3 research outputs found

    Coreference detection in XML metadata

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    Preserving data quality is an important issue in data collection management. One of the crucial issues hereby is the detection of duplicate objects (called coreferent objects) which describe the same entity, but in different ways. In this paper we present a method for detecting coreferent objects in metadata, in particular in XML schemas. Our approach consists in comparing the paths from a root element to a given element in the schema. Each path precisely defines the context and location of a specific element in the schema. Path matching is based on the comparison of the different steps of which paths are composed. The uncertainty about the matching of steps is expressed with possibilistic truth values and aggregated using the Sugeno integral. The discovered coreference of paths can help for determining the coreference of different XML schemas

    Semantical mapping of attribute values for data integration

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    Nowadays the amount of data is increasing very fast. Moreover, useful information is scattered over multiple sources. Therefore, automatic data integration that guarantees high data quality is extremely important. One of the crucial operations in integration of information from independent databases is detection of different representations of the same piece of information (called coreferent data) and translation of the representation of data from one source into the representation of the other source. That translation is also known as object mapping. In this paper, we investigate automatic mapping methods for attributes the values of which may need semantical comparison and can be sorted by means of an order relation that reflects a notion of generality. These mapping methods are investigated closely in terms of their effectiveness. An experimental evaluation of our method shows that using different mapping methods can enlarge a set of true positive mappings

    Handling metadata in the scope of coreference detection in data collections

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