The primary goal of today’s search and browsing techniques is to find relevant documents. As the current web evolves into the next generation termed the Semantic Web, the emphasis will shift from finding documents to finding facts, actionable information, and insights. Improving ability to extract facts, mainly in the form of entities, embedded within documents leads to the fundamental challenge of discovering relevant and interesting relationships amongst the entities that these documents describe. Relationships are fundamental to semantics—to associate meanings to words, terms and entities. Detecting semantic relations is at the heart of many research and analytical activities. Based on our research over the last few years, this presentation takes look at various new relationship based knowledge discovery techniques: (1) Our first technique finds the semantic relations between people, and measures collaboration strength to provide an estimate of potential Conflict of Interest in a peer-review scenario. (2) Secondly, we describe an approach that uses semantic relations to find experts using the implicit co-authorship network of the DBLP bibliography. (3) Thirdly, we present a novel entity disambiguation method that uses different relationships in a document as well as from the ontology to provide clues in determining the correct entity. (4) Finally, we present a new method to use semantic relationships for improved ranking of web documents.

DATE: 11 June, 2008, Wednesday@ 13:40
PLACE: EA 409