Call for Chapter - Ontology Learning and Knowledge Discovery Using the Web: Challenges and Recent Advances

resource thumbnail

Remove from Bookmarks

Do you really want to remove?
This action cannot be undone. Choose 'Cancel' to stop and go back.
Cancel
Ratings: 0
  • Which text to add here??

Added by Martin on 2009-11-19 14:13

» Viewed 798 times
» Favorited by 0 user(s)
» 0 Comments
» This resource has public visibility

Holder of Rights:

License: unknown

Creator(s):

Description:
Ontologies provide formal specifications of what might exist in a domain to ensure reusability and interoperability of multiple heterogeneous systems. Ontologies form an indispensable part of the Semantic Web standard stack. While the Semantic Web is still our vision into the future, ontologies have already found a myriad of applications such as document retrieval, question answering, image retrieval, agent interoperability and document annotation. In recent years, automatic ontology learning from text has provided support and relief for knowledge engineers from the labourious task of manually engineering of ontologies. Ontology learning research, an area integrating advances from information retrieval, text mining, data mining, machine learning and natural language processing, has attracted increasing interests from a wide spectrum of application domains (e.g. bioinformatics, manufacturing). Being a rapidly growing area, it is crucial to collect the recent advances in tools and technologies in ontology learning and related areas.

Add to Collection

You don't have any collections yet. Click here to create your first collection!

Okay

Share to Group

You don't have any group you can share this resource with: the resource is already shared to all groups you are member in. Click here to see available groups!

Okay

Create QR Code

Please select the URI for the QR Code:




Create Cancel

Tags

use blanks to separate tags

Comments

Call for Chapter - Ontology Learning and Knowledge Discovery Using the Web: Challenges and Recent Advances Ontologies provide formal specifications of what might exist in a domain to ensure reusability and interoperability of multiple heterogeneous systems. Ontologies form an indispensable part of the Semantic Web standard stack. While the Semantic Web is still our vision into the future, ontologies have already found a myriad of applications such as document retrieval, question answering, image retrieval, agent interoperability and document annotation. In recent years, automatic ontology learning from text has provided support and relief for knowledge engineers from the labourious task of manually engineering of ontologies. Ontology learning research, an area integrating advances from information retrieval, text mining, data mining, machine learning and natural language processing, has attracted increasing interests from a wide spectrum of application domains (e.g. bioinformatics, manufacturing). Being a rapidly growing area, it is crucial to collect the recent advances in tools and technologies in ontology learning and related areas.