Lewandowski, D.: ¬The retrieval effectiveness of web search engines : considering results descriptions (2008)
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- Abstract
- Purpose - The purpose of this paper is to compare five major web search engines (Google, Yahoo, MSN, Ask.com, and Seekport) for their retrieval effectiveness, taking into account not only the results, but also the results descriptions. Design/methodology/approach - The study uses real-life queries. Results are made anonymous and are randomized. Results are judged by the persons posing the original queries. Findings - The two major search engines, Google and Yahoo, perform best, and there are no significant differences between them. Google delivers significantly more relevant result descriptions than any other search engine. This could be one reason for users perceiving this engine as superior. Research limitations/implications - The study is based on a user model where the user takes into account a certain amount of results rather systematically. This may not be the case in real life. Practical implications - The paper implies that search engines should focus on relevant descriptions. Searchers are advised to use other search engines in addition to Google. Originality/value - This is the first major study comparing results and descriptions systematically and proposes new retrieval measures to take into account results descriptions.
Lewandowski, D.; Mayr, P.: Exploring the academic invisible Web (2006)
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- Abstract
- Purpose: To provide a critical review of Bergman's 2001 study on the deep web. In addition, we bring a new concept into the discussion, the academic invisible web (AIW). We define the academic invisible web as consisting of all databases and collections relevant to academia but not searchable by the general-purpose internet search engines. Indexing this part of the invisible web is central to scientific search engines. We provide an overview of approaches followed thus far. Design/methodology/approach: Discussion of measures and calculations, estimation based on informetric laws. Literature review on approaches for uncovering information from the invisible web. Findings: Bergman's size estimate of the invisible web is highly questionable. We demonstrate some major errors in the conceptual design of the Bergman paper. A new (raw) size estimate is given. Research limitations/implications: The precision of our estimate is limited due to a small sample size and lack of reliable data. Practical implications: We can show that no single library alone will be able to index the academic invisible web. We suggest collaboration to accomplish this task. Originality/value: Provides library managers and those interested in developing academic search engines with data on the size and attributes of the academic invisible web.
