Social Search and Discovery Using a Unified Approach.
In:
HT '09: Proceedings of the Twentieth ACM Conference on Hypertext and Hypermedia.
ACM, New York, NY, USA, 2009.
Einat Amitay, David Carmel, Nadav Hare'l, Shila Ofek-Koifman, Aya Soffer, Sivan Yogev und Nadav Golbandi.
[Kurzfassung]
[BibTeX]
This research explores new ways to augment the search and discovery of relations between Web 2.0 entities using multiple types and sources of social information. Our goal is to allow the search for all object types such as documents, persons and tags, while retrieving related objects of all types. We implemented a social-search engine using a unified approach, where the search space is expanded to represent heterogeneous information objects that are interrelated by several relation types. Our solution is based on multifaceted search, which provides an efficient update mechanism for relations between objects, as well as efficient search over the heterogeneous data. We describe a social search engine positioned within a large enterprise, applied over social data gathered from several Web 2.0 applications. We conducted a large user study with over 600 people to evaluate the contribution of social data for search. Our results demonstrate the high precision of social search results and confirm the strong relationship of users and tags to the topics retrieved.