Metadata for Name Disambiguation and Collocation

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Metadata for Name Disambiguation and Collocation

Searching names of persons, families, and organizations is often difficult in online databases because different persons or organizations frequently share the same name and because a single person’s or organization’s name may appear in different forms in various online documents. Databases and search engines can use metadata as a tool to solve the problem of name ambiguity and name variation in...

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Log analysis shows that PubMed users frequently use author names in queries for retrieving scientific literature. However, author name ambiguity may lead to irrelevant retrieval results. To improve the PubMed user experience with author name queries, we designed an author name disambiguation system consisting of similarity estimation and agglomerative clustering. A machine-learning method was e...

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Unsupervised Personal Name Disambiguation

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Efficient Name Disambiguation for Large-Scale Databases

Name disambiguation can occur when one is seeking a list of publications of an author who has used different name variations and when there are multiple other authors with the same name. We present an efficient integrative framework for solving the name disambiguation problem: a blocking method retrieves candidate classes of authors with similar names and a clustering method, DBSCAN, clusters p...

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Name disambiguation is an important challenge in data cleaning. In this paper, we focus on the problem that multiple real-world objects (e.g., authors, actors) in a dataset share the same name. We show that Web corpora can be exploited to significantly improve the accuracy (i.e. precision and recall) of name disambiguation. We introduce a novel approach called WebNaD (Web-based Name Disambiguat...

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ژورنال

عنوان ژورنال: Future Internet

سال: 2010

ISSN: 1999-5903

DOI: 10.3390/fi2010001