Adaptive Information Retrieval Adaptive Result Composition Personalized Search Socio-Semantic Search
Ben Steichen, Vincent Wade, Adaptive Retrieval and Composition of Socio-Semantic Content for Personalised Customer Care, CEUR Workshop Proceedings, International Workshop on Adaptation in Social and Semantic Web (SAS-WEB 2010) in connection with UMAP 2010, Waikoloa, HI, USA, June 21, 2010, Federica Cena, Antonina Dattolo, Styliani Kleanthous, Carlo Tasso, David Bueno Vallejo, and Julita Vassileva, CEUR-WS.org, 2010, 1 - 10
The parallel rise of the Semantic and Social Web provides unprecedented possibilities for the development of novel search system architectures. However, many traditional search systems have so far followed a simple one-size-fits-all paradigm by ignoring the different user information needs, preferences and intentions. In the last number of years, we have begun to
see initial evidence that personalisation may be applied within web search engines, however little detail has been published other than adaptation based on user histories. Moreover, current implementations often fail to combine the
mutual benefits of both structured and unstructured information resources. This paper presents techniques and architectures for leveraging socio-semantic content and adaptively retrieving and composing such content in order to provide personalised result presentations. The system is presented in a customer care scenario, which provides an application area for personalisation in terms of available heterogeneous resources as well as user preferences, context and characteristics. The presented architectures combine techniques from the fields of Information Retrieval, Semantic Search as well as Adaptive Hypermedia in order to enable efficient adaptive retrieval as well as personalised compositions.
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