Search (3 results, page 1 of 1)

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Abstract

News is information about recent events of general interest, especially as currently reportes by newspapers, periodicals, radio or television. News is the quintessential multimedia data. While newspaper editors (human and/or algorithmic) may still define the core content of electronic news, new communication technologies will enable the integration of news from a wide variety of sources and provide access to supplemental material from enormous archives of electronic news data (text, photos, and video) in digital libraries as well as the continual streams of newly created data. The goal of electronic news delivery within this context is, however, distiguishable from both news news groups and document retrieval. Electronic news promises to deliver to the reader an edited collage of recent events from wide domains in a manner that is both comprehensive and personalized. As part of a long-term research project into the design of future news delivery systems, we have developed an overall architecture and several prototypes. These prototypes are presented in the article, along with a discussion of issues related to the presentation metaphor and to the functionality of electronic news delivery services. A prototype was demonstrated at the 1995 G-7 Economic Summit in Halifax, Canada, integrating newspaper text and photographs with television news video clips across an ATM network

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Abstract

Relevance has been a difficult concept to define, let alone measure. In this paper, a simple operational definition of relevance is proposed for a Web-based library catalog: whether or not during a search session the user saves, prints, mails, or downloads a citation. If one of those actions is performed, the session is considered relevant to the user. An analysis is presented illustrating the advantages and disadvantages of this definition. With this definition and good transaction logging, it is possible to ascertain the relevance of a session. This was done for 905,970 sessions conducted with the University of California's Melvyl online catalog. Next, a methodology was developed to try to predict the relevance of a session. A number of variables were defined that characterize a session, none of which used any demographic information about the user. The values of the variables were computed for the sessions. Principal components analysis was used to extract a new set of variables out of the original set. A stratified random sampling technique was used to form ten strata such that each new strata of 90,570 sessions contained the same proportion of relevant to nonrelevant sessions. Logistic regression was used to ascertain the regression coefficients for nine of the ten strata. Then, the coefficients were used to predict the relevance of the sessions in the missing strata. Overall, 17.85% of the sessions were determined to be relevant. The predicted number of relevant sessions for all ten strata was 11 %, a 6.85% difference. The authors believe that the methodology can be further refined and the prediction improved. This methodology could also have significant application in improving user searching and also in predicting electronic commerce buying decisions without the use of personal demographic data