Information filtering and information retrieval: two sides of the same coin?
Communications of the ACM - Special issue on information filtering
Modern Information Retrieval
Exploiting the hierarchical structure for link analysis
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
PageRank without hyperlinks: structural re-ranking using links induced by language models
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Improving web search results using affinity graph
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Webpage Importance Analysis Using Conditional Markov Random Walk
WI '05 Proceedings of the 2005 IEEE/WIC/ACM International Conference on Web Intelligence
Improving web search ranking by incorporating user behavior information
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Respect my authority!: HITS without hyperlinks, utilizing cluster-based language models
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Multi-document summarization using cluster-based link analysis
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
BrowseRank: letting web users vote for page importance
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Co-ranking Authors and Documents in a Heterogeneous Network
ICDM '07 Proceedings of the 2007 Seventh IEEE International Conference on Data Mining
Recommender systems by means of information retrieval
Proceedings of the International Conference on Web Intelligence, Mining and Semantics
Text retrieval methods for item ranking in collaborative filtering
ECIR'11 Proceedings of the 33rd European conference on Advances in information retrieval
Enhanced information retrieval using domain-specific recommender models
ICTIR'11 Proceedings of the Third international conference on Advances in information retrieval theory
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Inspired by the use of PageRank algorithms in document ranking, we develop and evaluate a cluster-based PageRank algorithm to re-rank information retrieval (IR) output with the objective of improving ad hoc search effectiveness. Unlike existing work, our methods exploit recommender techniques to extract the correlation between documents and apply detected correlations in a cluster-based PageRank algorithm to compute the importance of each document in a dataset. In this study two popular recommender techniques are examined in four proposed PageRank models to investigate the effectiveness of our approach. Comparison of our methods with strong baselines demonstrates the solid performance of our approach. Experimental results are reported on an extended version of the FIRE 2011 personal information retrieval (PIR) data collection which includes topically related queries with click-through data and relevance assessment data collected from the query creators. The search logs of the query creators are categorized based on their different topical interests. The experimental results show the significant improvement of our approach compared to results using standard IR and cluster-based PageRank methods.