We describe a new family of topic-ranking algorithms for multi-labeled documents. The motivation for the algorithms stems from recent advances in online learning algorithms. The a...
This paper investigates the agreement of relevance assessments between official TREC judgments and those generated from an interactive IR experiment. Results show that 63% of docu...
Retrieval systems rank documents according to their retrieval status values (RSV) if these are monotonously increasing with the probability of relevance of documents. In this work,...
Abstract. We consider a collaboration of peers autonomously crawling the Web. A pivotal issue when designing a peer-to-peer (P2P) Web search engine in this environment is query rou...
Sebastian Michel, Matthias Bender, Peter Triantafi...
Abstract. Evaluation is one of the hardest tasks in automatic text summarization. It is perhaps even harder to determine how much a particular component of a summarization system c...