Cart (Loading....) | Create Account
Close category search window
 

Deep textual semantics acquisition based on the activation of domain knowledge

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

5 Author(s)
Xiangfeng Luo ; High Performance Comput. Center, Shanghai Univ., Shanghai, China ; Lei Lu ; Weidong Liu ; Jun Zhang
more authors

The acquisition of deep textual semantics is a key issue on the process of text understanding which improves the performances of e-learning, web search and web services significantly. Though many methods have been developed to acquire textual semantics, the acquisition of deep textual semantics is still a challenge issue. Herein, the acquisition method of deep textual semantics is developed to enhance the capability of text understanding of machine, including two parts:1) how to obtain and organize the domain knowledge extracted from domain text set; 2) how to stimulate the domain knowledge for obtaining the deep textual semantics. The activation process involves two cognitive mechanisms; one is the Landscape model and the other is human memory system model. The former model is a human reading model. The later model describes the memory change in the text reading process. Generalized semantic field is proposed to store the domain knowledge as the form of Long Time Memory (LTM). Specialized semantic field, which is acquired by the interaction between the text fragment and the domain knowledge, is introduced to describe the change process of textual semantics. By their mutual actions, we can get the deep textual semantics which enhances the capability of text understanding of machine; therefore, the machine can understand the text more precisely and correctly than those methods which only obtain surface textual semantics.

Published in:

Cognitive Informatics & Cognitive Computing (ICCI*CC ), 2011 10th IEEE International Conference on

Date of Conference:

18-20 Aug. 2011

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.