Context-aware query classification

ABSTRACT

Understanding users'search intent expressed through their search queries is crucial to Web search and online advertisement. Web query classification (QC) has been widely studied for this purpose. Most previous QC algorithms classify individual queries without considering their context information. However, as exemplified by the well-known example on query "jaguar", many Web queries are short and ambiguous, whose real meanings are uncertain without the context information. In this paper, we incorporate context information into the problem of query classification by using conditional random field (CRF) models. In our approach, we use neighboring queries and their corresponding clicked URLs (Web pages) in search sessions as the context information. We perform extensive experiments on real world search logs and validate the effectiveness and effciency of our approach. We show that we can improve the F1 score by 52% as compared to other state-of-the-art baselines.

REFERENCES

• 1: http://search.yahoo.com/dir.
• 2: http://www.google.com/dirhp?hl=en.
• 3: Rakesh Agrawal , Tomasz Imieliński , Arun Swami, Mining association rules between sets of items in large databases, Proceedings of the 1993 ACM SIGMOD international conference on Management of data, p.207-216, May 25-28, 1993, Washington, D.C., United States
• 4: Steven M. Beitzel , Eric C. Jensen , Abdur Chowdhury , David Grossman , Ophir Frieder, Hourly analysis of a very large topically categorized web query log, Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval, July 25-29, 2004, Sheffield, United Kingdom [doi>10.1145/1008992.1009048]
• 5: Steven M. Beitzel , Eric C. Jensen , Ophir Frieder , David Grossman , David D. Lewis , Abdur Chowdhury , Aleksandr Kolcz, Automatic web query classification using labeled and unlabeled training data, Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval, August 15-19, 2005, Salvador, Brazil [doi>10.1145/1076034.1076138]
• 6: Steven M. Beitzel , Eric C. Jensen , Ophir Frieder , David D. Lewis , Abdur Chowdhury , Aleksander Kolcz, Improving Automatic Query Classification via Semi-Supervised Learning, Proceedings of the Fifth IEEE International Conference on Data Mining, p.42-49, November 27-30, 2005 [doi>10.1109/ICDM.2005.80]
• 7: Broder, A., Z. A taxonomy of web search. In SIGIR Forums pages 3---10, 2002.
• 8: Andrei Z. Broder , Marcus Fontoura , Evgeniy Gabrilovich , Amruta Joshi , Vanja Josifovski , Tong Zhang, Robust classification of rare queries using web knowledge, Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval, July 23-27, 2007, Amsterdam, The Netherlands [doi>10.1145/1277741.1277783]
• 9: Huanhuan Cao , Daxin Jiang , Jian Pei , Qi He , Zhen Liao , Enhong Chen , Hang Li, Context-aware query suggestion by mining click-through and session data, Proceeding of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining, August 24-27, 2008, Las Vegas, Nevada, USA [doi>10.1145/1401890.1401995]
• 10: Huanhuan Cao , Daxin Jiang , Jian Pei , Enhong Chen , Hang Li, Towards context-aware search by learning a very large variable length hidden markov model from search logs, Proceedings of the 18th international conference on World wide web, April 20-24, 2009, Madrid, Spain [doi>10.1145/1526709.1526736]
• 11: Hang Cui , Ji-Rong Wen , Jian-Yun Nie , Wei-Ying Ma, Probabilistic query expansion using query logs, Proceedings of the 11th international conference on World Wide Web, May 07-11, 2002, Honolulu, Hawaii, USA [doi>10.1145/511446.511489]
• 12: Honghua (Kathy) Dai , Lingzhi Zhao , Zaiqing Nie , Ji-Rong Wen , Lee Wang , Ying Li, Detecting online commercial intention (OCI), Proceedings of the 15th international conference on World Wide Web, May 23-26, 2006, Edinburgh, Scotland [doi>10.1145/1135777.1135902]
• 13: Bruno M. Fonseca , Paulo Golgher , Bruno Pôssas , Berthier Ribeiro-Neto , Nivio Ziviani, Concept-based interactive query expansion, Proceedings of the 14th ACM international conference on Information and knowledge management, October 31-November 05, 2005, Bremen, Germany [doi>10.1145/1099554.1099726]
