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Optimizing two-dimensional search results presentation

Published: 09 February 2011 Publication History

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.

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      cover image ACM Conferences
      WSDM '11: Proceedings of the fourth ACM international conference on Web search and data mining
      February 2011
      870 pages
      ISBN:9781450304931
      DOI:10.1145/1935826
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      Published: 09 February 2011

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      Author Tags

      1. image search
      2. markov chain
      3. page layout
      4. user scan model

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      WSDM '11 Paper Acceptance Rate 83 of 372 submissions, 22%;
      Overall Acceptance Rate 498 of 2,863 submissions, 17%

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      • (2023)Enriching Recommender Systems Results with Data about Sustainability and Ethical Standards of Brands2023 IEEE International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT)10.1109/WI-IAT59888.2023.00037(238-242)Online publication date: 26-Oct-2023
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      • (2019)A Markovian Approach to Evaluate Session-Based IR SystemsAdvances in Information Retrieval10.1007/978-3-030-15712-8_40(621-635)Online publication date: 7-Apr-2019
      • (2018)How Well do Offline and Online Evaluation Metrics Measure User Satisfaction in Web Image Search?The 41st International ACM SIGIR Conference on Research & Development in Information Retrieval10.1145/3209978.3210059(615-624)Online publication date: 27-Jun-2018
      • (2018)Optimizing Whole-Page Presentation for Web SearchACM Transactions on the Web10.1145/320446112:3(1-25)Online publication date: 17-Jul-2018
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