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Mapping enterprise entities to text segments
Citation key	DBLP:conf/cikm/BrauerLD08
Author	Falk Brauer, Alexander Löser, Hong-Hai Do
Pages	85-88
Year	2008
Journal	Proceedings of the 2nd PhD workshop on Information and knowledge management
Organization	CIKM
Institution	Conference on Information and Knowledge Management
Abstract	Today, valuable business information is increasingly stored as unstructured data (documents, emails, etc.). For example, documents exchanged between business partners capture information on transactions between them like purchases or invoices. A major challenge is to correctly recognize and associate real-world entities in unstructured data, e.g. documents, with those stored in structured data e.g., enterprise databases. To address this, we propose in this paper a robust process methodology consisting of three phases: entity extraction from documents, generation of mapping of recognized entities with structured data, and disambiguation of mappings exploiting relationships from the enterprise data and the documents' structure.