Popularity Weighted Ranking for Academic Digital Libraries

Abstract. We propose a popularity weighted ranking algorithm for academic digital libraries that uses the popularity factor of a publication venue overcoming the limitations of impact factors. We compare our method with the naive PageRank, citation counts and HITS algorithm, three popular measures currently used to rank papers beyond lexical similarity. The ranking results are evaluated by discounted cumulative gain(DCG) method using four human evaluators. We show that our proposed ranking algorithm improves the DCG performance by 8.5% on average compared to naive PageRank, 16.3% compared to citation count and 23.2% compared to HITS. The algorithm is also evaluated by click through data from CiteSeer usage log.

• Type: Conference
• Year: 2007
• Where: ECIR
• Authors: Yang Sun, C. Lee Giles
• Keywords: Citation Count, ECIR 2007, Information Technology, Naive Pagerank, Ranking Algorithm