2009 | OriginalPaper | Buchkapitel
Cross-Channel Query Recommendation on Commercial Mobile Search Engine: Why, How and Empirical Evaluation
Erschienen in: Advances in Knowledge Discovery and Data Mining
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
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.