This paper presents two approaches to ranking reader emotions of documents. Past studies assign a document to a single emotion category, so their methods cannot be applied directl...
Web search quality can vary widely across languages, even for the same information need. We propose to exploit this variation in quality by learning a ranking function on bilingua...
While numerous metrics for information retrieval are available in the case of binary relevance, there is only one commonly used metric for graded relevance, namely the Discounted ...
Olivier Chapelle, Donald Metlzer, Ya Zhang, Pierre...
: In this paper, we report our experiments in the mixed query task of the Web track for TREC 2004. We deal with the problem of ranking Web documents within a multicriteria framewor...
Ranking for multilingual information retrieval (MLIR) is a task to rank documents of different languages solely based on their relevancy to the query regardless of query’s langu...