Social search and discovery using a unified approach

This research explores new ways for augmenting search and discovery of relations between Web 2.0 entities using multi-ple types and sources of social information. Our goal is to al-low searching for all object types such as documents, persons and tags, while also retrieving related objects of all types. To realize this goal, we implemented a social-search engine using a unified approach. In this approach, the search space is expanded to represent heterogeneous information objects that are interrelated by several relation types. We address a novel solution 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 en-terprise, 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 they were retrieved for