Social networks and discovery in the enterprise (SaND)

Traditional information discovery methods are based on content: documents, terms, and the relationships between them. In Web 2.0, people come into play as they create documents and tags in many forms. Personalized search, social graphs, content and people recommendation, are some of the tasks that can take advantage of this newly formed ecosystem. The Social Networks and Discovery (SaND) platform is an aggregation tool for information discovery and analysis over social data gathered from Web 2.0 applications in the enterprise. It leverages complex relationships between content and people as surfaced through the social applications to unleash the value of information. Its integrated index supports combining content-based analysis and people-based analysis over a rich data foundation. Enterprise social data is easily modeled and ingested into SaND, and can be further combined with data from external social applications. This demo will present three main functions provided by SaND: Social search: SaND supports search over the social data using a unified approach [1] in which all system entities (documents, people, tags) are searchable and retrievable (See Figure 1). The search UI enables the searcher to get a wider view on the query topic through results from all entity types, while uncovering the relationships between the on-screen entities. Entity recommendation: SaND can be utilized to recommend people and content for the searcher (Figure 2 shows the “Do You Know” widget for people recommendation). People are recommended according to their “social similarity” relations with the searcher, e.g. organizational and friending ties, similar tagging activity and more. Similarly, content that is related to people that are “socially related” to the searcher is recommended as valuable interesting data. Personalization: Search results are personalized by considering the relations of retrieved entities with the searcher. Entities are ranked according to their relevance to the query as well as according to their relationship strength with the searcher.