Community-based author and academic paper recommending system and recommending method

A recommendation system and paper technology, applied in other database retrieval, special data processing applications, network data retrieval, etc., can solve problems such as large amount of calculation, poor community building results, etc., and achieve the effect of reducing the amount of calculation

Active Publication Date: 2014-02-05
BEIJING UNIV OF POSTS & TELECOMM
View PDF2 Cites 88 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The system can not only use the correlation of research content among authors, build author community through topic model, solve the problem of poor community construction results due to lack of information; but also calculate the correlation value of authors and papers to be recommended within th

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Community-based author and academic paper recommending system and recommending method
  • Community-based author and academic paper recommending system and recommending method
  • Community-based author and academic paper recommending system and recommending method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0046] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings.

[0047] see image 3 , introduces the structure of the recommender system based on the community-based authors and their academic papers in the present invention: firstly use the citation relationship between the author and the paper and the community information to construct a two-layer citation network composed of the author layer and the paper layer, and then, according to the user's history Behavior records and the collection of papers that users have read build a user interest model, and finally analyze user needs based on the obtained double-layer citation network and user interest model, and recommend authors and their papers to users; the system has six components: paper crawling module, a preprocessing module, a two-tier citation network building block, a ...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention relates to a community-based author and academic paper recommending system and a recommending method. A double-layer quotation network consisting of an author layer and an academic paper layer is formed by utilizing a quotation relation between an author and the academic paper and the community information, then a user interesting model is established according to a historic behavior record of the user and the academic paper set read by the user, finally the user demand is analyzed according to the obtained double-layer quotation network and the user interesting model, and the author and academic paper thereof can be recommended to the user. The system is provided with an academic paper capturing module, an academic paper preprocessing module, a double-layer quotation network establishing module, a user interesting model establishing module and an individualized academic paper recommending module as well as a database. By adopting the recommending system and recommending method, not only can the correlation of the study content among users be used for establishing an author community through a subjective model, but also multiple attribute values of the to-be-recommended author and academic paper inside the community can be calculated, and the weakness that the calculation of the existing recommending algorithm is large can be improved; and meanwhile, multiple attribute values of the author and academic paper can be simultaneously calculated, so that the recommend result is more diversified, and the user requirement can be better met.

Description

technical field [0001] The present invention relates to a system and method for recommending authors and their academic papers, to be precise, to a community-based personalized recommendation system and method for authors and their academic papers, belonging to the technical fields of data mining and machine learning. Background technique [0002] In 2003, Blei et al. proposed the latent Dirichlet distribution LDA (Latent Dirichlet Allocation) topic model. Subsequently, researchers made many improvements to LDA. The mining of academic papers based on the topic model is an important application of the topic model. By mining the topics of the papers, the development and evolution of academic papers can be understood more deeply. In 2004, Michal Rosen-Zvi et al proposed the Author-Topic AT (Author-Topic) model based on LDA. The AT model is to build a text topic model of academic papers from the perspective of the author. For the corpus of academic papers, the LDA model does ...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G06F17/30
CPCG06F16/951
Inventor 卢美莲王萌星高洁刘智超秦臻
Owner BEIJING UNIV OF POSTS & TELECOMM
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap