Ontology Learning and Population from Text: Algorithms, Evaluation and Applications / Edition 1

Ontology Learning and Population from Text: Algorithms, Evaluation and Applications / Edition 1

by Philipp Cimiano
     
 

Standard formalisms for knowledge representation such as RDFS or OWL have been recently developed by the semantic web community and are now in place. However, the crucial question still remains: how will we acquire all the knowledge available in people's heads to feed our machines?

Natural language is THE means of communication for humans, and consequently

See more details below

Overview

Standard formalisms for knowledge representation such as RDFS or OWL have been recently developed by the semantic web community and are now in place. However, the crucial question still remains: how will we acquire all the knowledge available in people's heads to feed our machines?

Natural language is THE means of communication for humans, and consequently texts are massively available on the Web. Terabytes and terabytes of texts containing opinions, ideas, facts and information of all sorts are waiting to be mined for interesting patterns and relationships, or used to annotate documents to facilitate their retrieval. A semantic web which ignores the massive amount of information encoded in text, might actually be a semantic, but not a very useful, web. Knowledge acquisition, and in particular ontology learning from text, actually has to be regarded as a crucial step within the vision of a semantic web.

Ontology Learning and Population from Text: Algorithms, Evaluation and Applications presents approaches for ontology learning from text and will be relevant for researchers working on text mining, natural language processing, information retrieval, semantic web and ontologies. Containing introductory material and a quantity of related work on the one hand, but also detailed descriptions of algorithms, evaluation procedures etc. on the other, this book is suitable for novices, and experts in the field, as well as lecturers.

Datasets, algorithms and course material can be downloaded at http://www.cimiano.de/olp. Ontology Learning and Population from Text: Algorithms, Evaluation and Applications is designed for practitioners in industry, as well researchers and graduate-level students in computer science.

Read More

Product Details

ISBN-13:
9781441940322
Publisher:
Springer US
Publication date:
10/29/2010
Edition description:
Softcover reprint of hardcover 1st ed. 2006
Pages:
347
Product dimensions:
0.78(w) x 9.21(h) x 6.14(d)

Table of Contents

Preliminaries.- Ontologies.- Ontology Learning from Text.- Basics.- Datasets.- Methods and Applications.- Concept Hierarchy Induction.- Learning Attributes and Relations.- Population.- Applications.- Conclusion.- Contribution and Outlook.- Concluding Remarks.

Customer Reviews

Average Review:

Write a Review

and post it to your social network

     

Most Helpful Customer Reviews

See all customer reviews >