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Stratified analysis of AOL query log

Autor(es) y otros:
Brenes Martínez, David JoséAutoridad Uniovi; Gayo Avello, DanielAutoridad Uniovi
Palabra(s) clave:

Query log analysis

User behaviour

User interactions

User intent

User profiling

Fecha de publicación:
2009
Editorial:

Elsevier

Versión del editor:
http://dx.doi.org/10.1016/j.ins.2009.01.027
Citación:
Information Sciences, 179 (12), p. 1844-1858 (2009); doi:10,1016/j.ins.2009.01.027
Descripción física:
p. 1844-1858
Resumen:

Characterizing user's intent and behaviour while using a retrieval information tool (e.g a search engine) is a key question on web research, as it hold the keys to know how the users interact, what they are expecting and how we can provide them information in the most bene cial way. Previous research has focused on identifying the average characteristics of user interactions. This paper proposes a strati ed method for analyzing query logs that groups queries and sessions according to their hit frequency and analyzes the characteristics of each group in order to nd how representative the average values are. Findings show that behaviours typically associated with the average user do not t in most of the aforementioned groups.

Characterizing user's intent and behaviour while using a retrieval information tool (e.g a search engine) is a key question on web research, as it hold the keys to know how the users interact, what they are expecting and how we can provide them information in the most bene cial way. Previous research has focused on identifying the average characteristics of user interactions. This paper proposes a strati ed method for analyzing query logs that groups queries and sessions according to their hit frequency and analyzes the characteristics of each group in order to nd how representative the average values are. Findings show that behaviours typically associated with the average user do not t in most of the aforementioned groups.

URI:
http://hdl.handle.net/10651/8385
ISSN:
0020-0255
DOI:
10.1016/j.ins.2009.01.027
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