Estimating intent types for search result diversification

Kosetsu Tsukuda, Tetsuya Sakai, Zhicheng Dou, Katsumi Tanaka

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    4 Citations (Scopus)

    Abstract

    Given an ambiguous or underspecified query, search result diversification aims at accommodating different user intents within a single Search Engine Result Page (SERP). While automatic identification of different intents for a given query is a crucial step for result diversification, also important is the estimation of intent types (informational vs. navigational). If it is possible to distinguish between informational and navigational intents, search engines can aim to return one best URL for each navigational intent, while allocating more space to the informational intents within the SERP. In light of the observations, we propose a new framework for search result diversification that is intent importance-aware and type-aware. Our experiments using the NTCIR-9 INTENT Japanese Subtopic Mining and Document Ranking test collections show that: (a) our intent type estimation method for Japanese achieves 64.4% accuracy; and (b) our proposed diversification method achieves 0.6373 in D#-nDCG and 0.5898 in DIN#-nDCG over 56 topics, which are statistically significant gains over the top performers of the NTCIR-9 INTENT Japanese Document Ranking runs. Moreover, our relevance oriented model significantly outperforms our diversity oriented model and the original model by Dou et al..

    Original languageEnglish
    Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Pages25-37
    Number of pages13
    Volume8281 LNCS
    DOIs
    Publication statusPublished - 2013
    Event9th Asia Information Retrieval Societies Conference on Information Retrieval Technology, AIRS 2013 - Singapore
    Duration: 2013 Dec 92013 Dec 11

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Volume8281 LNCS
    ISSN (Print)03029743
    ISSN (Electronic)16113349

    Other

    Other9th Asia Information Retrieval Societies Conference on Information Retrieval Technology, AIRS 2013
    CitySingapore
    Period13/12/913/12/11

    Fingerprint

    Diversification
    Search engines
    Search Engine
    Ranking
    Websites
    Query
    Ambiguous
    Mining
    Model
    Experiments
    Experiment

    Keywords

    • Intent Type
    • Search Result Diversity
    • Subtopic

    ASJC Scopus subject areas

    • Computer Science(all)
    • Theoretical Computer Science

    Cite this

    Tsukuda, K., Sakai, T., Dou, Z., & Tanaka, K. (2013). Estimating intent types for search result diversification. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8281 LNCS, pp. 25-37). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8281 LNCS). https://doi.org/10.1007/978-3-642-45068-6_3

    Estimating intent types for search result diversification. / Tsukuda, Kosetsu; Sakai, Tetsuya; Dou, Zhicheng; Tanaka, Katsumi.

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 8281 LNCS 2013. p. 25-37 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8281 LNCS).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Tsukuda, K, Sakai, T, Dou, Z & Tanaka, K 2013, Estimating intent types for search result diversification. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 8281 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 8281 LNCS, pp. 25-37, 9th Asia Information Retrieval Societies Conference on Information Retrieval Technology, AIRS 2013, Singapore, 13/12/9. https://doi.org/10.1007/978-3-642-45068-6_3
    Tsukuda K, Sakai T, Dou Z, Tanaka K. Estimating intent types for search result diversification. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 8281 LNCS. 2013. p. 25-37. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-642-45068-6_3
    Tsukuda, Kosetsu ; Sakai, Tetsuya ; Dou, Zhicheng ; Tanaka, Katsumi. / Estimating intent types for search result diversification. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 8281 LNCS 2013. pp. 25-37 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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