• Journal of Korea Multimedia Society
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• v.11 no.7
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• pp.905-913
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• 2008

Many heterogeneous XML documents are being widely used with the increasing employment of XML, and the importance of data structure research for more efficient document management has been growing steadily. We propose a query processing technique which uses parent node information in a partitioned inverted index tree. The searching efficiency of these heterogeneous documents is greatly influenced by the number of query processing and the amount of target data sets in many ways. Therefore, considering these two factors is very important for designing a data structure. First, our technique stores parent node's information in an inverted index table. Then using this information, we can reduce the number of query processing by half. Also, the amount of target data sets can be lessoned by using partitioned inverted index table. Some XML documents collected from the Internet will be used to demonstrate the new method, and its high efficiency will be compared with some of the existing searching methods.

• Journal of KIISE:Databases
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• v.37 no.3
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• pp.146-164
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• 2010

Due to an increasing volume of XML data, it is considered prudent to store XML data on an industry-strength database system instead of relying on a domain specific application or a file system. For shredded XML data stored in relational tables, however, it may not be straightforward to apply existing algorithms for twig query processing, since most of the algorithms require XML data to be accessed in a form of streams of elements grouped by their tags and sorted in a particular order. In order to support XML query processing within the common framework of relational database systems, we first propose several bitmap indexes and their strategies for supporting holistic twig joining on XML data stored in relational tables. Since bitmap indexes are well supported in most of the commercial and open-source database systems, the proposed bitmapped indexes and twig query processing strategies can be incorporated into relational query processing framework with more ease. The proposed query processing strategies are efficient in terms of both time and space, because the compressed bitmap indexes stay compressed during data access. In addition, we propose a hybrid index which computes twig query solutions with only bit-vectors, without accessing labeled XML elements stored in the relational tables.