Pseudo-relevance feedback is an effective technique for improving retrieval results. Traditional feedback algorithms use a whole feedback document as a unit to extract words for ...
We present a novel interpretation of Clarity [5], a widely used query performance predictor. While Clarity is commonly described as a measure of the “distance” between the lan...
Shay Hummel, Anna Shtok, Fiana Raiber, Oren Kurlan...
In information retrieval, relevance of documents with respect to queries is usually judged by humans, and used in evaluation and/or learning of ranking functions. Previous work ha...
Jingfang Xu, Chuanliang Chen, Gu Xu, Hang Li, Elbi...
We describe ongoing research on segmenting and labeling HTML medical journal articles. In contrast to existing approaches in which HTML tags usually serve as strong indicators, we...
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...