Abstract
The ultimate goal of an IR system is to fulfill the user’s information need. Traditional search systems have been reactive in nature wherein the search systems react to an input query and return a set of ranked documents most probable to contain the desired information. Due to the inability of, and efforts required by users to create efficient queries expressing their information needs, techniques such as query expansion, query suggestions, using relevance feedback and click-through information, personalization, etc. have been used to better understand and satisfy users’ information needs. Given the increasing popularity of smartphones and Internet enabled wearable devices, how can the information retrieval systems use the additional data, and better interact with the user so as to better understand, and even anticipate her precise information needs? Building such zero query or minimum user effort systems require research efforts from multiple disciplines covering algorithmic aspects of retrieval models, user modeling and profiling, evaluation, context modeling, novel user interfaces design, etc. The proposed workshop intends to gather together the researchers from academia and industry practitioners with these diverse backgrounds to share their experiences and opinions on challenges and possibilities of developing such proactive information retrieval systems.
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© 2016 Springer International Publishing Switzerland
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Bhatia, S., Majumdar, D., Aggarwal, N. (2016). Proactive Information Retrieval: Anticipating Users’ Information Need. In: Ferro, N., et al. Advances in Information Retrieval. ECIR 2016. Lecture Notes in Computer Science(), vol 9626. Springer, Cham. https://doi.org/10.1007/978-3-319-30671-1_84
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DOI: https://doi.org/10.1007/978-3-319-30671-1_84
Publisher Name: Springer, Cham
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