Title :
HCHIRSIMEX: An extended method for domain ontology learning based on conditional mutual information
Author :
El Idrissi, Omar ; Frikh, Bouchra ; Ouhbi, Brahim
Author_Institution :
LM2I Lab., Moulay Ismail Univ., Meknès, Morocco
Abstract :
This paper presents HCHIRSIMEX, an extended version of our previous algorithm HCHIRSIM for building domain ontology from web corpus. The new version introduces a novel measure based on the Conditional Mutual Information (CMI) statistic method to define the taxonomic relations and the similarity between selected concepts. By using this method, the ontology extracted by HCHIRSIMEX is more concise and contains a richer concept knowledge base compared with the previous version HCHIRSIM. To evaluate our new algorithm effectiveness, we apply the two algorithms and Sanchez et al. algorithm in Finance domain ontology constructed from the web. Then, we compare the obtained concepts with those on the “Financial glossary” provided by Yahoo.com.
Keywords :
financial data processing; learning (artificial intelligence); ontologies (artificial intelligence); CMI statistic method; HCHIRSIMEX method; Web corpus; conditional mutual information; domain ontology learning; finance domain ontology; financial glossary; knowledge base; taxonomic relations; Algorithm design and analysis; Data mining; Finance; Mutual information; Ontologies; Semantics; Terminology; CHIR-statistic; Conditional Mutual Information; Domain Ontology; Finance Ontology; Machine Learning; Ontology learning;
Conference_Titel :
Information Science and Technology (CIST), 2014 Third IEEE International Colloquium in
Conference_Location :
Tetouan
Print_ISBN :
978-1-4799-5978-5
DOI :
10.1109/CIST.2014.7016600
