Inferring Searcher Attention and Intention by Mining Behavior Data

Eugene Agichtein was Keynote speaker at the 36TH EUROPEAN CONFERENCE ON INFORMATION RETRIEVAL (ECIR 2014) in Amsterdam where he gave a speech very relevant to MindSee tilted: Inferring Searcher Attention and Intention by Mining Behavior Data.

Here's the abstract: A long standing challenge in Web search is how to accurately determine the intention behind a searcher’s query, which is needed to rank, organize, and present results most effectively. The difficulty is that users often do not (or cannot) provide sufficient information about their goals. As this talk with show, it is nevertheless possible to read their intentions through clues revealed by behavior, such as the amount of attention paid to a document or a text fragment. I will overview the approaches that have emerged for acquiring and mining behavioral data for inferring search intent, ranging from robust models of click data in the aggregate, to modeling fine-grained user interactions such as mouse cursor movements in the searcher’s browser. The latter can also be used to measure the searcher’s attention “in the wild’’, with granularity approaching that of using eye tracking equipment in the laboratory. The resulting techniques and models have already shown noteworthy improvements for search tasks such as ranking, relevance estimation, and result summary generation, and have applications to other domains, such as psychology, neurology, and online education.