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Cross-Channel Query Recommendation on Commercial Mobile Search Engine: Why, How and Empirical Evaluation

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Advances in Knowledge Discovery and Data Mining (PAKDD 2009)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5476))

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Abstract

Mobile search not only inherits some features of traditional search on PC, but also has many of its own special characteristics. In this paper, we firstly share some unique features about mobile search and discuss why vertical search is preferred. Providing multiple vertical searches is proved to be convenient to users but causes some minor problem as well. This plays as the initiative for us to propose cross-channel query recommendation. Secondly, we briefly introduce how to realize the cross-channel recommendation effectively and efficiently online. Finally, we analyze the performance of the proposed method from three different but related metrics: expected effect, off-line evaluation and on-line evaluation. All three studies together indicate that the proposed cross-channel recommendation is quite useful. Being the first study about query recommendation on mobile search, it is believed that the findings, proposed solution and collected feedback as presented here will be beneficial to both researchers and industry companies while considering how to provide better mobile search service.

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References

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© 2009 Springer-Verlag Berlin Heidelberg

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Fu, S. et al. (2009). Cross-Channel Query Recommendation on Commercial Mobile Search Engine: Why, How and Empirical Evaluation. In: Theeramunkong, T., Kijsirikul, B., Cercone, N., Ho, TB. (eds) Advances in Knowledge Discovery and Data Mining. PAKDD 2009. Lecture Notes in Computer Science(), vol 5476. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01307-2_92

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  • DOI: https://doi.org/10.1007/978-3-642-01307-2_92

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-01306-5

  • Online ISBN: 978-3-642-01307-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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