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2 edition of Development of a hybrid symbolic/connectionist system for word sense disambiguation. found in the catalog.

Development of a hybrid symbolic/connectionist system for word sense disambiguation.

Xinyu Wu

Development of a hybrid symbolic/connectionist system for word sense disambiguation.

by Xinyu Wu

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  • 29 Currently reading

Published by The Author] in [s.l .
Written in English


Edition Notes

Thesis (D. Phil.) - University of Ulster, 1995.

ID Numbers
Open LibraryOL19097240M

esinConnectionistandNeuralComputationTheoryVolume1:High. 1 The Hidden Pattern Ben Goertzel. 2 Preface In this book I present some interim results from a quest I ve been on for many years a quest for a coherent conceptual framework making it possible to understand the various aspects of mind and intelligence in a unified way. The underlying goals of this quest have been twofold: a general desire to understand myself and the universe, and a .

Free essays, homework help, flashcards, research papers, book reports, term papers, history, science, politics. Book on Academia and Publishing Date: Wed, 12 May + X-Humanist: Vol. 18 Num. 13 (13) I don't remember hearing anything about this book, so apologies if my reference (from the Harvard Bookstore) is repetitive.


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Development of a hybrid symbolic/connectionist system for word sense disambiguation by Xinyu Wu Download PDF EPUB FB2

This paper describes a hybrid system—SYMCON (SYMbolic and CONnectionist) which integrates symbolic and connectionist techniques in an attempt to solve the problem of word sense disambiguation Author: Andrzej Siemiński.

A symbolic-connectionist hybrid system called HYBthetasPRED (hybrid symbolic-connectionist thematic (thetas) predictor) is proposed here. Its main. Wu X, Mctear M and Ojha P () SYMCON—A Hybrid Symbolic/Connectionist Systemfor Word Sense Disambiguation, Applied Intelligence,(), Online publication date: 1-Jan Ng H and Lee H Integrating multiple knowledge sources to disambiguate word sense Proceedings of the 34th annual meeting on Association for Computational.

R.S. Michalski and R.L. Chilausky, "Learning by being told and learning from examples: An experimental comparison of the two methods of knowledge acquisition in the context of developing an expert system for soybean disease diagnosis," International Journal of Policy Analysis and Information Systems, vol.

4, pp. Cited by: Analogical Retrieval Within a Hybrid Spreading-Activation Network Figure 3. Simplified ROBIN network segment at two different cycles during processing of The shark ate the diver. Each figure shows the parallel paths over which evidential activation (bottom plane) and signature activa tion (top plane) are spread for by: 3.

Symbolic, Connectionist, and Statistical Approaches to Learning for Natural Language Processing, S. Wermter, E. Riloff and G. Scheler, Eds, Spring Verlag, This paper presents results from recent experiments with CHILL, a corpus-based parser acquisition system. Comparing expert and novice understanding of a complex system from the perspective of structures, behaviors, and functions, Cindy E.

Hmelo-Silver & Merav Green Pfeffer – @INPROCEEDINGS{AltunEMNLP, AUTHOR Word Sense Disambiguation with World Knowledge}, AUTHOR = {Massimiliano Ciaramita and Thomas Gabriele}, TITLE = {A statistical syntactic disambiguation program and what it learns}, BOOKTITLE = {Symbolic, Connectionist, and Statistical Approaches to Learning for Natural.

(1) The word parser receives word sequences as input (i.e. one word at a time, taken from the GSL) and is trained (via backpropagation) to produce a case-role representation (i.e. patterns of activation for the case-roles of Actor, Object, Act, Location, etc.) in its output layer. For example, given the input sequence "John went to Leone's.

Word sense induction attempts to find the senses of polysemous words. Synonymy detection attempts to find when two words are interchangeable.

We combine these tasks, first inducing word senses and then detecting similar senses to form word-sense synonym sets (synsets) in an unsupervised fashion. Given pairs of images and text with noun phrase. NASA Images Solar System Collection Ames Research Center.

Brooklyn Museum. Full text of "mind and language" See other formats. The System Engineering Laboratory is primarily concerned with interactions between people and systems at all stages of development and operation, including subsequent maintenance and system evolution. This work is underpinned by a close, longstanding collaboration with colleagues in psychology, who participate in the work of the laboratory.

A Hybrid Symbolic-Connectionist Processor of Natural Language Semantic Relations. In: EEE Workshop on Hybrid Intelligent Models and Applications (HIMA), IEEE Symposium Series on Computational Intelligence, IEEE SSCI, Nashville, Tennessee, EUA.

IEEE Workshop on Hybrid Intelligent Models and Applications (HIMA) Proceedings. Full text of "Machine learning and its applications: advanced lectures" See other formats. The system provides several different tools for terrain manipulation. We provide a usability study on this system running on MULTI, comparing the laser pointer to the mouse, and the wall display to the tabletop.

The factors compared include accuracy, speed, visibility, comfort and overall preference/ease of use. A special case is grammar induction, which uses context-free grammars in addition to probabilistic information from texts.

Probabilistic Grammar Induction and Disambiguation In this book, Ersan and Charniak present a system for syntactic disambiguation using probabilistic information on word classes derived from the Wall Street Journal : The potentially large number of word hypotheses, the additional book-keeping performance, and the number of individual modules for syntax, semantics and dialog processing explain why the total analysis time of the whole unoptimized screen system is in the order of seconds although a single recurrent network performs in the order of 10 4 : Learning Language in Logic (LLL) is an emerging research area lying at the intersection of computational logic, machine learning and natural language processing (Fig 1).

To see what is to be gained by focussing effort at this intersection begin by considering the role of logic in natural language processing (NLP).

Although both word frequency and word class were significant on their own, the most predictive model of the data was found by using the log-converted CELEX frequency category (see section ).

Raw Frequency in the Corpus One issue when trying to use lexical frequency as a predictive factor in the study of a naturally occurring. A hybrid (symbolic/connectionist) cognitive architecture, DUAL, is proposed. It consists of a multitude of agents having both a symbolic and a connectionist part.

The symbolic part represents some knowledge structure, while the connectionist part represents its. 为大人带来形象的羊生肖故事来历 为孩子带去快乐的生肖图画故事阅读.40 years of AI.Susan C h i p m a n, Ph.D.

(/@nprdc. arpa] Program Manager Cognitive Science, 1 1 4 2 C S Office of N a v a l Research Arlington, V A # T h e 11th A n n u a l • Conference of • The Cognitive • Science Society. 0 August J