Book ChapterDOI
Connectionist Analysis and Creation of Context for Natural Language Understanding and Knowledge Management
Reads0
Chats0
TLDR
This paper summarizes how an artificial neural network, the self-organizing map, can be used in modeling contextuality in data analysis and natural language processing.Abstract:
Context affects many aspects of the behavior. Natural language understanding is one of the prime examples. This paper summarizes how an artificial neural network, the self-organizing map, can be used in modeling contextuality in data analysis and natural language processing. Important aspects are adaptivity gained by using a learning system, autonomous nature of the processing based on unsupervised learning paradigm, and gradedness of the representation. Examples in the application areas of information retrieval and knowledge management are considered. For instance, the visualization of self-organizing maps provides meaningful context for documents.read more
Citations
More filters
Bibliography of Self-Organizing Map SOM) Papers: 1998-2001 Addendum
TL;DR: This work has provided a keyword index to help finding articles of interest, and additionally a modern automatically constructed variant of a thematic index: a WEBSOM interface to the whole article collection of years 1981-2000.
Self-organizing maps of document collections: A new approach to interactive exploration
TL;DR: This article presents a method, WEBSOM, for automatic organization of full-text document collections using the self-organizing map (SOM) algorithm, and presents a case study of its use.
Book ChapterDOI
FAQ-Centered Organizational Memory
TL;DR: A natural language dialogue system for sharing the valuable knowledge of an organization and applies natural language processing techniques to build a computer system that can help achieve the goal of OM.
Virtual Director: Visualization of Simple Scenarios
TL;DR: This paper presents Virtual Director, an application that combines Intelligent Text Processing and a Virtual Reality Module in order to visualize scenarios and create a Virtual Scene and produce a Virtual Animation.
References
More filters
Book
Self-Organizing Maps
TL;DR: The Self-Organising Map (SOM) algorithm was introduced by the author in 1981 as mentioned in this paper, and many applications form one of the major approaches to the contemporary artificial neural networks field, and new technologies have already been based on it.
Journal ArticleDOI
Self-organized formation of topologically correct feature maps
TL;DR: In this paper, the authors describe a self-organizing system in which the signal representations are automatically mapped onto a set of output responses in such a way that the responses acquire the same topological order as that of the primary events.
Journal ArticleDOI
Artificial neural networks: a tutorial
TL;DR: The article discusses the motivations behind the development of ANNs and describes the basic biological neuron and the artificial computational model, and outlines network architectures and learning processes, and presents some of the most commonly used ANN models.
Journal ArticleDOI
Self-organizing semantic maps
Helge Ritter,Teuvo Kohonen +1 more
TL;DR: Self-organized formation of topographic maps for abstract data, such as words, is demonstrated and it is argued that a similar process may be at work in the brain.