inverted index is done to OWL instances of ontology storehouse;
3) this volume elements frequency statistics module does this volume elements frequency statistics to this volume elements of OWL inverted index table, and sorts according to the size of the frequency;
4) OWL Seed model generation module, using this volume elements of specified quantity of coming above as focus Seed model candidate, them with the form of knowledge model stored in internet news OWL model bank;
5) Ontology Model aggregation module, each Seed model in internet news OWL model bank is taken out respectively, do concept with other this volume elements in inverted index table to be polymerized, and amended hot news knowledge model is deposited back internet news OWL model bank, move in circles, until all Seed models are all complete by polymerization;
6) OWL hot spot model statistical module, traversal internet news OWL model bank, the knowledge model that statistical correlation concept is many also sorts, and the knowledge model coming specified quantity is above taken out as hot news knowledge model;
7) hot news frequency statistics module, the instances of ontology corresponding with hot news knowledge model is found by inverted index table, the original article corresponding with these instances of ontology is found again by original document management system, call traditional statistical method, to the frequency statistics that the article at the concept place in these hot news knowledge models is propagated, pays close attention to and commented on.Finally, form hot news analysis result to export.
Below disclose the present invention with preferred embodiment, so it is not intended to limiting the invention, and all employings are equal to replacement or the technical scheme that obtains of equivalent transformation mode, all drop within protection scope of the present invention.
Claims (1)
1., based on mainstream media's social focus analytic system of learning type OWL modeling, it is characterized in that, comprise following functional module:
1) OWL instances of ontology modular converter: the conversion of OWL instances of ontology is done to the magnanimity news information text that search engine obtains; Described OWL is network ontology language;
2) inverted index module: this volume elements inverted index is done to OWL instances of ontology storehouse, described volume elements is undecomposable body minimum in OWL instances of ontology storehouse;
3) this volume elements frequency statistics module: this volume elements frequency statistics is done to this volume elements of OWL inverted index table, and sort according to the size of the frequency;
4) OWL focus Seed model generation module: using this volume elements of specified quantity of coming above as focus Seed model candidate, and by focus Seed model in the mode of knowledge model stored in internet news OWL model bank;
5) Ontology Model aggregation module: each the focus Seed model in internet news OWL model bank is taken out respectively, do concept with other this volume elements in inverted index table to be polymerized, and amended hot news knowledge model is deposited back internet news OWL model bank, move in circles, until all focus Seed models are all complete by polymerization;
6) OWL hot spot model statistical module: traversal internet news OWL model bank, the knowledge model that statistical correlation concept is many also sorts, and the knowledge model coming specified quantity is above taken out as hot news knowledge model;
7) hot news frequency statistics module: find the instances of ontology corresponding with hot news knowledge model by inverted index table, the original article corresponding with instances of ontology is found again by original document management system, and the frequency that original article is propagated, pays close attention to and commented on is added up, form hot news analysis result and export.
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| CN101923544A (en) * | 2009-06-15 | 2010-12-22 | 北京百分通联传媒技术有限公司 | Method for monitoring and displaying Internet hot spots |
| CN102004792A (en) * | 2010-12-07 | 2011-04-06 | 百度在线网络技术（北京）有限公司 | Method and system for generating hot-searching word |
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| CN101923544A (en) * | 2009-06-15 | 2010-12-22 | 北京百分通联传媒技术有限公司 | Method for monitoring and displaying Internet hot spots |
| CN102004792A (en) * | 2010-12-07 | 2011-04-06 | 百度在线网络技术（北京）有限公司 | Method and system for generating hot-searching word |
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