This item is a Poster.
- Amitay, Einat - IBM Research Laboratory Haifa
- Carmel, David - IBM Research Laboratory Haifa
- Har'El, Nadav - IBM Research Laboratory Haifa
- Ofek-Koifman, Shila - IBM Research Laboratory Haifa
- Soffer, Aya - IBM Research Laboratory Haifa
- Yogev, Sivan - IBM Research Laboratory Haifa
- Golbandi, Nadav - IBM Research Laboratory Haifa
We explore new ways of improving a search engine using data from Web 2.0 applications such as blogs and social bookmarks. This data contains entities such as documents, people and tags, and relationships between them. We propose a simple yet effective method, based on faceted search, that treats all entities in a uniﬁed manner: returning all of them (documents, people and tags) on every search, and allowing all of them to be used as search terms. We describe an implementation of such a social search engine on the intranet of a large enterprise, and present large-scale experiments which verify the validity of our approach.
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