• 14: Jiafeng Guo , Gu Xu , Hang Li , Xueqi Cheng, A unified and discriminative model for query refinement, Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval, July 20-24, 2008, Singapore, Singapore [doi>10.1145/1390334.1390400]
• 15: He, D., et al. Detecting session boundaries from Web user logs. In Proceedings of BCS-IRSG 22nd Annual Colloquium on Information Retrieval Research, pages 57--66, 2000.
• 16: Qi He , Daxin Jiang , Zhen Liao , Steven C. H. Hoi , Kuiyu Chang , Ee-Peng Lim , Hang Li, Web Query Recommendation via Sequential Query Prediction, Proceedings of the 2009 IEEE International Conference on Data Engineering, p.1443-1454, March 29-April 02, 2009 [doi>10.1109/ICDE.2009.71]
• 17: Rosie Jones , Kristina Lisa Klinkner, Beyond the session timeout: automatic hierarchical segmentation of search topics in query logs, Proceeding of the 17th ACM conference on Information and knowledge management, October 26-30, 2008, Napa Valley, California, USA [doi>10.1145/1458082.1458176]
• 18: In-Ho Kang , GilChang Kim, Query type classification for web document retrieval, Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval, July 28-August 01, 2003, Toronto, Canada [doi>10.1145/860435.860449]
• 19: John D. Lafferty , Andrew McCallum , Fernando C. N. Pereira, Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data, Proceedings of the Eighteenth International Conference on Machine Learning, p.282-289, June 28-July 01, 2001
• 20: Uichin Lee , Zhenyu Liu , Junghoo Cho, Automatic identification of user goals in Web search, Proceedings of the 14th international conference on World Wide Web, May 10-14, 2005, Chiba, Japan [doi>10.1145/1060745.1060804]
• 21: Xiao Li , Ye-Yi Wang , Alex Acero, Learning query intent from regularized click graphs, Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval, July 20-24, 2008, Singapore, Singapore [doi>10.1145/1390334.1390393]
• 22: Mccallum, A. Efficiently inducing features of conditional random fields. In UAI'03, pages 403--410, 2003.
• 23: J. Scott Olsson , Douglas W. Oard , Jan Hajič, Cross-language text classification, Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval, August 15-19, 2005, Salvador, Brazil [doi>10.1145/1076034.1076170]
• 24: Daniel E. Rose , Danny Levinson, Understanding user goals in web search, Proceedings of the 13th international conference on World Wide Web, May 17-20, 2004, New York, NY, USA [doi>10.1145/988672.988675]
• 25: G. Salton , A. Wong , C. S. Yang, A vector space model for automatic indexing, Communications of the ACM, v.18 n.11, p.613-620, Nov. 1975 [doi>10.1145/361219.361220]
• 26: Burr Settles, ABNER: an open source tool for automatically tagging genes, proteins and other entity names in text, Bioinformatics, v.21 n.14, p.3191-3192, July 2005 [doi>10.1093/bioinformatics/bti475]
• 27: Dou Shen , Jian-Tao Sun , Qiang Yang , Zheng Chen, Building bridges for web query classification, Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval, August 06-11, 2006, Seattle, Washington, USA [doi>10.1145/1148170.1148196]
• 28: Charles Sutton , Khashayar Rohanimanesh , Andrew McCallum, Dynamic conditional random fields: factorized probabilistic models for labeling and segmenting sequence data, Proceedings of the twenty-first international conference on Machine learning, p.99, July 04-08, 2004, Banff, Alberta, Canada [doi>10.1145/1015330.1015422]
• 29: Ji-Rong Wen , Jian-Yun Nie , Hong-Jiang Zhang, Clustering user queries of a search engine, Proceedings of the 10th international conference on World Wide Web, p.162-168, May 01-05, 2001, Hong Kong, Hong Kong [doi>10.1145/371920.371974]

INDEX TERMS

Primary Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.m Miscellaneous

Additional Classification:
  I. Computing Methodologies
  I.5 PATTERN RECOGNITION
      I.5.2 Design Methodology
          Subjects: Classifier design and evaluation

General Terms:
Algorithms, Experimentation

Keywords:
query classification, search context