From information to knowledge: harvesting entities and relationships from web sources
From information to knowledge: harvesting entities and relationships from web sources
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DOI：
10.1145/1807085.1807097
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发表时间：
2010-06
期刊：
影响因子：
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通讯作者：
G. Weikum;M. Theobald
中科院分区：
文献类型：
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作者：
G. Weikum;M. Theobald
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.
