In order to minimize redundancy and optimize coverage of multiple user interests, search engines and recommender systems aim to diversify their set of results. To date, these dive...
This paper presents a framework for efficient HMM-based estimation of unreliable spectrographic speech data. It discusses the role of Hidden Markov Models (HMMs) during minimum mea...
In this paper we present a prototype system to enrich audiovisual contents with annotations, which exploits existing technologies for automatic extraction of metadata (such as OCR...
Giuseppe Amato, Paolo Bolettieri, Franca Debole, F...
In order to artificially boost the rank of commercial pages in search engine results, search engine optimizers pay for links to these pages on other websites. Identifying paid lin...
Most retrieval models estimate the relevance of each document to a query and rank the documents accordingly. However, such an approach ignores the uncertainty associated with the ...
Jianhan Zhu, Jun Wang, Ingemar J. Cox, Michael J. ...