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A Pinch of Humor for Short-Text Conversation: An Information Retrieval Approach

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Experimental IR Meets Multilinguality, Multimodality, and Interaction (CLEF 2017)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10456))

Abstract

The paper describes a work in progress on humorous response generation for short-text conversation using information retrieval approach. We gathered a large collection of funny tweets and implemented three baseline retrieval models: BM25, the query term reweighting model based on syntactic parsing and named entity recognition, and the doc2vec similarity model. We evaluated these models in two ways: in situ on a popular community question answering platform and in laboratory settings. The approach proved to be promising: even simple search techniques demonstrated satisfactory performance. The collection, test questions, evaluation protocol, and assessors’ judgments create a ground for future research towards more sophisticated models.

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Notes

  1. 1.

    https://www.apple.com/ios/siri/.

  2. 2.

    https://github.com/micyril/humor.

  3. 3.

    See for example http://www.hongkiat.com/blog/funny-twitter-accounts/.

  4. 4.

    https://github.com/ekzhu/datasketch.

  5. 5.

    https://twitter.com/MensHumor/status/360113491937472513.

  6. 6.

    https://answers.yahoo.com/dir/index?sid=396546041.

  7. 7.

    https://github.com/jhlau/doc2vec.

  8. 8.

    https://en.wikipedia.org/wiki/Big_Five_personality_traits.

  9. 9.

    http://eigentaste.berkeley.edu/about.html.

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Correspondence to Vladislav Blinov .

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Blinov, V., Mishchenko, K., Bolotova, V., Braslavski, P. (2017). A Pinch of Humor for Short-Text Conversation: An Information Retrieval Approach. In: Jones, G., et al. Experimental IR Meets Multilinguality, Multimodality, and Interaction. CLEF 2017. Lecture Notes in Computer Science(), vol 10456. Springer, Cham. https://doi.org/10.1007/978-3-319-65813-1_1

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  • DOI: https://doi.org/10.1007/978-3-319-65813-1_1

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