Title
A Novel Approach for Personalized Article Recommendation in Online Scientific Communities
Abstract
Rapid proliferation of information technologies has generated sheer volume of information which makes scientific research related information searching more challenging. Personalized recommendation is the widely adopted technique to recommend relevant documents to researchers. Current methods are suffering from mismatch problem and match irrelevance problem and fail to generate highly related results. To overcome these problems, we propose a novel approach to recommend articles to the researchers. In our approach we integrate three types of similarity measures: keyword similarity, journal similarity, and author similarity to measure the relevance of the articles to researchers. The keyword similarity is used to generate candidate list of articles, and the journal similarity and author similarity are used to select most suitable articles from the candidate list. The integrated similarity measure is used to rank the articles based on their relevance. The proposed method is implemented in Scholar Mate (www.scholarmate.com), the online research social network platform. The evaluation results exhibit that proposed method is more effective than existing ones.
Year
DOI
Venue
2013
10.1109/HICSS.2013.48
HICSS
Keywords
Field
DocType
evaluation results exhibit,rapid proliferation,information technology,information generation,scientific information systems,information searching,recommender systems,pattern matching,online scientific communities,scholarmate,social network platform,personalized article recommendation,author similarity,current method,keyword similarity,similarity measure,candidate list,information technologies,document handling,irrelevance problem matching,integrated similarity measure,integrated similarity measurement,novel approach,journal similarity
Recommender system,Similarity measure,Information retrieval,Information technology,Computer science,Similarity heuristic,Online research methods,Pattern matching,Semantics,Scientific method
Conference
ISSN
ISBN
Citations 
1530-1605 E-ISBN : 978-0-7695-4892-0
978-0-7695-4892-0
3
PageRank 
References 
Authors
0.38
14
7
Name
Order
Citations
PageRank
Jianshan Sun119217.65
Jian Ma21662103.00
Xiaoyan Liu310919.35
Zhiying Liu4324.85
Gang Wang52007.20
Hongbing Jiang6994.08
Thushari Silva7365.87