DocumentCode :
3739182
Title :
Research Paper Recommendation Based on the Knowledge Gap
Author :
Weidong Zhao;Ran Wu;Weihui Dai;Yonghui Dai
Author_Institution :
Shanghai Key Lab. of Data Sci. Sch. of Software, Fudan Univ., Shanghai, China
fYear :
2015
Firstpage :
373
Lastpage :
380
Abstract :
The massively growing of literature resource makes it a challenge for researchers to find useful papers. To solve the information overload problem, some researches on personalized paper recommendation have been conducted. However, the knowledge gap between a researcher´s background knowledge and research target is seldom concerned. In this paper, we propose a knowledge-gap based literature recommendation method to support researchers to fulfill literature support. Firstly, domain knowledge is modeled with the concept map, based on which background knowledge and target knowledge are analyzed. Then, knowledge gap is defined both graphically and intuitively with the knowledge map. To bridge the knowledge gap, we design a graph-based method to explore some suitable knowledge paths, which can help a researcher to learn the requisite knowledge in accordance with cognition pattern. Finally, experiments are performed to demonstrate the effectiveness of the proposed method.
Keywords :
"Semantics","Correlation","Filtering","Proposals","Ontologies","Collaboration"
Publisher :
ieee
Conference_Titel :
Data Mining Workshop (ICDMW), 2015 IEEE International Conference on
Electronic_ISBN :
2375-9259
Type :
conf
DOI :
10.1109/ICDMW.2015.40
Filename :
7395694
Link To Document :
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