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User Oriented Information Retrieval in a Collaborative and Context Aware Search Engine
| Citations: | 3 - 2 self |
BibTeX
@MISC{Angioni_useroriented,
author = {Manuela Angioni and Roberto Demontis and Massimo Deriu and Emanuela De Vita and Cristian Lai and Ivan Marcialis and Antonio Pintus and Andrea Piras and Alessandro Soro and Franco Tuveri},
title = {User Oriented Information Retrieval in a Collaborative and Context Aware Search Engine},
year = {}
}
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Abstract
Abstract: The web is the largest knowledge system who people can access. Unfortunately, its size makes very complex to find the right information. Search engines help people but they face user with a large amount of results, mostly useless, and he have to select one by one the right satisfying needs. To focus the attention on user requirements and involving the end-user in their systems, new search engines should evolve from keyword-based indexing and classification to more sophisticated techniques considering the meaning, the context and the usage of information. The key aspects are three: semantics, geo-referencing, collaboration. Semantic analysis lets to increase the results relevance. The geo-referencing of catalogued resources allows contextualisation based on user position. Collaboration distributes storage, processing and trust on a world-wide network of nodes running on users ’ computers, getting rid of bottlenecks and central points of failures. In this paper, we describe the studies, the concepts and the solutions developed in the DART project to introduce these three key features in a novel search engine architecture.
Keyphrases
user oriented information retrieval context aware search engine knowledge system central point novel search engine architecture help people dart project sophisticated technique world-wide network right information user requirement key feature new search engine large amount user computer keyword-based indexing semantic analysis let result relevance user position catalogued resource key aspect
