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Sinopsis
In recent years, several knowledge bases have been built to enable large-scale knowledge sharing, but also an entity-centric Web search, mixing both structured data and text querying. These knowledge bases offer machine-readable descriptions of real-world entities, e.g., persons, places, published on the Web as Linked Data. However, due to the different information extraction tools and curation policies employed by knowledge bases, multiple, complementary and sometimes conflicting descriptions of the same real-world entities may be provided. Entity resolution aims to identify different descriptions that refer to the same entity appearing either within or across knowledge bases. The objective of this book is to present the new entity resolution challenges stemming from the openness of the Web of data in describing entities by an unbounded number of knowledge bases, the semantic and structural diversity of the descriptions provided across domains even for the same real-world entities, as well as the autonomy of knowledge bases in terms of adopted processes for creating and curating entity descriptions. The scale, diversity, and graph structuring of entity descriptions in the Web of data essentially challenge how two descriptions can be effectively compared for similarity, but also how resolution algorithms can efficiently avoid examining pairwise all descriptions. The book covers a wide spectrum of entity resolution issues at the Web scale, including basic concepts and data structures, main resolution tasks and workflows, as well as state-of-the-art algorithmic techniques and experimental trade-offs.
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Vassilis Christophides is a professor of Computer Science at the University of Crete. He has been recently appointed to an advanced research position at INRIA Paris-Rocquencourt. Previously, he worked as a Distinguished Scientist at Technicolor, R&I Center in Paris. He studied Electrical Engineering at the National Technical University of Athens (NTUA), Greece, July 1988, he received his DEA in computer science from the University PARIS VI, June 1992, and his Ph.D. from the Conservatoire National des Arts et Metiers (CNAM) of Paris, October 1996. His main research interests include Databases and Web Information Systems, as well as Big Data Processing and Analysis. He has published over 130 articles in high-quality international conferences, journals, and workshops. He has been scientific coordinator of a number of research projects funded by the European Union, the Greek State, and private foundations on the Semantic Web and Digital Preservation at the Institute of Computer Science of FORTH. He has received the 2004 SIGMOD Test of Time Award and the Best Paper Award at the 2nd and 6th International Semantic Web Conference in 2003 and 2007. He served as General Chair of the joint EDBT/ICDT Conference in 2014 at Athens and as Area Chair for the ICDE "Semi-structured, Web, and Linked Data Management" track in 2016 at Bali, Indonesia. Vasilis Efthymiou is a Ph.D. candidate at the University of Crete and a member of the Information Systems Laboratory of the Institute of Computer Science at FORTH. The topic of his Ph.D. research is entity resolution in the Web of data. He got his MSc and BSc degrees from the same university in 2012 and 2010, respectively. He has received undergraduate and postgraduate scholarships from FORTH, working in the areas of Semantic Web, non-monotonic reasoning, and Ambient Intelligence.
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Entity Resolution in the Web of Data
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Entity Resolution in the Web of Data (Paperback)
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Paperback. Condición: new. Paperback. In recent years, several knowledge bases have been built to enable large-scale knowledge sharing, but also an entity-centric Web search, mixing both structured data and text querying. These knowledge bases offer machine-readable descriptions of real-world entities, e.g., persons, places, published on the Web as Linked Data. However, due to the different information extraction tools and curation policies employed by knowledge bases, multiple, complementary and sometimes conflicting descriptions of the same real-world entities may be provided. Entity resolution aims to identify different descriptions that refer to the same entity appearing either within or across knowledge bases.The objective of this book is to present the new entity resolution challenges stemming from the openness of the Web of data in describing entities by an unbounded number of knowledge bases, the semantic and structural diversity of the descriptions provided across domains even for the same real-world entities, as well as the autonomy of knowledge bases in terms of adopted processes for creating and curating entity descriptions. The scale, diversity, and graph structuring of entity descriptions in the Web of data essentially challenge how two descriptions can be effectively compared for similarity, but also how resolution algorithms can efficiently avoid examining pairwise all descriptions.The book covers a wide spectrum of entity resolution issues at the Web scale, including basic concepts and data structures, main resolution tasks and workflows, as well as state-of-the-art algorithmic techniques and experimental trade-offs. In recent years, several knowledge bases have been built to enable large-scale knowledge sharing, but also an entity-centric Web search, mixing both structured data and text querying. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Nº de ref. del artículo: 9783031794674
