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Search method based on membrane computing

A search method and membrane computing technology, applied in the field of network search, can solve problems such as incomplete documents and topics in calculation considerations, flaws in similarity calculation models, etc., and achieve the effect of improving recall and accuracy, and improving accuracy.

Inactive Publication Date: 2014-07-30
XIHUA UNIV +1
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AI Technical Summary

Problems solved by technology

[0004] In order to solve the problems in the prior art, the present invention provides a search method based on membrane calculation, which solves the problem of incomplete calculation of the priority value calculation of unvisited URLs and the similarity calculation of documents and topics in the crawling of the network main body in the prior art. The problem with flaws in the model

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  • Search method based on membrane computing

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Embodiment Construction

[0025] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments.

[0026] A search method based on membrane computing, including the following steps: (A) obtaining the optimal weighting factor; (B) obtaining document topic similarity; (C) predicting the ranking priority value.

[0027] The step (A) further includes acquiring training data; generating initial objects and setting related parameters on the surface membrane, intermediate membrane and basic membrane; applying evolution rules to the surface membrane, intermediate membrane and basic membrane; applying Communication rules; surface membrane output best object.

[0028] The step (B) further includes acquiring four different documents; calculating the subject similarity of the four documents; the four different documents are the full text of the webpage, link anchor text, link context and webpage title documents respectively.

[0029] The step (C) furth...

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Abstract

The invention relates to the field of network search, and discloses a search method based on membrane computing. The method comprises the following steps of (A) obtaining the optimum weighing factor; (B) obtaining the similarity of document themes; (3) predicting and sequencing the optimum values. The method has the beneficial effect that the accuracy of predicting the similarity of the unvisited URL (uniform resource locator) themes is improved, and the recall ratio and accuracy of theme crawlers are further improved, so the theme crawlers are instructed to collect more webpage sets with higher quality from an internet, and the webpage sets which are more interested by a user can be more effectively collected.

Description

technical field [0001] The invention relates to the field of network search, in particular to a search method based on membrane calculation. Background technique [0002] Most topic crawling methods are based on the text content method. Typical topic crawlers in these topic crawlers include VSM topic crawler and SSRM topic crawler. VSM topic crawler will not visit URLs full text of web pages and two documents of link anchor text The topic relevance and the corresponding two weighting factors are integrated into their priority values, and the similarity between the document and the topic is calculated using the Vector Space Model (Vector Space Model VSM); S.Chakrabarti, M.V.D.Berg, B.Dom, Focused crawling : a new approach for topic specific resource discovery, Computer Networks, 1999, 31: 1623-1640. The SSRM topic crawler also compares the topic relevance of the two documents of the full text of the web page and the link anchor text of the URLs that have not been visited with...

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Application Information

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IPC IPC(8): G06F17/30
CPCG06F16/313G06F16/951
Inventor 杜亚军刘文君孟庆瑞李曦王晓明
Owner XIHUA UNIV
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