Search (2 results, page 1 of 1)

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Abstract

Information seeking is a fundamental human activity. In the modern world, it is frequently conducted through interactions with search systems. The retrieval and comprehension of information returned by these systems is a key part of decision making and action in a broad range of settings. Advances in data availability coupled with new interaction paradigms, and mobile and cloud computing capabilities, have created a broad range of new opportunities for information access and use. In this comprehensive book for professionals, researchers, and students involved in search system design and evaluation, search expert Ryen White discusses how search systems can capitalize on new capabilities and how next-generation systems must support higher order search activities such as task completion, learning, and decision making. He outlines the implications of these changes for the evolution of search evaluation, as well as challenges that extend beyond search systems in areas such as privacy and societal benefit.

Footnote

Vgl. auch den Beitrag: Lewandowski, D.: Wie "Next Generation Search Systems" die Suche auf eine neue Ebene heben und die Informationswelt verändern. In: http://www.password-online.de/?wysija-page=1&controller=email&action=view&email_id=254&wysijap=subscriptions&user_id=1045..

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Abstract

The aim of the work described in this paper is to evaluate the influencing effects of query-biased summaries in web searching. For this purpose, a summarisation system has been developed, and a summary tailored to the user's query is generated automatically for each document retrieved. The system aims to provide both a better means of assessing document relevance than titles or abstracts typical of many web search result lists. Through visiting each result page at retrieval-time, the system provides the user with an idea of the current page content and thus deals with the dynamic nature of the web. To examine the effectiveness of this approach, a task-oriented, comparative evaluation between four different web retrieval systems was performed; two that use query-biased summarisation, and two that use the standard ranked titles/abstracts approach. The results from the evaluation indicate that query-biased summarisation techniques appear to be more useful and effective in helping users gauge document relevance than the traditional ranked titles/abstracts approach. The same methodology was used to compare the effectiveness of two of the web's major search engines; AltaVista and Google.