"Driving curiosity in search with large-scale entity networks" by Ilaria Bordino, Mounia Lalmas, Yelena Mejova, and Olivier Van Laere with Martin Vesely as coordinator

In many search scenarios, users sometimes find unexpected, yet interesting and useful results, which make them curious; they experience serendipity. This curiosity encourages them to explore further. We developed an entity search system designed to support such an experience. The system explores the potential of entities extracted from two of the most popular sources of user-generated content -- Wikipedia, a user-curated online encyclopedia, and Yahoo Answers, a more unconstrained question & answering forum -- in promoting serendipitous search. The content of each data source is represented as a large network of entities, enriched with metadata about sentiment, writing quality, and topical category. A lazy random walk with restart is implemented to retrieve entities from the networks for a given entity query. This paper discusses our work, focusing on our experience in designing, developing, and evaluating such a system. We also discuss the challenges in developing large-scale systems that aim to drive curiosity in search.

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