Varying approaches to topical web query classification

ABSTRACT

Topical classification of web queries has drawn recent interest because of the promise it offers in improving retrieval effectiveness and efficiency. However, much of this promise depends on whether classification is performed before or after the query is used to retrieve documents. We examine two previously unaddressed issues in query classification: pre versus post-retrieval classification effectiveness and the effect of training explicitly from classified queries versus bridging a classifier trained using a document taxonomy. Bridging classifiers map the categories of a document taxonomy onto those of a query classification problem to provide sufficient training data. We find that training classifiers explicitly from manually classified queries outperforms the bridged classifier by 48% in F1 score. Also, a pre-retrieval classifier using only the query terms performs merely 11% worse than the bridged classifier which requires snippets from retrieved documents.

REFERENCES

• 1: 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]
• 2: Ying Li , Zijian Zheng , Honghua (Kathy) Dai, KDD CUP-2005 report: facing a great challenge, ACM SIGKDD Explorations Newsletter, v.7 n.2, p.91-99, December 2005 [doi>10.1145/1117454.1117466]
• 3: 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]

INDEX TERMS

Primary Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.5 On-line Information Services
          Subjects: Web-based services

General Terms:
Experimentation, Measurement, Reliability

Keywords:
query classification, web search