First query term extraction from current webpage for mobile applications

  • Authors:

  • Masayuki Okamoto;Nayuko Watanabe;Masaaki Kikuchi;Takayuki Iida;Kenta Sasaki;Kensuke Horiuchi;Tomohiro Yamasaki;Sumi Omura;Masanori Hattori

  • Affiliations:

  • Toshiba Corporation, Saiwai-ku, Kawasaki, Japan;Toshiba Corporation, Saiwai-ku, Kawasaki, Japan;Toshiba Corporation, Ome, Tokyo, Japan;Toshiba Corporation, Ome, Tokyo, Japan;Toshiba Corporation, Saiwai-ku, Kawasaki, Japan;Toshiba Corporation, Ome, Tokyo, Japan;Toshiba Corporation, Saiwai-ku, Kawasaki, Japan;Toshiba Corporation, Ome, Tokyo, Japan;Toshiba Corporation, Saiwai-ku, Kawasaki, Japan

  • Venue:
  • Proceedings of the 9th International Conference on Mobile and Ubiquitous Multimedia
  • Year:
  • 2010

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Abstract

Inputting query terms on a mobile terminal is frustrating because of device limitations though mobile web search is becoming popular. Query prediction is a promising approach for mobile search. In the literature, however, little attention has been paid to the first query term, though there are many reports on query expansion or second query recommendation. In this paper, we propose a first query prediction method that enables users to search related information for the current browsed webpage with an easier interface such as touch operation without any background search processes. The proposed method consists of body-text extraction, candidate query term extraction, and a scoring process. We also implemented a one-touch search application that works for Japanese webpages at a practical speed on a smartphone. According to our closed evaluation with 299 webpages and open evaluation with 14 users, our method achieved practical quality.