NDLI: Optimizing two-dimensional search results presentation

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Optimizing two-dimensional search results presentation

Content Provider	ACM Digital Library
Author	Kumar, Ravi Chierichetti, Flavio Raghavan, Prabhakar
Abstract	Classic search engine results are presented as an ordered list of documents and the problem of presentation trivially reduces to ordering documents by their scores. This is because users scan a list presentation from top to bottom. This leads to natural list optimization measures such as the discounted cumulative gain (DCG) and the rank-biased precision (RBP). Increasingly, search engines are using two-dimensional results presentations; image and shopping search results are long-standing examples. The simplistic heuristic used in practice is to place images by row-major order in the matrix presentation. However, a variety of evidence suggests that users' scan of pages is not in this matrix order. In this paper we (1) view users' scan of a results page as a Markov chain, which yields DCG and RBP as special cases for linear lists; (2) formulate, study, and develop solutions for the problem of inferring the Markov chain from click logs; (3) from these inferred Markov chains, empirically validate folklore phenomena (e.g., the "golden triangle" of user scans in two dimensions); and (4) develop and experimentally compare algorithms for optimizing user utility in matrix presentations. The theory and algorithms extend naturally beyond matrix presentations.
Starting Page	257
Ending Page	266
Page Count	10
File Format	PDF MP4
ISBN	9781450304931
DOI	10.1145/1935826.1935873
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2011-02-09
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Image search Markov chain Page layout User scan model
Content Type	Audio Text
Resource Type	Article

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