From information to knowledge: Harvesting entities and relationships from web sources
|From information to knowledge: Harvesting entities and relationships from web sources|
|Author(s)||Weikum G., Theobald M.|
|Published in||Proceedings of the ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems|
|Keyword(s)||entities, information extraction, knowledge harvesting, relationships (Extra: entities, Expressive semantics, High precision, Information Extraction, Knowledge base, Knowledge-sharing, Mutual relations, Named entities, Research opportunities, Semantic class, Semi-structured, State-of-the-art methods, Web sources, Wikipedia, Database systems, Information analysis, Information retrieval systems, Knowledge based systems, Search engines, Semantics, Harvesting)|
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From information to knowledge: Harvesting entities and relationships from web sources is a 2010 conference paper written in English by Weikum G., Theobald M. and published in Proceedings of the ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems.
There are major trends to advance the functionality of search engines to a more expressive semantic level. This is enabled by the advent of knowledge-sharing communities such as Wikipedia and the progress in automatically extracting entities and relationships from semistructured as well as natural-language Web sources. Recent endeavors of this kind include DBpedia, EntityCube, KnowItAll, ReadTheWeb, and our own YAGO-NAGA project (and others). The goal is to automatically construct and maintain a comprehensive knowledge base of facts about named entities, their semantic classes, and their mutual relations as well as temporal contexts, with high precision and high recall. This tutorial discusses state-of-the-art methods, research opportunities, and open challenges along this avenue of knowledge harvesting.
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