Information retrieval (IR) has changed considerably in recent years with the expansion of the
World Wide Web and the advent of modern and inexpensive graphical user interfaces and …

People have looked for experts since before the advent of computers. With advances in
information retrieval technology and the large-scale availability of digital traces of …

Query performance prediction (QPP) is a core task in information retrieval. The QPP task is
to predict the retrieval quality of a search system for a query without relevance judgments …

Current prediction techniques, which are generally designed for content-based queries and
are typically evaluated on relatively homogenous test collections of small sizes, face serious …

In an expert search task, the users' need is to identify people who have relevant expertise to
a topic of interest. An expert search system predicts and ranks the expertise of a set of …

Pseudo-relevance feedback (PRF) via query-expansion has been proven to be e® ective in
many information retrieval (IR) tasks. In most existing work, the top-ranked documents from …

This work tries to answer the question of what makes a query difficult. It addresses a novel
model that captures the main components of a topic and the relationship between those …

Query performance prediction aims to estimate the quality of answers that a search system
will return in response to a particular query. In this paper we propose a new family of pre …

Effective organization of search results is critical for improving the utility of any search
engine. Clustering search results is an effective way to organize search results, which allows …

Predicting query performance, that is, the effectiveness of a search performed in response to
a query, is a highly important and challenging problem. We present a novel approach to this …