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Automatic construction of lexicons, taxonomies, ontologies, and other knowledge structures
Author(s) -
Medelyan Olena,
Witten Ian H.,
Divoli Anna,
Broekstra Jeen
Publication year - 2013
Publication title -
wiley interdisciplinary reviews: data mining and knowledge discovery
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.506
H-Index - 47
eISSN - 1942-4795
pISSN - 1942-4787
DOI - 10.1002/widm.1097
Subject(s) - computer science , data science , knowledge representation and reasoning , knowledge extraction , world wide web , representation (politics) , ontology , cluster analysis , open knowledge base connectivity , semantic web , knowledge management , information retrieval , personal knowledge management , artificial intelligence , organizational learning , philosophy , epistemology , politics , political science , law
, structured, representations of knowledge such as lexicons, taxonomies, and ontologies have proven to be powerful resources not only for the systematization of knowledge in general, but to support practical technologies of document organization, information retrieval, natural language understanding, and question‐answering systems. These resources are extremely time consuming for people to create and maintain, yet demand for them is growing, particularly in specialized areas ranging from legacy documents of large enterprises to rapidly changing domains such as current affairs and celebrity news. Consequently, researchers are investigating methods of creating such structures automatically from document collections, calling on the proliferation of interlinked resources already available on the web for background knowledge and general information about the world. This review surveys what is possible, and also outlines current research directions. This article is categorized under: Algorithmic Development > Text Mining Fundamental Concepts of Data and Knowledge > Knowledge Representation Technologies > Structure Discovery and Clustering