Literature retrieval method based on semantic small-word model

Abstract

This invention discloses one file index method based on language meanings small world, which comprises the following steps: firstly using latent meanings index to extract file property vector to maintain file property to lower its dimensions and to reduce the information memory volume; then using supportive vector machine to sort all common files to form sort information to mark the sort interest proportion; finally using social network small world with small linkage point with high proportion interest of certain file sort to form network topological structure with small property.

Description

Technical field [0001] The invention belongs to distributed computing and information retrieval in the computer field, and specifically relates to a document retrieval method based on a semantic small world model. The method mainly uses the semantic small world model to solve efficient information storage and retrieval in a peer-to-peer network for document information sharing problem. Background technique [0002] Because of its scalability, fault tolerance, autonomy and self-organization, the peer-to-peer network system has attracted more and more attention in the field of large-scale information retrieval. However, in the peer-to-peer network of document information sharing, how to effectively store and retrieve information is still a very challenging problem. [0003] The phenomenon of small worlds is widespread in social networks, that is, everyone in the world can be connected through a short chain of social relations. The length of the chain of social relations is generall...

AI Technical Summary

Problems solved by technology

However, the above methods all require precise metadata matching (such as file names or keywords) to complete the search requirements. Since the semantic information of other nodes in the network cannot be obtained, it is necessary to blindly search a large number of nodes to ensure the recall rate of information retrieval. causing severe network load

Guiding query messages through improved neighbor node index information (such as local indexes) can improve query performance, but updating index information requires very large additional overhead

A structured peer-to-peer network (such as CAN, Chord) based on a distributed hash table can provide good scalability and effective search performance, but it can only support the keyword / value lookup method. For the information retrieval field Full-text search is not suitable, and the overhead of maintaining a structured peer-to-peer network structure is very high

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