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    Towards Aggregated Answers for Semistructured Data

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    Semistructured data are usually formalized as trees or more generally as graphs. Query languages for semistructured data have been proposed that, like SQL, can be seen as involving a number of variables, but, in contrast to SQL, arrange the variables in trees or graphs reflecting the structure of the semistructured data to be retrieved. Leaving aside the ``construct'' parts of queries, answers can be formalized as mappings represented as tuples, hence called answer tuples, that assign database nodes to query variables. These answer tuples underly the semistructured data delivered as answers. A simple enumeration of answer tuples following the old relational approach is problematic for several reasons. First, the number of answer tuples for a query may grow exponentially in the size of both, the query and the database. Second, even if the number of answer tuples is manageable, the frequent sharing of common data between distinct answer tuples is no more apparent in their enumeration. In this article, it is first argued that, in the context of semistructured data, enumerating answer tuples is often inappropriate and that aggregated answers are preferable. Then, a notion of aggregated answers called complete answer aggregate (CAA) is introduced and algorithms for computing CAAs are given. It is shown that CAAs enjoy nice complexity properties: (1) While the number of answer tuples may be exponential in the size of the query, the size of the CAA is at most linear in the size of the query and quadratic in the size of the database; (2) the complexity of computing the CAA of a query depends on the query's structural complexity (i.e. whether it is a sequence, tree, graph, etc.) but is independent of the structural complexity of the database. For tree queries, efficient polynomial algorithms are given. Besides, it is argued that CAAs are particularly appropriate for answer searching and answer browsing.

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    Description

    Title : Towards Aggregated Answers for Semistructured Data
    Author(s) : Holger Meuss, Klaus U Schulz, François Bry
    Abstract : Semistructured data are usually formalized as trees or more generally as graphs. Query languages for semistructured data have been proposed that, like SQL, can be seen as involving a number of variables, but, in contrast to SQL, arrange the variables in trees or graphs reflecting the structure of the semistructured data to be retrieved. Leaving aside the ``construct'' parts of queries, answers can be formalized as mappings represented as tuples, hence called answer tuples, that assign database nodes to query variables. These answer tuples underly the semistructured data delivered as answers. A simple enumeration of answer tuples following the old relational approach is problematic for several reasons. First, the number of answer tuples for a query may grow exponentially in the size of both, the query and the database. Second, even if the number of answer tuples is manageable, the frequent sharing of common data between distinct answer tuples is no more apparent in their enumeration. In this article, it is first argued that, in the context of semistructured data, enumerating answer tuples is often inappropriate and that aggregated answers are preferable. Then, a notion of aggregated answers called complete answer aggregate (CAA) is introduced and algorithms for computing CAAs are given. It is shown that CAAs enjoy nice complexity properties: (1) While the number of answer tuples may be exponential in the size of the query, the size of the CAA is at most linear in the size of the query and quadratic in the size of the database; (2) the complexity of computing the CAA of a query depends on the query's structural complexity (i.e. whether it is a sequence, tree, graph, etc.) but is independent of the structural complexity of the database. For tree queries, efficient polynomial algorithms are given. Besides, it is argued that CAAs are particularly appropriate for answer searching and answer browsing.
    Keywords : xml query languages caa navigation theory path vis

    Subject : unspecified
    Area : Other
    Language : English
    Year : 2001

    Affiliations Institute for Informatics, Ludwig Maximilian University of Munich
    Conference_title : Proc Intl Conf on Database Theory
    Publisher : Springer-Verlag
    Pages : 346-360
    Url : http://www.pms.ifi.lmu.de/publikationen/#PMS-FB-2000-15

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