排序方式: 共有48条查询结果,搜索用时 15 毫秒
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Cercone N. Aijun An Chan C. 《Knowledge and Data Engineering, IEEE Transactions on》1999,11(1):166-174
Researchers have embraced a variety of machine learning (ML) techniques in their efforts to improve the quality of learning programs. The recent evolution of hybrid architectures for machine learning systems has resulted in several approaches that combine rule induction methods with case-based reasoning techniques to engender performance improvements over more traditional single-representation architectures. We briefly survey several major rule-induction and case-based reasoning ML systems. We then examine some interesting hybrid combinations of these systems and explain their strengths and weaknesses as learning systems. We present a balanced approach to constructing a hybrid architecture, along with arguments in favor of this balance and mechanisms for achieving a proper balance. Finally, we present some initial empirical results from testing our ideas and draw some conclusions based on those results 相似文献
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Xindong?WuEmail author Philip?S.?Yu Gregory?Piatetsky-Shapiro Nick?Cercone T.?Y.?Lin Ramamohanarao?Kotagiri Benjamin?W.?Wah 《Knowledge and Information Systems》2003,5(2):248-261
At the 2001 IEEE International Conference on Data Mining in San Jose, California,
on November 29 to December 2, 2001, there was a panel discussion on how data
mining research meets practical development. One of the motivations for organizing the
panel discussion was to provide useful advice for industrial people to explore their directions
in data mining development. Based on the panel discussion, this paper presents
the views and arguments from the panel members, the Conference Chair and the Program
Committee Co-Chairs. These people as a group have both academic and industrial
experiences in different data mining related areas such as databases, machine learning,
and neural networks. We will answer questions such as (1) how far data mining is from
practical development, (2) how data mining research differs from practical development,
and (3) what are the most promising areas in data mining for practical development. 相似文献
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The objective of this study is to develop a knowledge-base framework for generatingcooperative answers to indirect queries. Anindirect query can be considered as a nonstandard database query in which a user did not specify explicitly the information request. In a cooperative query answering system, a user's indirect query should be answered with an informative response, either anaffirmative response or anegative response, which is generated on the basis of the inference of the user's information request and the reformulation of the users' indirect query.This paper presents methods for inferring users' intended actions, determining users' information requirements, and for automatically reformulating indirect queries into direct queries. The inference process is carried out on the basis of a user model, calluser action model, as well as the query context. Two kinds ofinformative responses, i.e.affirmative responses andnegative responses can be generated by arule-based approach. 相似文献
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Multiply sectioned Bayesian networks (MSBNs) support multi-agent probabilistic inference in distributed large problem domains, where agents (subdomains) are organized by a tree structure (called hypertree). In earlier work, all belief updating methods on a hypertree are made of two rounds of propagation, each of which is implemented as a recursive process. Both processes need to be started from the same designated (root) hypernode. Agents perform local belief updating at most in a partial parallel manner. Such methods may not be suitable for practical multi-agent environments because they are easy to crush for the problems happened in communication or local belief updating. In this paper, we present a fault-tolerant belief updating method for multi-agent probabilistic inference. In this method, multiple agents concurrently perform exact belief updating in a complete parallel. Temporary problems happened from time to time at some agents or some communication channels would not prevent agents from eventually converging to the correct beliefs. Permanently disconnected communication channels would not keep the properly connected portions of the system from appropriately finishing their belief updating within portions. Compared to the previous traversal-based belief updating, the proposed approach is not only fault-tolerant but also robust and scalable. 相似文献
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Srisavakon Dangsaart Kanlaya Naruedomkul Nick Cercone Booncharoen Sirinaovakul 《Computers & Education》2008
We present the Intelligent Thai text – Thai sign translation for language learning (IT3STL). IT3STL is able to translate Thai text into Thai sign language simply and conveniently anytime, anywhere. Thai sign language is the language of the deaf in Thailand. In the translation process, the distinction between Thai text and Thai sign language in both grammar and vocabulary are concerned in each processing step to ensure the accuracy of translation. IT3STL was designed not only to be an automatic interpreter but also to be a language tutor assistant. It provides meaning of each word and describes the structure formation and word order of the translated sentence. With IT3STL, the deaf and hearing-impaired are able to enhance their communication ability and to improve their knowledge and learning skills. Moreover IT3STL has increased motivation and opportunity for them to access multimedia and e-learning. 相似文献
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