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Filtering compressed XML streams

Posted on:2008-03-05Degree:M.ScType:Thesis
University:Acadia University (Canada)Candidate:Demmings, Brian JohnFull Text:PDF
GTID:2448390005954829Subject:Computer Science
Abstract/Summary:
Information Filtering is the problem of extracting data we desire from a corpus of data. The task of filtering depends heavily on the format of that corpus. For example, the corpus may be a stationary relational database, flat-file, collection of files, or, in the case of a news feed, may be continually streamed to clients.;In this research, we examine the problem of filtering data from a continual stream that has been compressed with an online, XML-conscious compressor. We introduce a filtering system that leverages the format of compressed XML streams to provide subscription-oriented filtering of the data contained in the stream. Additionally, the system provides persistence by efficiently storing the compressed results in relational tables, allowing subscribers to received filtered content even if they are disconnected when filtering occurs. These features make our system useful in applications where XML data is continually streamed such as news-feeds, scientific document notification services or in XML routing applications.
Keywords/Search Tags:XML, Filtering, Data, Compressed
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