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Non-transitory computer readable medium storing a program, search apparatus, search method, and clustering device

A search method and clustering technology, applied in the field of search devices, can solve unrealistic problems

Active Publication Date: 2013-07-24
FUJIFILM BUSINESS INNOVATION CORP
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

From the viewpoint of required time, it is unrealistic to calculate the PPR based on the latest attention of the user every time a search query from the user (hereinafter referred to as "user query") is obtained

Method used

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  • Non-transitory computer readable medium storing a program, search apparatus, search method, and clustering device
  • Non-transitory computer readable medium storing a program, search apparatus, search method, and clustering device
  • Non-transitory computer readable medium storing a program, search apparatus, search method, and clustering device

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Experimental program
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Embodiment Construction

[0026] Basic idea

[0027] The reason why the PPR (Personalized Page Ranking) algorithm can not obtain the importance (web page ranking value) or ranking of the node in real time is to perform the calculation of the Markov chain for the entire large-scale network as the object. It takes a lot of time to perform such calculations for all web pages (www: World Wide Web) on the Internet.

[0028] However, in order to obtain the node importance or ranking related to the user query (search request), it will be sufficient to perform Markov chain calculations using only the part related to the user query instead of the entire original network. For example, in the case of performing Markov chain calculations to obtain the importance or ranking of nodes related to drug development queries, the scope of the Markov chain (representing walking on the network) includes medical science, drug Areas related to science, biochemistry, etc., but may not be required to include, for example, areas rel...

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PUM

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Abstract

Provided is a non-transitory computer readable medium storing a program causing a computer to function as a learning data acquiring unit that acquires learning data, a memory unit that performs machine learning using the learning data about cluster division where Markov chains of transition via a link from a node to a node on a network formed from plural nodes are divided into plural clusters each of which is indicated by a biased Markov chain and calculates a steady state of each biased Markov chain, a search condition receiving unit that receives a search condition from a user, a cluster extracting unit that extracts clusters suitable for the search condition, a partial network cutting unit that cuts a partial network formed by a node group belonging to the clusters, and an importance calculating unit that calculates importance of each node on the partial network.

Description

Technical field [0001] The invention relates to a search device, a search method and a clustering device. Background technique [0002] Page, L. et al. Stanford Digital Library Technologies Project (1998), [online], [searched on January 10, 2011] Internet (http: / / www-db.stanford.edu / ~backrub / pageranksub.ps ) (Non-Patent Document 1) discloses a web page ranking algorithm that appropriately defines “web page ranking” indicating the importance of each web page (node) based on a graphic structure formed by web pages and hyperlinks. Schematically, the webpage ranking algorithm defines the webpage ranking value of each node according to the "probability" assigned to each node in the steady state of the Markov chain. This algorithm is based on a simulation with the following process (Markov random walk) in which a human representative walks randomly following links on a graph from node to node. It means that the higher the probability that a node exists, the higher the page ranking va...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30G06N20/10
CPCG06N99/005G06N20/00G06N20/10
Inventor 冈本洋
Owner FUJIFILM BUSINESS INNOVATION CORP