CiteRank: combination similarity and static ranking with research paper searching

Abstract

Search engines and social bookmarking systems are important tools for web resource discovery. The performance and capabilities of web search engines are vital. This paper proposes CiteRank, a combination of a similarity ranking with a static ranking. Similarity ranking measures the match between a query and a research paper index; while a static ranking, or a query independent ranking, measures the quality of a research paper. For this particular study, a group of factors containing: number of groups contained the posted paper, year of publication, research paper posted time, and priority of a research paper was used to determine a static ranking score. The NDCG was used as an evaluation metric. CiteRankwas compared with SimRankand StaticRank. The results of the experiment showed that CiteRank produces a better ranking than the other methods. This implies that CiteRank can improve the effectiveness of research paper searching on social bookmarking websites.