Kumaripaba Athukorala defends her PhD thesis on Information Search as Adaptive Interaction on October 12th, 2016
M.Sc. Kumaripaba Athukorala will defend her doctoral thesis Information Search as Adaptive Interaction in the University of Helsinki Main Building, Auditorium XIII (Unioninkatu 34, 3rd floor) on Wednesday the 12th of October 2016 at 12 o'clock. Her opponent is Assistant Professor Robert Capra (University of North Carolina at Chapel Hill, USA) and custos Professor Giulio Jacucci (University of Helsinki). The defence will be held in English.
Information Search as Adaptive
We use information retrieval (IR) systems to meet a broad range of information needs, from simple ones involving day-to-day decisions to complex and imprecise information needs that cannot be easily formulated as a question. In consideration of these diverse goals, search activities are commonly divided into two broad categories: lookup and exploratory. Lookup searches begin with precise search goals and end soon after reaching of the target, while exploratory searches center on learning or investigation activities with imprecise search goals. Although exploration is a prominent life activity, it is naturally challenging for users because they lack domain knowledge; at the same time, information needs are broad, complex, and subject to constant change. It is also rather difficult for IR systems to offer support for exploratory searches, not least because of the complex information needs and dynamic nature of the user. It is hard also to conceptualize exploration distinctly. In consequence, most of the popular IR systems are targeted at lookup searches only. There is a clear need for better IR systems that support a wide range of search activities.
The primary objective for this thesis is to enable the design of IR systems that support exploratory and lookup searches equally well. I approached this problem by modeling information search as a rational adaptation of interactions, which aids in clear conceptualization of exploratory and lookup searches. In work building on an existing framework for examination of adaptive interaction, it is assumed that three main factors influence how we interact with search systems: the ecological structure of the environment, our cognitive and perceptual limits, and the goal of optimizing the tradeoff between information gain and time cost. This thesis contributes three models developed in research proceeding from this adaptive interaction framework, to 1) predict evolving information needs in exploratory searches, 2) distinguish between exploratory and lookup tasks, and 3) predict the emergence of adaptive search strategies. It concludes with development of an approach that integrates the proposed models for the design of an IR system that provides adaptive support for both exploratory and lookup searches.
The findings confirm the ability to model information search as adaptive interaction. The models developed in the thesis project have been empirically validated through user studies, with an adaptive search system that emphasizes the practical implications of the models for supporting several types of searches. The studies conducted with the adaptive search system further confirm that IR systems could improve information search performance by dynamically adapting to the task type. The thesis contributes an approach that could prove fruitful for future IR systems in efforts to offer more efficient and less challenging search experiences.
Availability of the dissertation
An electronic version of the doctoral dissertation is available on the e-thesis site of the University of Helsinki at http://urn.fi/URN:ISBN:978-951-51-2517-0.
Printed copies will be available on request from Kumaripaba Athukorala: kumaripaba.athukorala@cs.helsinki.fi.