The query-flow graph: Model and applications

Paolo Boldi, Francesco Bonchi, Carlos Castillo, Debora Donato, Aristides Gionis, Sebastiano Vigna

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

216 Citations (Scopus)

Abstract

Query logs record the queries and the actions of the users of search engines, and as such they contain valuable information about the interests, the preferences, and the behavior of the users, as well as their implicit feedback to searchengine results. Mining the wealth of information available in the query logs has many important applications including query-log analysis, user profiling and personalization, advertising, query recommendation, and more. In this paper we introduce the query-flow graph, a graph representation of the interesting knowledge about latent querying behavior. Intuitively, in the query-flow graph a directed edge from query qi to query qj means that the two queries are likely to be part of the same "search mission". Any path over the query-flow graph may be seen as a searching behavior, whose likelihood is given by the strength of the edges along the path. The query-flow graph is an outcome of query-log mining and, at the same time, a useful tool for it. We propose a methodology that builds such a graph by mining time and textual information as well as aggregating queries from different users. Using this approach we build a real-world query-flow graph from a large-scale query log and we demonstrate its utility in concrete applications, namely, finding logical sessions, and query recommendation. We believe, however, that the usefulness of the query-flow graph goes beyond these two applications.

Original languageEnglish
Title of host publicationInternational Conference on Information and Knowledge Management, Proceedings
Pages609-617
Number of pages9
DOIs
Publication statusPublished - 1 Dec 2008
Externally publishedYes
Event17th ACM Conference on Information and Knowledge Management, CIKM'08 - Napa Valley, CA, United States
Duration: 26 Oct 200830 Oct 2008

Other

Other17th ACM Conference on Information and Knowledge Management, CIKM'08
CountryUnited States
CityNapa Valley, CA
Period26/10/0830/10/08

Fingerprint

Query
Graph model
Graph
Query logs
Implicit feedback
Query log analysis
Logic
Search engine
Profiling
Personalization
Wealth
Methodology
Usefulness

Keywords

  • Query flow graph
  • Query recommendation
  • Session segmentation

ASJC Scopus subject areas

  • Business, Management and Accounting(all)
  • Decision Sciences(all)

Cite this

Boldi, P., Bonchi, F., Castillo, C., Donato, D., Gionis, A., & Vigna, S. (2008). The query-flow graph: Model and applications. In International Conference on Information and Knowledge Management, Proceedings (pp. 609-617) https://doi.org/10.1145/1458082.1458163

The query-flow graph : Model and applications. / Boldi, Paolo; Bonchi, Francesco; Castillo, Carlos; Donato, Debora; Gionis, Aristides; Vigna, Sebastiano.

International Conference on Information and Knowledge Management, Proceedings. 2008. p. 609-617.

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

Boldi, P, Bonchi, F, Castillo, C, Donato, D, Gionis, A & Vigna, S 2008, The query-flow graph: Model and applications. in International Conference on Information and Knowledge Management, Proceedings. pp. 609-617, 17th ACM Conference on Information and Knowledge Management, CIKM'08, Napa Valley, CA, United States, 26/10/08. https://doi.org/10.1145/1458082.1458163
Boldi P, Bonchi F, Castillo C, Donato D, Gionis A, Vigna S. The query-flow graph: Model and applications. In International Conference on Information and Knowledge Management, Proceedings. 2008. p. 609-617 https://doi.org/10.1145/1458082.1458163
Boldi, Paolo ; Bonchi, Francesco ; Castillo, Carlos ; Donato, Debora ; Gionis, Aristides ; Vigna, Sebastiano. / The query-flow graph : Model and applications. International Conference on Information and Knowledge Management, Proceedings. 2008. pp. 609-617
@inproceedings{18e52e5f18b34274bc4cf011e8f14880,
title = "The query-flow graph: Model and applications",
abstract = "Query logs record the queries and the actions of the users of search engines, and as such they contain valuable information about the interests, the preferences, and the behavior of the users, as well as their implicit feedback to searchengine results. Mining the wealth of information available in the query logs has many important applications including query-log analysis, user profiling and personalization, advertising, query recommendation, and more. In this paper we introduce the query-flow graph, a graph representation of the interesting knowledge about latent querying behavior. Intuitively, in the query-flow graph a directed edge from query qi to query qj means that the two queries are likely to be part of the same {"}search mission{"}. Any path over the query-flow graph may be seen as a searching behavior, whose likelihood is given by the strength of the edges along the path. The query-flow graph is an outcome of query-log mining and, at the same time, a useful tool for it. We propose a methodology that builds such a graph by mining time and textual information as well as aggregating queries from different users. Using this approach we build a real-world query-flow graph from a large-scale query log and we demonstrate its utility in concrete applications, namely, finding logical sessions, and query recommendation. We believe, however, that the usefulness of the query-flow graph goes beyond these two applications.",
keywords = "Query flow graph, Query recommendation, Session segmentation",
author = "Paolo Boldi and Francesco Bonchi and Carlos Castillo and Debora Donato and Aristides Gionis and Sebastiano Vigna",
year = "2008",
month = "12",
day = "1",
doi = "10.1145/1458082.1458163",
language = "English",
isbn = "9781595939913",
pages = "609--617",
booktitle = "International Conference on Information and Knowledge Management, Proceedings",

