Abstract. Pseudo-Relevance Feedback (PRF) assumes that the topranking n documents of the initial retrieval are relevant and extracts expansion terms from them. In this work, we int...
Abstract. In spite of the wide use of the Internet, it is difficult to develop desirable web documents evaluation that reflects users’ needs. Many automatic ranking systems have ...
Keyphrases are widely used as a brief summary of documents. Since manual assignment is time-consuming, various unsupervised ranking methods based on importance scores are proposed...
In this paper we present an evaluation of techniques that are designed to encourage web searchers to interact more with the results of a web search. Two specific techniques are ex...
We consider the problem of learning to rank relevant and novel documents so as to directly maximize a performance metric called Expected Global Utility (EGU), which has several de...