Evaluating Relevance Feedback Algorithms for Searching on Small Displays

@incollection{citeulike:2174763, abstract = {Searching online information resources using mobile devices is affected by displays on which only a small fraction of the set of ranked documents can be displayed. In this paper, we ask whether the search effort can be reduced, on average, by user feedback indicating a single most relevant document in each display. For small display sizes and limited user actions, we are able to construct a tree representing all possible outcomes. Examination of the tree permits us to compute an upper limit on relevance feedback performance. Three standard feedback algorithms are considered - Rocchio, Robertson/Sparck-Jones and a Bayesian algorithm. Two display strategies are considered, one based on maximizing the immediate information gain and the other on most likely documents. Our results bring out the strengths and weaknesses of the algorithms, and the need for exploratory display strategies with conservative feedback algorithms.}, author = {Vinay, Vishwa and Cox, Ingemar J. and Milic-Frayling, Natasa and Wood, Ken }, citeulike-article-id = {2174763}, journal = {Advances in Information Retrieval}, keywords = {hci, mobile, relevance\_feedback}, pages = {185--199}, posted-at = {2008-02-18 11:59:45}, priority = {2}, title = {Evaluating Relevance Feedback Algorithms for Searching on Small Displays}, url = {http://www.springerlink.com/content/qf4v06ug0jn6ntff }, year = {2005} }

TY - CHAP ID - citeulike:2174763 L3 - citeulike-article-id:2174763 TI - Evaluating Relevance Feedback Algorithms for Searching on Small Displays JF - Advances in Information Retrieval SP - 185 EP - 199 N2 - Searching online information resources using mobile devices is affected by displays on which only a small fraction of the set of ranked documents can be displayed. In this paper, we ask whether the search effort can be reduced, on average, by user feedback indicating a single most relevant document in each display. For small display sizes and limited user actions, we are able to construct a tree representing all possible outcomes. Examination of the tree permits us to compute an upper limit on relevance feedback performance. Three standard feedback algorithms are considered - Rocchio, Robertson/Sparck-Jones and a Bayesian algorithm. Two display strategies are considered, one based on maximizing the immediate information gain and the other on most likely documents. Our results bring out the strengths and weaknesses of the algorithms, and the need for exploratory display strategies with conservative feedback algorithms. KW - hci KW - mobile KW - relevance_feedback AU - Vinay, Vishwa AU - Cox, Ingemar AU - Milic-Frayling, Natasa AU - Wood, Ken PY - 2005/// UR - http://www.springerlink.com/content/qf4v06ug0jn6ntff ER -