Search (2 results, page 1 of 1)

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Abstract

A growing body of research is beginning to explore the information-seeking behavior of Web users. The vast majority of these studies have concentrated on the area of textual information retrieval (IR). Little research has examined how people search for non-textual information on the Internet, and few large-scale studies have investigated visual information-seeking behavior with Web search engines. This study examined visual information needs as expressed in users' Web image queries. The data set examined consisted of 1,025,908 sequential queries from 211,058 users of EXCITE, a major Internet search service. Twenty-eight (28) terms were used to identify queries for both still and moving images, resulting in a subset of 33,149 image queries by 9,855 users. We provide data on: (1) image queries -- the number of queries and the number of search terms per user, (2) image search sessions -- the number of queries per user, modifications made to subsequent queries in a session, and (3) image terms -- their rank/frequency distribution and the most highly used search terms. On average, there were 3. 36 image queries per user containing an average of 3.74 terms per query. Image queries contained a large number of unique terms. The most frequently occurring image related terms appeared less than 10 percent of the time, with most terms occurring only once. This analysis is contrasted to earlier work by Enser (1995) who examined written queries for pictorial information in a non-digital environment. Implications for the development of models for visual information retrieval, and for the design of Web search engines are discussed

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Abstract

Defining works is complex, but defining video works is extremely complex because of the large number of instantiations available and because of the intricate relationships among them. The terrorist attacks on the World Trade Center on September 11, 2001 and other important news events offer rich examples of the complexity of the problem and help us gain an understanding of how managing video news material can be modelled. The need for a taxonomy of some of the instantiations of material that need to be managed in the context of a news video library is identified.