CS Colloquium: Suzan Verberne (Leiden Institute of Advanced Computer Science at Leiden University)
March 12 at 11:00 AM Eastern-Time
Explainable Information Retrieval
Abstract: In this presentation I will address the explainability of web search engines. I will present recent work in which we added explainable elements to the deep relevance matching model (DRMM). In a user study we showed that a visualization of these explainable elements on the search engine result page improved the assessability of the search results: users judge our proposed interface significantly more explainable and easier to assess than a regular search engine result page. This indicates that the explainability of the search engine result page leads to a better user experience. Our current research follows up on these results in the direction of professional search contexts. Explainable search is particularly relevant for professional search contexts, where users are critical towards search results and have the need to be in control. In these contexts, trust is even more important than in generic web search.
Bio: Suzan Verberne is an associate professor at the Leiden Institute of Advanced Computer Science at Leiden University. She is group leader of Text Mining and Retrieval (http://tmr.liacs.nl) in which she supervises 8 PhD students. She obtained her PhD in 2010 on the topic of Question Answering and has since then been working on the edge between Natural Language Processing and Information Retrieval. She has been involved in projects involving a large number of application domains and collaborations: from art history to law and from archeologists to medical specialists. Her recent work centers around interactive information access for specific domains. She is highly active in the NLP and IR communities, holding chairing positions in the large world-wide conferences.