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Automatic multi-document summarization for digital librariesWith the rapid growth of the World Wide Web and online information services, more and more information is available and accessible online. Automatic summarization is an indispensable solution to reduce the information overload problem. Multi-document summarization is useful to provide an overview of a topic and allow users to zoom in for more details on aspects of interest. This paper reports three types of multi-document summaries generated for a set of research abstracts, using different summarization approaches: a sentence-based summary generated by a MEAD summarization system that extracts important sentences using various features, another sentence-based summary generated by extracting research objective sentences, and a variable-based summary focusing on research concepts and relationships. A user evaluation was carried out to compare the three types of summaries. The evaluation results indicated that the majority of users (70%) preferred the variable-based summary, while 55% of the users preferred the research objective summary, and only 25% preferred the MEAD summary.
Indexing and Abstracting on the World Wide Web: An Examination of Six Web DatabasesWeb databases, commonly known as search engines or web directories, are currently the most useful way to search the Internet. In this article, the author draws from library literature to develop a series of questions that can be used to analyze these web searching tools. Six popular web databases are analyzed using this method. Using this analysis, the author creates three categories for web databases and explores the most appropriate searches to perform with each. The work concludes with a proposal for the ideal web database.