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international conference on Tools for Artificial Intelligence (ICTAI)

作者： P.S. Jacobs SRA Corporation Arlington VA USA

Many of the more ambitious goals of artificial intelligence have proved unattainable because of the failure of the many small, successful systems to scale up. The general use of technologies such as natural language interfaces and expert systems has done little to alleviate the basic difficulties and overwhelming cost of knowledge engineering. At the same time, emerging text processing techniques, including data extraction from text and new text retrieval methods, offer a means of accessing stores of information many times larger than any organized knowledge base or database. Although knowledge acquisition from text is at the heart of the information management problem, interpreting text, paradoxically, requires large amounts of knowledge, mainly about the way words are used in context. In other words, before intelligent text processing systems can be trained to mine for useful knowledge, they must already have enough knowledge to interpret what they read. The point at which there is "enough", is still a matter of debate, as no real program seems close to having enough knowledge to achieve general human-like understanding. Current research in large-scale natural language processing has come, rightly, to focus on lexical acquisition as the key to future progress. Unfortunately, the current state of the art is quite far from the recipe for acquiring knowledge about words, because it leans too heavily on resources that are available, without consideration for what is needed.< >

关键词： Information management Text processing Data mining Artificial intelligence natural languages Expert systems Costs knowledge engineering Information retrieval Databases

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Command language For Supervisory Control Of Mining Teleoperation

Command Language For Supervisory Control Of Mining Teleopera...

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WVU international Mining Electrotechnology conference

作者： C.A. Ntuen Eui H. Park Department of Industrial Engineering College of Engineering North Carolina Agriculture and Technical State University Greensboro NC USA

This paper presents a knowledge-based user interface model system for support of a mining teleoperation. The model makes extensive use of non-verbal sentential structures (NVSS). The NVSS is built with the GURU/sup tm/ expert system and natural a language processing shell. Conceptually, the elements of the NVSS are built around the user intentions which allow knowledge representation about mining tasks as finite state grammars of behavioral as well as task trajectories. A prototype dialogue-based interaction system known as OASIP (Open Architecture for System Interaction Platform) is developed. OASIP is an adaptive system that exploits several sources of environmental knowledge from built-in blackboard cells.

关键词： Command languages Supervisory control Humans Remotely operated vehicles Mobile robots Communication system control Uncertainty IEEE members Industrial engineering Educational institutions

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On jointly learning the parameters in a character-synchronous integrated speech and language model

On jointly learning the parameters in a character-synchronou...

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international conference on Acoustics, Speech, and Signal processing (ICASSP)

作者： Tung-Hui Chiang Yi-Chung Lin Keh-Yih Su Department of Electrical Engineering National Tsing Hua University Hsinchu Taiwan

ISBN: (纸本)0780317750

A joint learning algorithm which enabled the parameters in an integrated speech and language model to be trained jointly, was proposed in this paper. The integrated model enhanced the spoken language system with high level knowledge, and operated in a character-synchronous mode. This integration model was tested on the task of recognizing isolated Chinese characters in the speaker independent mode with very large vocabulary of 90,495 words, and the performance of 88.26% character accuracy rate was obtained. In contrast, only 75.71% accuracy rate was achieved with the baseline system, which directly coupled the speech recognizer with a character bi-gram language module. Afterwards, the parameters of both speech and language modules were jointly adjusted according to their contribution in discrimination. The dynamic range variations among the parameters in different modules were also well tuned during the learning processes. After applying this procedure to the character-synchronous integration model, a very promising result of 94.16% character accuracy (75.96% error reduction rate) was obtained.< >

关键词： natural languages Dynamic range Maximum likelihood estimation Character recognition Speech recognition Robustness Tagging Testing Vocabulary Dictionaries

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INTEGRATING knowledge-BASED SYSTEMS AND DATABASES

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CLINICA CHIMICA ACTA 1993年第1-2期222卷 101-115页

作者： GRIMSON, JB Knowledge and Data Engineering Group Department of Computer Science Trinity College Dublin 2 Ireland

In recent years, there has been an explosion of interest among the computing community in the field of artificial intelligence, particularly in the areas of natural language processing and knowledge-based systems (KBS). The medical domain has seen the development of hundreds of KBSs and there is substantial evidence to show that the application of a knowledge-based approach to decision support can go a long way towards overcoming the information overload experienced by many clinicians today. Yet many of these medical KBSs are still at the prototype stage and are mainly confined to research laboratories. There are many reasons for this apparently slow take-up of the technology, but one of the most significant is the lack of integration into the regular routine information processing of the organisation, in particular the database processing. This paper discusses the benefits of such integration and methods for achieving it in the context of general trends in information systems. Database technology provides efficient and secure management of large amounts of data in a multi-user, multiapplication environment. knowledge-based technology, on the other hand, provides mechanisms for building intelligent systems. Thus, for example, given a set of facts about a domain (symptoms, laboratory test results, etc.) together with a set of rules which apply to that domain (e.g.'if TT4 > 150 nmol/l then suspect hyperthyroidism'), a KBS can deduce new information about that domain automatically. The effective integration of these two technologies is seen as a means of achieving the intelligent information systems of the future. There are three basic approaches to integrating KBSs and databases. The first is to start with the KBS and incorporate data management functions. Alternatively, intelligence from the KBS can be incorporated into the database. Finally, the two systems can be allowed to coexist as independent systems which can talk to each other by means of standard interfaces.

关键词： DATABASE MANAGEMENT knowledge-BASED SYSTEMS EXPERT SYSTEMS

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Proceedings of the 5th international conference on Tools with Artificial Intelligence TAI '93

Proceedings of the 5th International Conference on Tools wit...

