Aging effects on query flow graphs for query suggestion

Ranieri Baraglia, Carlos Castillo, Debora Donato, Franco Maria Nardini, Raffaele Perego, Fabrizio Silvestri

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

17 Citations (Scopus)

Abstract

World Wide Web content continuously grows in size and importance. Furthermore, users ask Web search engines to satisfy increasingly disparate information needs. New techniques and tools are constantly developed aimed at assisting users in the interaction with the Web search engine. Query recommender systems suggesting interesting queries to users are an example of such tools. Most query recommendation techniques are based on the knowledge of the behaviors of past users of the search engine recorded in query logs. A recent query-log mining approach for query recommendation is based on Query Flow Graphs (QFG). In this paper we propose an evaluation of the effects of time on this query recommendation model. As users interests change over time, the knowledge extracted from query logs may suffer an aging effect as new interesting topics appear. In order to validate experimentally this hypothesis, we build different query flow graphs from the queries belonging to a large query log of a real-world search engine. Each query flow graph is built on distinct query log segments. Then, we generate recommendations on different sets of queries. Results are assessed both by means of human judgments and by using an automatic evaluator showing that the models inexorably age.

Original languageEnglish
Title of host publicationInternational Conference on Information and Knowledge Management, Proceedings
Pages1947-1950
Number of pages4
DOIs
Publication statusPublished - 1 Dec 2009
Externally publishedYes
EventACM 18th International Conference on Information and Knowledge Management, CIKM 2009 - Hong Kong, China
Duration: 2 Nov 20096 Nov 2009

Other

OtherACM 18th International Conference on Information and Knowledge Management, CIKM 2009
CountryChina
CityHong Kong
Period2/11/096/11/09

Fingerprint

Graph
Query
Query logs
Search engine
Web search
Recommender systems
Interaction
Evaluation
Information needs
World Wide Web
Evaluator

Keywords

  • Aging effects
  • Effectiveness in query recommendations
  • Query flow graph
  • Query suggestion
  • Topic drift

ASJC Scopus subject areas

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

Cite this

Baraglia, R., Castillo, C., Donato, D., Nardini, F. M., Perego, R., & Silvestri, F. (2009). Aging effects on query flow graphs for query suggestion. In International Conference on Information and Knowledge Management, Proceedings (pp. 1947-1950) https://doi.org/10.1145/1645953.1646272

Aging effects on query flow graphs for query suggestion. / Baraglia, Ranieri; Castillo, Carlos; Donato, Debora; Nardini, Franco Maria; Perego, Raffaele; Silvestri, Fabrizio.

International Conference on Information and Knowledge Management, Proceedings. 2009. p. 1947-1950.

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

Baraglia, R, Castillo, C, Donato, D, Nardini, FM, Perego, R & Silvestri, F 2009, Aging effects on query flow graphs for query suggestion. in International Conference on Information and Knowledge Management, Proceedings. pp. 1947-1950, ACM 18th International Conference on Information and Knowledge Management, CIKM 2009, Hong Kong, China, 2/11/09. https://doi.org/10.1145/1645953.1646272
Baraglia R, Castillo C, Donato D, Nardini FM, Perego R, Silvestri F. Aging effects on query flow graphs for query suggestion. In International Conference on Information and Knowledge Management, Proceedings. 2009. p. 1947-1950 https://doi.org/10.1145/1645953.1646272
Baraglia, Ranieri ; Castillo, Carlos ; Donato, Debora ; Nardini, Franco Maria ; Perego, Raffaele ; Silvestri, Fabrizio. / Aging effects on query flow graphs for query suggestion. International Conference on Information and Knowledge Management, Proceedings. 2009. pp. 1947-1950
@inproceedings{5b90e67d5eb945278fdb42b4373c1775,
title = "Aging effects on query flow graphs for query suggestion",
abstract = "World Wide Web content continuously grows in size and importance. Furthermore, users ask Web search engines to satisfy increasingly disparate information needs. New techniques and tools are constantly developed aimed at assisting users in the interaction with the Web search engine. Query recommender systems suggesting interesting queries to users are an example of such tools. Most query recommendation techniques are based on the knowledge of the behaviors of past users of the search engine recorded in query logs. A recent query-log mining approach for query recommendation is based on Query Flow Graphs (QFG). In this paper we propose an evaluation of the effects of time on this query recommendation model. As users interests change over time, the knowledge extracted from query logs may suffer an aging effect as new interesting topics appear. In order to validate experimentally this hypothesis, we build different query flow graphs from the queries belonging to a large query log of a real-world search engine. Each query flow graph is built on distinct query log segments. Then, we generate recommendations on different sets of queries. Results are assessed both by means of human judgments and by using an automatic evaluator showing that the models inexorably age.",
keywords = "Aging effects, Effectiveness in query recommendations, Query flow graph, Query suggestion, Topic drift",
author = "Ranieri Baraglia and Carlos Castillo and Debora Donato and Nardini, {Franco Maria} and Raffaele Perego and Fabrizio Silvestri",
year = "2009",
month = "12",
day = "1",
doi = "10.1145/1645953.1646272",
language = "English",
isbn = "9781605585123",
pages = "1947--1950",
booktitle = "International Conference on Information and Knowledge Management, Proceedings",

