Information retrieval: data structures and algorithms
Information retrieval: data structures and algorithms
Deriving concept hierarchies from text
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Snowball: extracting relations from large plain-text collections
DL '00 Proceedings of the fifth ACM conference on Digital libraries
Finding topic words for hierarchical summarization
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
The C-value/NC-value Method of Automatic Recognition for Multi-Word Terms
ECDL '98 Proceedings of the Second European Conference on Research and Advanced Technology for Digital Libraries
Generating hierarchical summaries for web searches
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Unsupervised learning of soft patterns for generating definitions from online news
Proceedings of the 13th international conference on World Wide Web
Automatic acquisition of hyponyms from large text corpora
COLING '92 Proceedings of the 14th conference on Computational linguistics - Volume 2
Refining term weights of documents using term dependencies
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
A comparison of ontology reasoning systems using query sequences
Proceedings of the 2nd international conference on Ubiquitous information management and communication
Ontology reasoning in agent-oriented programming
SBIA'10 Proceedings of the 20th Brazilian conference on Advances in artificial intelligence
Agent-Oriented programming with underlying ontological reasoning
DALT'05 Proceedings of the Third international conference on Declarative Agent Languages and Technologies
Agent societies and social networks for ubiquitous computing
Personal and Ubiquitous Computing
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One of the key elements of the Semantic Web technologies is domain ontologies and those ontologies are important constructs for multi-agent system. The Semantic Web relies on domain ontologies that structure underlying data enabling comprehensive and transportable machine understanding. It takes so much time and efforts to construct domain ontologies because these ontologies can be manually made by domain experts and knowledge engineers. To solve these problems, there have been many researches to semi-automatically construct ontologies. Most of the researches focused on relation extraction part but manually selected terms for ontologies. These researches have some problems. In this paper, we propose a hybrid method to extract relations from domain documents which combines a named relation approach and an unnamed relation approach. Our named relation approach is based on the Hearst's pattern and the Snowball system. We merge a generalized pattern scheme into their methods. In our unnamed relation approach, we extract unnamed relations using association rules and clustering method. Moreover, we recommend candidate relation names of unnamed relations. We evaluate our proposed method by using Ziff document set offered by TREC.