Self-Organizing Maps In Natural Language Processing
@inproceedings{Honkela1997SelfOrganizingMI, title={Self-Organizing Maps In Natural Language Processing}, author={Timo Honkela}, year={1997} }
Kohonen's Self-Organizing Map (SOM) is one of the most popular arti cial neural network algorithms. Word category maps are SOMs that have been organized according to word similarities, measured by the similarity of the short contexts of the words. Conceptually interrelated words tend to fall into the same or neighboring map nodes. Nodes may thus be viewed as word categories. Although no a priori information about classes is given, during the self-organizing process a model of the word classes…
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References
SHOWING 1-10 OF 190 REFERENCES
Self-Organizing Maps of Document Collections: A New Approach to Interactive Exploration
- Computer ScienceKDD
- 1996
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.
A Practical Approach for Representing Context and for Performing Word Sense Disambiguation Using Neural Networks
- Computer ScienceNeural Computation
- 1991
A method for representing some context information so that the correct meaning for a word in a sentence can be selected and the development of more powerful context algorithms will be an important topic for future research.
Exploration of very large databases by self-organizing maps
- Computer ScienceProceedings of International Conference on Neural Networks (ICNN'97)
- 1997
A data organization system and genuine content-addressable memory called the WEBSOM, a two-layer self-organizing map (SOM) architecture where documents become mapped as points on the upper map, in a geometric order that describes the similarity of their contents.
Natural Language Processingwith Modular Neural Networks and Distributed Lexicon
- Computer Science
- 1991
An approach to connectionist natural language processing is proposed, which is based on hierarchically organized modular Parallel Distributed Processing (PDP) networks and a central lexicon of…
Engineering applications of the self-organizing map
- Computer ScienceProc. IEEE
- 1996
The self-organizing map method, which converts complex, nonlinear statistical relationships between high-dimensional data into simple geometric relationships on a low-dimensional display, can be utilized for many tasks: reduction of the amount of training data, speeding up learning nonlinear interpolation and extrapolation, generalization, and effective compression of information for its transmission.
A self-organizing semantic map for information retrieval
- Computer ScienceSIGIR '91
- 1991
A neural network’s unsupervised learning algorithm is applied to constructing a selforganizing semantic map for information retrieval, which visualizes semantic relationships between input documents, and has properties of economic representation of data with their interrelationships.
Newsgroup Exploration with WEBSOM Method and Browsing Interface
- Computer Science
- 1996
The WEBSOM method is introduced, which visualizes similarity relations between the documents on a map display, which can be utilized in exploring the material rather than having to rely on traditional search expressions.
Resolving Linguistic Ambiguities with a Neural Data-Oriented Parsing (DOP) System
- Computer Science
- 1992
Comparing Self-Organizing Maps
- Computer ScienceICANN
- 1996
Two measures for comparing how different maps represent relations between data items are developed, one of which combines an index of discontinuities in the mapping from the input data set to the map grid with a measure of the accuracy with which the map represents the data set.
Lessons Learned in Text Document Classification
- Computer Science
- 1997
This paper takes advantage of the fact that text archives lend themselves naturally to a hierarchical structure by using a hierarchically organized network built up from independent self-organizing maps in order to enable the true establishment of a document taxonomy.