This paper presents an approach to mining domain-dependent ontologies using term extraction and relationship discovery technology.There are two main innovations in the approach. One is extracting terms using log-likelihood ratio, which is based on the contrastive probabilityofterm occurrence in domain corpus and background corpus. The other is fusing together information from multiple knowledge sources as evidencesfor discovering particular semantic relationships among terms. In the experiment, traditional k-mediods algorithm is improved for multi-levelclustering. The approach to produce an ontology for the domain of computer science is applied and promising results are obtained.

072282.pdf

• We are an exchange download platform that only provides communication channels. The downloaded content comes from the internet. Except for download issues, please Google on your own.
• The downloaded content is provided for members to upload. If it unintentionally infringes on your copyright, please contact us.
• Please use Winrar for decompression tools
• If download fail, Try it againg or Feedback to us.
• If downloaded content did not match the introduction, Feedback to us，Confirm and will be refund.
• Before downloading, you can inquire through the uploaded person information

Nothing．