Web Recommender System for Identifying Semantic Related Scientific Papers
Manabu Ohta, Toshihiro Hachiki, Atsuhiro Takasu
International Journal of Web Applications, Vol. 4, No. 1, 2012.
DOI: 
Link: dline.info/ijwa/fulltext/v4n1/1.pdf
Abstract:
Identifying the related scientific papers is the unfinished agenda in the scientific research. Keywords are used as signals in the search process where it represents the text and such keys that reflect the content of papers. These keys do not solve the complexities in identifying semantic content and hence we develop a web based recommender system which relies on technical terms. These terms lead to the generation of bipartite graphs that contain the significant words from text corpus and technical terms generated. They are further used to rank the related papers using HITS algorithm for analyzing the bipartite graphs. Experimental results on our method show promising results.