Dynamic query intent mining from a search log stream

Yanan Qian, Tetsuya Sakai, Junting Ye, Qinghua Zheng, Cong Li

研究成果: Conference contribution

14 被引用数 (Scopus)

抄録

It has long been recognized that search queries are often broad and ambiguous. Even when submitting the same query, different users may have different search intents. Moreover, the intents are dynamically evolving. Some intents are constantly popular with users, others are more bursty. We propose a method for mining dynamic query intents from search query logs. By regarding the query logs as a data stream, we identify constant intents while quickly capturing new bursty intents. To evaluate the accuracy and efficiency of our method, we conducted experiments using 50 topics from the NTCIR INTENT-9 data and additional five popular topics, all supplemented with six-month query logs from a commercial search engine. Our results show that our method can accurately capture new intents with short response time.

本文言語English
ホスト出版物のタイトルCIKM 2013 - Proceedings of the 22nd ACM International Conference on Information and Knowledge Management
ページ1205-1208
ページ数4
DOI
出版ステータスPublished - 2013
イベント22nd ACM International Conference on Information and Knowledge Management, CIKM 2013 - San Francisco, CA, United States
継続期間: 2013 10 272013 11 1

出版物シリーズ

名前International Conference on Information and Knowledge Management, Proceedings

Conference

Conference22nd ACM International Conference on Information and Knowledge Management, CIKM 2013
国/地域United States
CitySan Francisco, CA
Period13/10/2713/11/1

ASJC Scopus subject areas

  • 決定科学(全般)
  • ビジネス、管理および会計(全般)

フィンガープリント

「Dynamic query intent mining from a search log stream」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

引用スタイル