A method and system for author recommendation based on clustering algorithm and locality-aware reconstruction model

A technology of reconstructing models and clustering algorithms, which is applied in computer parts, character and pattern recognition, text database clustering/classification, etc., can solve the problem of distinguishing between two samples of word space distribution and ignoring word space distribution information and other issues to achieve the effect of enhancing vector representation

Active Publication Date: 2021-08-06
HARBIN INST OF TECH SHENZHEN GRADUATE SCHOOL
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Problems solved by technology

However, this type of method only relies on the word frequency statistics of words in the text, and ignores the spatial distribution information of words, which makes it difficult for this method to distinguish two samples with similar word frequencies but different spatial distributions of words.

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  • A method and system for author recommendation based on clustering algorithm and locality-aware reconstruction model
  • A method and system for author recommendation based on clustering algorithm and locality-aware reconstruction model
  • A method and system for author recommendation based on clustering algorithm and locality-aware reconstruction model

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[0063] In order to make the object, technical solution and advantages of the present invention more clear, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0064] Research on author recommendation system based on clustering algorithm and local perceptual reconstruction model of the present invention. The main innovative work of the present invention is the following six parts: 1) tree structure expression module; 2) node feature expression module; 3) hierarchical node position mapping module; 4) local perception reconstruction model; 5) tree structure Unified vector representation; 6) Content-based author recommendation and retrieval. The first part is to organize the relevant information of the author, and organize the relevant information of the...

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Abstract

The present invention proposes an author recommendation method and system based on a clustering algorithm and a local perceptual reconstruction model. The establishment of , transforms the author information represented by the tree structure into a unified vector representation, which contains the relevant information of the author and the structural information of each level related to the author. Further, according to the unified vector representation of author information, the recommendation and retrieval of related authors are carried out. The method includes: A, tree structure expression; B, node feature expression; C, hierarchical node position mapping; D, establishing and solving local perception reconstruction model; E, unified vector representation of tree structure; F, content-based author recommendation and retrieval.

Description

technical field [0001] The present invention belongs to the field of text mining and recommendation systems, organizes heterogeneous information data into a tree structure according to its internal logic structure, and realizes an effective tree structure vector representation through clustering at each level and local perceptual reconstruction models. The method and system use the most original input of author information from different domains. Background technique [0002] With the continuous advancement and development of Internet technology, the scale of network data is increasing day by day. The source of data and the organizational form of data are diverse according to different application scenarios. For each user, the data sources related to it are diverse. If these data can be effectively organized, extracted, and fused, a more comprehensive information representation related to the user can be finally obtained. For example, for a certain author, data from differ...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F16/335G06F16/35G06K9/62
CPCG06F16/337G06F16/355G06F18/23213G06F18/2135
Inventor 张海军王双
Owner HARBIN INST OF TECH SHENZHEN GRADUATE SCHOOL
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