Discriminating meta-search: a framework for evaluation |
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| Institution: | 1. Interactive Media Laboratory, Department of Mechanical and Industrial Engineering, University of Toronto, King''s College Road, Toronto, Canada M5S 3G8;2. Knowledge Media Design Institute, University of Toronto, King''s College Road, Toronto, Canada M5S 3G8;1. Chemistry Department, University of Calgary, Calgary, Alta, Canada T2N 1N4;2. Sculich School of Engineering, University of Calgary, Calgary, Alta, Canada T2N 1N4;1. Geneva School of Economics and Management, University of Geneva, Uni-Mail, 1221 Geneva 4, Switzerland;2. Division of Market Development, International Trade Centre, Palais des Nations, 1211 Geneva 10, Switzerland;1. College of Communication and Media Sciences, Zayed University, United Arab Emirates;2. Media Management Sequence Coordinator, Department of Strategic, Legal, Management Communications, Graduate Department of Communication, Culture and Media Studies School of Communications Howard University, 2400 Sixth Street NW, Washington, DC, 20059, USA;1. Department of Geography, Environment and Geomatics, University of Guelph, Guelph, ON, Canada;2. Department of International and Area Studies, University of Oklahoma, Norman, OK, United States |
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| 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. |
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