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Proceedings of the 5th international conference on Tools with Artificial Intelligence TAI '93

ISBN: (纸本)0818642009

The conference materials contain 95 papers. The topics covered include artificial neural networks;artificial intelligence (AI) algorithms;AI and object-oriented systems;AI and software engineering;knowledge base architectures;machine learning;reasoning under uncertainty, fuzzy logic;expert systems and environments;natural language processing;logic and intelligent databases;parallel processing and hardware support.

关键词： Artificial intelligence

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On using syntactic constraints in text recognition

On using syntactic constraints in text recognition

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international conference on Document Analysis and Recognition

作者： R.M.K. Sinha Department of Computer Science and Engineering Indian Institute of Technology Kanpur India

The human reading process makes use of a number of knowledge sources which communicate with each other in arriving at correct interpretation. In order to obtain human competing performance in machines, this knowledge integration capability has to be built into the machines. A strategy for integration of the natural language syntactic knowledge in the text recognition task is presented. The syntactic knowledge layer is helpful only in those cases where the bottom-up hypothesized word alternatives belong to different syntactic categories. However, in the cases of unresolved ambiguities, the system comes with character pairs/groups over which more computationally-intensive low level processing is performed to ascertain its/their correct identity(/ies).< >

关键词： Text recognition Humans Character recognition Retina Matrices Computer science knowledge engineering natural languages Optical computing Optical character recognition software

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Linguistic instructions learning based on associative memories and its application to a facial model

Linguistic instructions learning based on associative memori...

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international Joint conference on Neural Networks (IJCNN)

作者： W. Ushida T. Takagi T. Yamaguchi Laboratory for lnternational Fuzzy Engineering Research Yokohama Japan Faculty of Engineering Utsunomiya University Utsunomiya Japan

Human learning on linguistic level is superior to other kinds of learning. If a neural network can be trained by natural language instead of numerical data, we can train machines as well as human beings without detailed training data. Conventional neural networks need numerical data to be trained. On the other hand, a linguistic level learning is able to train machines as if they were human beings. In this paper, we propose a linguistic instructions learning method based on a fuzzy associative memory network, which acquires knowledge from natural language, and we refine a facial expressions model by means of this method.

关键词： Humans Associative memory Biological neural networks natural languages Fuzzy systems Learning systems Equations Training data Machine learning Information processing

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SPEECH UNDERSTANDING ON A MASSIVELY PARALLEL COMPUTER 2

SPEECH UNDERSTANDING ON A MASSIVELY PARALLEL COMPUTER

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2nd international conference on Spoken language processing, ICSLP 1992

作者： Chung, Sang-Hwa Moldovan, Dan Department of Electrical Engineering-Systems University of Southern California Los AngelesCA90089-2562 United States

In this paper, we present a parallel computational model for the integration of speech and natural language processing (NLP). We have developed a parallel speech understanding system on the semantic network array processor (SNAP), a massively parallel computer developed at the University of Southern California. The parallel speech understanding algorithm is based on a memory-based parsing scheme. The key to the integration of speech and linguistic processing is the construction of a hierarchically structured knowledge base. The processing is carried out by passing markers parallelly through the knowledge base. Speech-specific problems like insertion, deletion, substitution, word boundary problems, and multiple hypotheses problems were analyzed and their parallel solutions were provided. The experimental results show that the processing time increases linearly with the length of target sentences, and increases logarithmically with the size of the knowledge base. This demonstrates that a massively parallel approach provides a viable platform for integrating speech and NLP on larger domains. © 1992 2nd international conference on Spoken language processing, ICSLP 1992. All rights reserved.

关键词： Speech

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2nd international Logic Programming Summer School, LPSS 1992

2nd International Logic Programming Summer School, LPSS 1992

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2nd international Logic Programming Summer School, LPSS 1992

ISBN: (纸本)9783540559306

The proceedings contain 22 papers. The special focus in this conference is on international Logic Programming Summer School. The topics include: Theory and practice in logic programming;constraint logic programming;scheduling and optimisation in the automobile industry;factory scheduling using finite domains;the prince project and its applications;knowledge based PPS applications in PROTOS-L;the SECReTS banking expert system from phase 1 to phase 2;logic engineering and clinical dilemmas;a knowledge-based approach to strategic planning;expert systems in mining;natural and formal language processing;PUNDIT — natural language interfaces;the esteam-316 dialogue manager;legislation as logic programs;knowledge representation for natural language processing;a set of tools for VHDL design;reasoning about logic programs;software formal specification by logic programming: the example of standard prolog;reverse engineering in prolog;opium — an advanced debugging system and automatic theorem proving within the portable AI lab.

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NLUS - A prolog based natural language understanding system 4

NLUS - A prolog based natural language understanding system

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4th international conference on Computing and Information, ICCI 1992

作者： Lee, M.C. Leong, H.V. Dept of Computer Science Chinese University of Hong Kong Shatin Hong Kong Dept of Computer Science University of California Santa BarbaraCA93106 United States

ISBN: (纸本)081862812X

NLUS is a Prolog-based natural language understanding system, which exploits multi-knowledge representation formalisms. Sentences input from the user are converted into semantic networks andlor production rules;whereas the grammar rules are represented in predicate logic. After processing a sentence, the software may initiate its inference engine to deduce a response. A question would also be parsed and converted into a semantic structure which may contain possibly some missing information. To find an answer to a question, the missing information may be extracted from another related semantic structure in the working memory. At present, the software can handle sentences with relatively simple syntactic structures and some restricted types of questions. However, intelligent man-machine dialogues can be realized. It is particularly good at handing the rule-oriented type of sentences and is considered a decent prototype for experimenting with natural language understanding. © 1992 IEEE.

关键词： Semantics

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