Temporal query substitution for ad search

ABSTRACT

Recently, information retrieval researchers have witnessed the increasing interest in query substitution for ad search. Most previous works substitute search queries via content based query similarities, and few of them take the temporal characteristics of queries into consideration. In this extended abstract, we propose a novel temporal similarity measurement for query substitution in ad search task. We firstly extract temporal features, such as burst and periodicity, from query frequency curves and then define the temporal query similarity by integrating these new features with the temporal query frequency distribution. Compared to the traditional temporal similarity measurements such as correlation coefficient, our proposed approach is more effective owing to the explicit extraction of high-level semantic query temporal features for similarity measure. The experimental results demonstrate that the proposed similarity measure can make the ads more relevant to user search queries compared to ad search without temporal features.

REFERENCES

• 1: Filip Radlinski , Andrei Broder , Peter Ciccolo , Evgeniy Gabrilovich , Vanja Josifovski , Lance Riedel, Optimizing relevance and revenue in ad search: a query substitution approach, Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval, July 20-24, 2008, Singapore, Singapore [doi>10.1145/1390334.1390404]
• 2: Steve Chien , Nicole Immorlica, Semantic similarity between search engine queries using temporal correlation, Proceedings of the 14th international conference on World Wide Web, May 10-14, 2005, Chiba, Japan [doi>10.1145/1060745.1060752]
• 3: Michail Vlachos , Christopher Meek , Zografoula Vagena , Dimitrios Gunopulos, Identifying similarities, periodicities and bursts for online search queries, Proceedings of the 2004 ACM SIGMOD international conference on Management of data, June 13-18, 2004, Paris, France [doi>10.1145/1007568.1007586]

INDEX TERMS

Primary Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.3 Information Search and Retrieval

General Terms:
Algorithms

Keywords:
ad search, query substitution, temporal similarity.