Comparative web search questions

Alexander Bondarenko, Pavel Braslavski, Michael Völske, Rami Aly, Maik Fröbe, Alexander Panchenko, Chris Biemann, Benno Stein, Matthias Hagen

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    14 Citations (Scopus)

    Abstract

    We analyze comparative questions, i.e., questions asking to compare different items, that were submitted to Yandex in 2012. Responses to such questions might be quite different from the simple “ten blue links” and could, for example, aggregate pros and cons of the different options as direct answers. However, changing the result presentation is an intricate decision such that the classification of comparative questions forms a highly precision-oriented task. From a year-long Yandex log, we annotate a random sample of 50,000 questions; 2.8% of which are comparative. For these annotated questions, we develop a precision-oriented classifier by combining carefully hand-crafted lexico-syntactic rules with feature-based and neural approaches—achieving a recall of 0.6 at a perfect precision of 1.0. After running the classifier on the full year log (on average, there is at least one comparative question per second), we analyze 6,250 comparative questions using more fine-grained subclasses (e.g., should the answer be a “simple” fact or rather a more verbose argument) for which individual classifiers are trained. An important insight is that more than 65% of the comparative questions demand argumentation and opinions, i.e., reliable direct answers to comparative questions require more than the facts from a search engine’s knowledge graph. In addition, we present a qualitative analysis of the underlying comparative information needs (separated into 14 categories like consumer electronics or health), their seasonal dynamics, and possible answers from community question answering platforms.

    Original languageEnglish
    Title of host publicationWSDM 2020 - Proceedings of the 13th International Conference on Web Search and Data Mining
    PublisherAssociation for Computing Machinery, Inc
    Pages52-60
    Number of pages9
    ISBN (Electronic)9781450368223
    DOIs
    Publication statusPublished - 20 Jan 2020
    Event13th ACM International Conference on Web Search and Data Mining, WSDM 2020 - Houston, United States
    Duration: 3 Feb 20207 Feb 2020

    Publication series

    NameWSDM 2020 - Proceedings of the 13th International Conference on Web Search and Data Mining

    Conference

    Conference13th ACM International Conference on Web Search and Data Mining, WSDM 2020
    Country/TerritoryUnited States
    CityHouston
    Period3/02/207/02/20

    Keywords

    • Query log analysis
    • Question answering
    • Question classification

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