We study models of incomplete information for XML, their computational properties, and query answering. While our approach is motivated by the study of relational incompleteness, incomplete information in XML documents may appear not only as null values but also as missing structural information. Our goal is to provide a classification of incomplete descriptions of XML documents, and separate features-or groups of features-that lead to hard computational problems from those that admit efficient algorithms. Our classification of incomplete information is based on the combination of null values with partial structural descriptions of documents. The key computational problems we consider are consistency of partial descriptions, representability of complete documents by incomplete ones, and query answering. We show how factors such as schema information, the presence of node ids, and missing structural information affect the complexity of these main computational problems, and find robust classes of incomplete XML descriptions that permit tractable query evaluation.
XML with Incomplete Information / Pablo, Barcelo; Leonid, Libkin; Poggi, Antonella; Cristina, Sirangelo. - In: JOURNAL OF THE ASSOCIATION FOR COMPUTING MACHINERY. - ISSN 0004-5411. - 58:1(2010), pp. 1-62. (Intervento presentato al convegno 27th ACM SIGMOD-SIGACT-SIGART Symposium on Principles of Database Systems (PODS) tenutosi a Vancouver, CANADA nel JUL 09-11, 2008) [10.1145/1870103.1870107].
XML with Incomplete Information
POGGI, Antonella;
2010
Abstract
We study models of incomplete information for XML, their computational properties, and query answering. While our approach is motivated by the study of relational incompleteness, incomplete information in XML documents may appear not only as null values but also as missing structural information. Our goal is to provide a classification of incomplete descriptions of XML documents, and separate features-or groups of features-that lead to hard computational problems from those that admit efficient algorithms. Our classification of incomplete information is based on the combination of null values with partial structural descriptions of documents. The key computational problems we consider are consistency of partial descriptions, representability of complete documents by incomplete ones, and query answering. We show how factors such as schema information, the presence of node ids, and missing structural information affect the complexity of these main computational problems, and find robust classes of incomplete XML descriptions that permit tractable query evaluation.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.