Learning-to-rank algorithms, which can automatically adapt ranking functions in web search, require a large volume of training data. A traditional way of generating training examp...
This paper presents a loosely coupled service-composition paradigm. This paradigm employs a distributed data flow that differs markedly from centralized information flow adopted b...
David Liu, Jun Peng, Kincho H. Law, Gio Wiederhold
This paper describes Armil, a meta-search engine that groups the web snippets returned by auxiliary search engines into disjoint labeled clusters. The cluster labels generated by A...
Filippo Geraci, Marco Pellegrini, Marco Maggini, F...
In this paper we present a new document representation model based on implicit user feedback obtained from search engine queries. The main objective of this model is to achieve be...
In this paper we present an analysis of HTTP traffic captured from Internet caf?es and kiosks from two different developing countries ? Cambodia and Ghana. This paper has two main...