Where as traditional databases manage only deterministic information, many applications that use databases involve uncertain data. This paper presents a Probabilistic Tree Data Base (ProTDB) to manage probabilistic data, represented in XML.#R##N##R##N#Our approach differs from previous efforts to develop probabilistic relational systems in that we build a probabilistic XML database. This design is driven by application needs that involve data not readily amenable to a relational representation. XML data poses several modeling challenges: due to its structure, due to the possibility of uncertainty association at multiple granularities, and due to the possibility of missing and repeated sub-elements. We present a probabilistic XML model that addresses all of these challenges. We devise an implementation of XML query operations using our probability model, and demonstrate the efficiency of our implementation experimentally.#R##N##R##N#We have used ProTDB to manage data from two application areas: protein chemistry data from the bioinformatics domain, and information extraction data obtained from the web using a natural language analysis system. We present a brief case study of the latter to demonstrate the value of probabilistic XML data management.
['Andrew Nierman', 'H. V. Jagadish']
ProTDB: probabilistic data in XML