Decayed DivRank: capturing relevance, diversity and prestige in information networks

Many network-based ranking approaches have been proposed to rank objects according to different criteria, including relevance, prestige and diversity. However, existing approaches either only aim at one or two of the criteria, or handle them with additional heuristics in multiple steps. Inspired by DivRank, we propose a unified ranking model, Decayed DivRank (DDRank), to meet the three criteria simultaneously. Empirical experiments on paper citation network show that DDRank can outperform existing algorithms in capturing relevance, diversity and prestige simultaneously in ranking. Categories and Subject Descriptors H.2.8 [Database Applications]: Data Mining General Terms Algorithms, Experimentation Keywords Diversity, Relevance, Prestige, Multi-objective Ranking

• Type: Journal
• Year: 2011
• Where: SIGIR
• Authors: Pan Du, Jiafeng Guo, Xueqi Cheng
• Keywords: Citation Network, Information Technology, Paper Citation, SIGIR 2011, Subject Descriptors