An optimization framework for query recommendation

Aris Anagnostopoulos, Luca Becchetti, Carlos Castillo, Aristides Gionis

Research output: Chapter in Book/Report/Conference proceedingConference contribution

57 Citations (Scopus)

Abstract

Query recommendation is an integral part of modern search engines. The goal of query recommendation is to facilitate users while searching for information. Query recommendation also allows users to explore concepts related to their information needs. In this paper, we present a formal treatment of the problem of query recommendation. In our framework we model the querying behavior of users by a probabilistic reformulation graph, or query-flow graph [Boldi et al. CIKM 2008]. A sequence of queries submitted by a user can be seen as a path on this graph. Assigning score values to queries allows us to define suitable utility functions and to consider the expected utility achieved by a reformulation path on the query-flow graph. Providing recommendations can be seen as adding shortcuts in the query-flow graph that "nudge" the reformulation paths of users, in such a way that users are more likely to follow paths with larger expected utility. We discuss in detail the most important questions that arise in the proposed framework. In particular, we provide examples of meaningful utility functions to optimize, we discuss how to estimate the effect of recommendations on the reformulation probabilities, we address the complexity of the optimization problems that we consider, we suggest efficient algorithmic solutions, and we validate our models and algorithms with extensive experimentation. Our techniques can be applied to other scenarios where user behavior can be modeled as a Markov process.

Original languageEnglish
Title of host publicationWSDM 2010 - Proceedings of the 3rd ACM International Conference on Web Search and Data Mining
Pages161-170
Number of pages10
DOIs
Publication statusPublished - 21 Apr 2010
Externally publishedYes
Event3rd ACM International Conference on Web Search and Data Mining, WSDM 2010 - New York City, NY, United States
Duration: 3 Feb 20106 Feb 2010

Other

Other3rd ACM International Conference on Web Search and Data Mining, WSDM 2010
CountryUnited States
CityNew York City, NY
Period3/2/106/2/10

Fingerprint

Flow graphs
Search engines
Markov processes

Keywords

  • Query reformulations
  • Query suggestions

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Software

Cite this

Anagnostopoulos, A., Becchetti, L., Castillo, C., & Gionis, A. (2010). An optimization framework for query recommendation. In WSDM 2010 - Proceedings of the 3rd ACM International Conference on Web Search and Data Mining (pp. 161-170) https://doi.org/10.1145/1718487.1718508

An optimization framework for query recommendation. / Anagnostopoulos, Aris; Becchetti, Luca; Castillo, Carlos; Gionis, Aristides.

WSDM 2010 - Proceedings of the 3rd ACM International Conference on Web Search and Data Mining. 2010. p. 161-170.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Anagnostopoulos, A, Becchetti, L, Castillo, C & Gionis, A 2010, An optimization framework for query recommendation. in WSDM 2010 - Proceedings of the 3rd ACM International Conference on Web Search and Data Mining. pp. 161-170, 3rd ACM International Conference on Web Search and Data Mining, WSDM 2010, New York City, NY, United States, 3/2/10. https://doi.org/10.1145/1718487.1718508
Anagnostopoulos A, Becchetti L, Castillo C, Gionis A. An optimization framework for query recommendation. In WSDM 2010 - Proceedings of the 3rd ACM International Conference on Web Search and Data Mining. 2010. p. 161-170 https://doi.org/10.1145/1718487.1718508
Anagnostopoulos, Aris ; Becchetti, Luca ; Castillo, Carlos ; Gionis, Aristides. / An optimization framework for query recommendation. WSDM 2010 - Proceedings of the 3rd ACM International Conference on Web Search and Data Mining. 2010. pp. 161-170
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