}

TY - GEN

T1 - Aging effects on query flow graphs for query suggestion

AU - Baraglia, Ranieri

AU - Castillo, Carlos

AU - Donato, Debora

AU - Nardini, Franco Maria

AU - Perego, Raffaele

AU - Silvestri, Fabrizio

PY - 2009/12/1

Y1 - 2009/12/1

N2 - World Wide Web content continuously grows in size and importance. Furthermore, users ask Web search engines to satisfy increasingly disparate information needs. New techniques and tools are constantly developed aimed at assisting users in the interaction with the Web search engine. Query recommender systems suggesting interesting queries to users are an example of such tools. Most query recommendation techniques are based on the knowledge of the behaviors of past users of the search engine recorded in query logs. A recent query-log mining approach for query recommendation is based on Query Flow Graphs (QFG). In this paper we propose an evaluation of the effects of time on this query recommendation model. As users interests change over time, the knowledge extracted from query logs may suffer an aging effect as new interesting topics appear. In order to validate experimentally this hypothesis, we build different query flow graphs from the queries belonging to a large query log of a real-world search engine. Each query flow graph is built on distinct query log segments. Then, we generate recommendations on different sets of queries. Results are assessed both by means of human judgments and by using an automatic evaluator showing that the models inexorably age.

AB - World Wide Web content continuously grows in size and importance. Furthermore, users ask Web search engines to satisfy increasingly disparate information needs. New techniques and tools are constantly developed aimed at assisting users in the interaction with the Web search engine. Query recommender systems suggesting interesting queries to users are an example of such tools. Most query recommendation techniques are based on the knowledge of the behaviors of past users of the search engine recorded in query logs. A recent query-log mining approach for query recommendation is based on Query Flow Graphs (QFG). In this paper we propose an evaluation of the effects of time on this query recommendation model. As users interests change over time, the knowledge extracted from query logs may suffer an aging effect as new interesting topics appear. In order to validate experimentally this hypothesis, we build different query flow graphs from the queries belonging to a large query log of a real-world search engine. Each query flow graph is built on distinct query log segments. Then, we generate recommendations on different sets of queries. Results are assessed both by means of human judgments and by using an automatic evaluator showing that the models inexorably age.

KW - Aging effects

KW - Effectiveness in query recommendations

KW - Query flow graph

KW - Query suggestion

KW - Topic drift

UR - http://www.scopus.com/inward/record.url?scp=74549120803&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=74549120803&partnerID=8YFLogxK

U2 - 10.1145/1645953.1646272

DO - 10.1145/1645953.1646272

M3 - Conference contribution

SN - 9781605585123

SP - 1947

EP - 1950

BT - International Conference on Information and Knowledge Management, Proceedings

ER -