Persistent Link:
http://hdl.handle.net/10150/105146
Title:
Discriminating Meta-Search: A Framework for Evaluation
Author:
Chignell, Mark; Gwizdka, Jacek; Bodner, Richard
Citation:
Discriminating Meta-Search: A Framework for Evaluation 1999, 35(3):337-362 Information Processing and Management
Publisher:
Elsevier
Journal:
Information Processing and Management
Issue Date:
1999
Description:
DOI: 10.1016/S0306-4573(98)00065-X
URI:
http://hdl.handle.net/10150/105146
Submitted date:
2007-03-12
Abstract:
There was a proliferation of electronic information sources and search engines in the 1990s. Many of these information sources became available through the ubiquitous interface of the Web browser. Diverse information sources became accessible to information professionals and casual end users alike. Much of the information was also hyperlinked, so that information could be explored by browsing as well as searching. While vast amounts of information were now just a few keystrokes and mouseclicks away, as the choices multiplied, so did the complexity of choosing where and how to look for the electronic information. Much of the complexity in information exploration at the turn of the twenty-first century arose because there was no common cataloguing and control system across the various electronic information sources. In addition, the many search engines available differed widely in terms of their domain coverage, query methods, and efficiency. Meta-search engines were developed to improve search performance by querying multiple search engines at once. In principle, meta-search engines could greatly simplify the search for electronic information by selecting a subset of first-level search engines and digital libraries to submit a query to based on the characteristics of the user, the query/topic, and the search strategy. This selection would be guided by diagnostic knowledge about which of the first-level search engines works best under what circumstances. Programmatic research is required to develop this diagnostic knowledge about first-level search engine performance. This paper introduces an evaluative framework for this type of research and illustrates its use in two experiments. The experimental results obtained are used to characterize some properties of leading search engines (as of 1998). Significant interactions were observed between search engine and two other factors (time of day, and Web domain). These findings supplement those of earlier studies, providing preliminary information about the complex relationship between search engine functionality and performance in different contexts. While the specific results obtained represent a time-dependent snapshot of search engine performance in 1998, the evaluative framework proposed should be generally applicable in the future.
Type:
Journal Article (Paginated)
Language:
en
Keywords:
Web Metrics; Information Retrieval; Hypertext and Hypermedia; User Studies
Local subject classification:
Search engine evaluation; Meta-search engines

Full metadata record

DC FieldValue Language
dc.contributor.authorChignell, Marken_US
dc.contributor.authorGwizdka, Jaceken_US
dc.contributor.authorBodner, Richarden_US
dc.date.accessioned2007-03-12T00:00:01Z-
dc.date.available2010-06-18T23:20:12Z-
dc.date.issued1999en_US
dc.date.submitted2007-03-12en_US
dc.identifier.citationDiscriminating Meta-Search: A Framework for Evaluation 1999, 35(3):337-362 Information Processing and Managementen_US
dc.identifier.urihttp://hdl.handle.net/10150/105146-
dc.descriptionDOI: 10.1016/S0306-4573(98)00065-Xen_US
dc.description.abstractThere was a proliferation of electronic information sources and search engines in the 1990s. Many of these information sources became available through the ubiquitous interface of the Web browser. Diverse information sources became accessible to information professionals and casual end users alike. Much of the information was also hyperlinked, so that information could be explored by browsing as well as searching. While vast amounts of information were now just a few keystrokes and mouseclicks away, as the choices multiplied, so did the complexity of choosing where and how to look for the electronic information. Much of the complexity in information exploration at the turn of the twenty-first century arose because there was no common cataloguing and control system across the various electronic information sources. In addition, the many search engines available differed widely in terms of their domain coverage, query methods, and efficiency. Meta-search engines were developed to improve search performance by querying multiple search engines at once. In principle, meta-search engines could greatly simplify the search for electronic information by selecting a subset of first-level search engines and digital libraries to submit a query to based on the characteristics of the user, the query/topic, and the search strategy. This selection would be guided by diagnostic knowledge about which of the first-level search engines works best under what circumstances. Programmatic research is required to develop this diagnostic knowledge about first-level search engine performance. This paper introduces an evaluative framework for this type of research and illustrates its use in two experiments. The experimental results obtained are used to characterize some properties of leading search engines (as of 1998). Significant interactions were observed between search engine and two other factors (time of day, and Web domain). These findings supplement those of earlier studies, providing preliminary information about the complex relationship between search engine functionality and performance in different contexts. While the specific results obtained represent a time-dependent snapshot of search engine performance in 1998, the evaluative framework proposed should be generally applicable in the future.en_US
dc.format.mimetypeapplication/pdfen_US
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.subjectWeb Metricsen_US
dc.subjectInformation Retrievalen_US
dc.subjectHypertext and Hypermediaen_US
dc.subjectUser Studiesen_US
dc.subject.otherSearch engine evaluationen_US
dc.subject.otherMeta-search enginesen_US
dc.titleDiscriminating Meta-Search: A Framework for Evaluationen_US
dc.typeJournal Article (Paginated)en_US
dc.identifier.journalInformation Processing and Managementen_US
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