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Entity Resolution in the Web of Data (Synthesis Lectures on Data, Semantics, and Knowledge)
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Entity Resolution in the Web of Data
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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -In recent years, several knowledge bases have been built to enable large-scale knowledge sharing, but also an entity-centric Web search, mixing both structured data and text querying. These knowledge bases offer machine-readable descriptions of real-world entities, e.g., persons, places, published on the Web as Linked Data. However, due to the different information extraction tools and curation policies employed by knowledge bases, multiple, complementary and sometimes conflicting descriptions of the same real-world entities may be provided. Entity resolution aims to identify different descriptions that refer to the same entity appearing either within or across knowledge bases.The objective of this book is to present the new entity resolution challenges stemming from the openness of the Web of data in describing entities by an unbounded number of knowledge bases, the semantic and structural diversity of the descriptions provided across domains even for the same real-world entities, as well as the autonomy of knowledge bases in terms of adopted processes for creating and curating entity descriptions. The scale, diversity, and graph structuring of entity descriptions in the Web of data essentially challenge how two descriptions can be effectively compared for similarity, but also how resolution algorithms can efficiently avoid examining pairwise all descriptions.The book covers a wide spectrum of entity resolution issues at the Web scale, including basic concepts and data structures, main resolution tasks and workflows, as well as state-of-the-art algorithmic techniques and experimental trade-offs. 124 pp. Englisch. Nº de ref. del artículo: 9783031794674
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Paperback. Condición: new. Paperback. In recent years, several knowledge bases have been built to enable large-scale knowledge sharing, but also an entity-centric Web search, mixing both structured data and text querying. These knowledge bases offer machine-readable descriptions of real-world entities, e.g., persons, places, published on the Web as Linked Data. However, due to the different information extraction tools and curation policies employed by knowledge bases, multiple, complementary and sometimes conflicting descriptions of the same real-world entities may be provided. Entity resolution aims to identify different descriptions that refer to the same entity appearing either within or across knowledge bases.The objective of this book is to present the new entity resolution challenges stemming from the openness of the Web of data in describing entities by an unbounded number of knowledge bases, the semantic and structural diversity of the descriptions provided across domains even for the same real-world entities, as well as the autonomy of knowledge bases in terms of adopted processes for creating and curating entity descriptions. The scale, diversity, and graph structuring of entity descriptions in the Web of data essentially challenge how two descriptions can be effectively compared for similarity, but also how resolution algorithms can efficiently avoid examining pairwise all descriptions.The book covers a wide spectrum of entity resolution issues at the Web scale, including basic concepts and data structures, main resolution tasks and workflows, as well as state-of-the-art algorithmic techniques and experimental trade-offs. In recent years, several knowledge bases have been built to enable large-scale knowledge sharing, but also an entity-centric Web search, mixing both structured data and text querying. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. Nº de ref. del artículo: 9783031794674
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Taschenbuch. Condición: Neu. Neuware -In recent years, several knowledge bases have been built to enable large-scale knowledge sharing, but also an entity-centric Web search, mixing both structured data and text querying. These knowledge bases offer machine-readable descriptions of real-world entities, e.g., persons, places, published on the Web as Linked Data. However, due to the different information extraction tools and curation policies employed by knowledge bases, multiple, complementary and sometimes conflicting descriptions of the same real-world entities may be provided. Entity resolution aims to identify different descriptions that refer to the same entity appearing either within or across knowledge bases.The objective of this book is to present the new entity resolution challenges stemming from the openness of the Web of data in describing entities by an unbounded number of knowledge bases, the semantic and structural diversity of the descriptions provided across domains even for the same real-world entities, as well as the autonomy of knowledge bases in terms of adopted processes for creating and curating entity descriptions. The scale, diversity, and graph structuring of entity descriptions in the Web of data essentially challenge how two descriptions can be effectively compared for similarity, but also how resolution algorithms can efficiently avoid examining pairwise all descriptions.The book covers a wide spectrum of entity resolution issues at the Web scale, including basic concepts and data structures, main resolution tasks and workflows, as well as state-of-the-art algorithmic techniques and experimental trade-offs.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 124 pp. Englisch. Nº de ref. del artículo: 9783031794674
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