A collaborative, semantic and context-aware search engine
Caricamento...
Data
2007-06
Autori
Angioni, Manuela
Demontis, Roberto
Deriu, Massimo
De Vita, Emanuela
Lai, Cristian
Marcialis, Ivan
Paddeu, Gavino
Pintus, Antonio
Piras, Andrea
Sanna, Raffaella
Titolo del periodico
ISSN
Titolo del volume
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Abstract
Search engines help people to find information in the largest public knowledge system of the world: the Web. Unfortunately its size makes very complex to discover the right information. The users are faced lots of useless results forcing them to select one by one the most suitable. The new generation of search engines evolve from keyword-based indexing and classification to more sophisticated techniques considering the
meaning, the context and the usage of information. We argue about the three key aspects: collaboration, geo-referencing and semantics. 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. The
geo-referencing of catalogued resources allows contextualisation based on user position. Semantic analysis lets to increase the results relevance. In this paper, we expose the studies, the concepts and the solutions of a research project to introduce these three key features in a novel search engine architecture.
Descrizione
Keywords
search engine , community , location aware , semantics , NLP , RDHT , DART , 3D-UI