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IEEE Intelligent Systems
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ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
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Domain-specific knowledge acquisition from text
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The automated acquisition of topic signatures for text summarization
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Automatic acquisition of hyponyms from large text corpora
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SOAT: a semi-automatic domain ontology acquisition tool from Chinese corpus
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OTM'07 Proceedings of the 2007 OTM confederated international conference on On the move to meaningful internet systems - Volume Part I
Companion Proceedings of the XIV Brazilian Symposium on Multimedia and the Web
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Data & Knowledge Engineering
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Expert Systems with Applications: An International Journal
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IEA/AIE'10 Proceedings of the 23rd international conference on Industrial engineering and other applications of applied intelligent systems - Volume Part III
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Semantic Web - On real-time and ubiquitous social semantics
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Ontology learning aims at reducing the time and efforts in the ontology development process. In recent years, several methods and tools have been proposed to speed up this process using different sources of information and different techniques. In this paper, we have reviewed 13 methods and 14 tools for semi-automatically building ontologies from texts and their relationships with the techniques each method follows. The methods have been grouped according to the main techniques followed and three groups have been identified: one based on linguistics, one on statistics, and one on machine learning. Regarding the tools, the criterion for grouping them, which has been the main aim of the tool, is to distinguish what elements of the ontology can be learned with each tool. According to this, we have identified three kinds of tools: tools for learning relations, tools for learning new concepts, and assisting tools for building up taxonomies.