MENTA: Inducing multilingual taxonomies from Wikipedia
|MENTA: Inducing multilingual taxonomies from Wikipedia|
|Author(s)||De Melo G., Weikum G.|
|Published in||International Conference on Information and Knowledge Management, Proceedings|
|Keyword(s)||Algorithms (Extra: Graph Partitioning, Knowledge basis, Lexical knowledge, Markov Chain, Orders of magnitude, Ranking approach, Taxonomic class, Wikipedia, Wordnet, Algorithms, Equivalence classes, Knowledge based systems, Knowledge management, Markov processes, Taxonomies)|
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MENTA: Inducing multilingual taxonomies from Wikipedia is a 2010 conference paper written in English by De Melo G., Weikum G. and published in International Conference on Information and Knowledge Management, Proceedings.
In recent years, a number of projects have turned to Wikipedia to establish large-scale taxonomies that describe orders of magnitude more entities than traditional manually built knowledge bases. So far, however, the multilingual nature of Wikipedia has largely been neglected. This paper investigates how entities from all editions of Wikipedia as well as WordNet can be integrated into a single coherent taxonomic class hierarchy. We rely on linking heuristics to discover potential taxonomic relationships, graph partitioning to form consistent equivalence classes of entities, and a Markov chain-based ranking approach to construct the final taxonomy. This results in MENTA (Multilingual Entity Taxonomy), a resource that describes 5.4 million entities and is presumably the largest multilingual lexical knowledge base currently available.
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