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 …

A novel probabilistic retrieval model is presented. It forms a basis to interpret the TF-IDF term
weights as making relevance decisions. It simulates the local relevance decision-making for …

We propose a principled approach to summarization of visual data (images or video) based
on optimization of a well-defined similarity measure. The problem we consider is re-targeting …

Despite the recent advances in search quality, the fast increase in the size of the Web
collection has introduced new challenges for Web ranking algorithms. In fact, there are still …

We present a method for automatic generate suggestions of related queries submitted to
Web search engines. The method extracts information from the log of past submitted queries …

This paper studies how link information can be used to improve classification results for Web
collections. We evaluate four different measures of subject similarity, derived from the Web …

Previous studies have shown that hybrid clustering methods that incorporate textual content
and bibliometric information can outperform clustering methods that use only one of these …

The World Wide Web is the largest publicly available image repository and a natural source
of attention. An immediate consequence is that searching for images on the Web has …

Bayesian networks, which nowadays constitute the dominant approach for managing
probability within the field of Artificial Intelligence, have been applied to Information Retrieval …

In this paper we present a proposal for the implementation and evaluation of a novel method
for automatically using data-rich text for filling form-based input interfaces. Our solution takes …