}

TY - GEN

T1 - The query-flow graph

T2 - Model and applications

AU - Boldi, Paolo

AU - Bonchi, Francesco

AU - Castillo, Carlos

AU - Donato, Debora

AU - Gionis, Aristides

AU - Vigna, Sebastiano

PY - 2008/12/1

Y1 - 2008/12/1

N2 - Query logs record the queries and the actions of the users of search engines, and as such they contain valuable information about the interests, the preferences, and the behavior of the users, as well as their implicit feedback to searchengine results. Mining the wealth of information available in the query logs has many important applications including query-log analysis, user profiling and personalization, advertising, query recommendation, and more. In this paper we introduce the query-flow graph, a graph representation of the interesting knowledge about latent querying behavior. Intuitively, in the query-flow graph a directed edge from query qi to query qj means that the two queries are likely to be part of the same "search mission". Any path over the query-flow graph may be seen as a searching behavior, whose likelihood is given by the strength of the edges along the path. The query-flow graph is an outcome of query-log mining and, at the same time, a useful tool for it. We propose a methodology that builds such a graph by mining time and textual information as well as aggregating queries from different users. Using this approach we build a real-world query-flow graph from a large-scale query log and we demonstrate its utility in concrete applications, namely, finding logical sessions, and query recommendation. We believe, however, that the usefulness of the query-flow graph goes beyond these two applications.

AB - Query logs record the queries and the actions of the users of search engines, and as such they contain valuable information about the interests, the preferences, and the behavior of the users, as well as their implicit feedback to searchengine results. Mining the wealth of information available in the query logs has many important applications including query-log analysis, user profiling and personalization, advertising, query recommendation, and more. In this paper we introduce the query-flow graph, a graph representation of the interesting knowledge about latent querying behavior. Intuitively, in the query-flow graph a directed edge from query qi to query qj means that the two queries are likely to be part of the same "search mission". Any path over the query-flow graph may be seen as a searching behavior, whose likelihood is given by the strength of the edges along the path. The query-flow graph is an outcome of query-log mining and, at the same time, a useful tool for it. We propose a methodology that builds such a graph by mining time and textual information as well as aggregating queries from different users. Using this approach we build a real-world query-flow graph from a large-scale query log and we demonstrate its utility in concrete applications, namely, finding logical sessions, and query recommendation. We believe, however, that the usefulness of the query-flow graph goes beyond these two applications.

KW - Query flow graph

KW - Query recommendation

KW - Session segmentation

UR - http://www.scopus.com/inward/record.url?scp=70349237629&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=70349237629&partnerID=8YFLogxK

U2 - 10.1145/1458082.1458163

DO - 10.1145/1458082.1458163

M3 - Conference contribution

AN - SCOPUS:70349237629

SN - 9781595939913

SP - 609

EP - 617

BT - International Conference on Information and Knowledge Management, Proceedings

ER -