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Proceedings 11th International Conference on Tools with Artificial Intelligence最新文献

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Solving hard satisfiability problems: a unified algorithm based on discrete Lagrange multipliers 求解难满足性问题:基于离散拉格朗日乘子的统一算法
Proceedings 11th International Conference on Tools with Artificial Intelligence Pub Date : 1999-11-08 DOI: 10.1109/TAI.1999.809788
Zhe Wu, B. Wah
{"title":"Solving hard satisfiability problems: a unified algorithm based on discrete Lagrange multipliers","authors":"Zhe Wu, B. Wah","doi":"10.1109/TAI.1999.809788","DOIUrl":"https://doi.org/10.1109/TAI.1999.809788","url":null,"abstract":"Presents improved strategies in DLM-99-SAT (Discrete Lagrange Multipliers 1999, Satisfiability) to escape from traps and to select proper parameter sets to use when applied to solve some difficult but satisfiable SAT problems. One of the main issues in DLM-99-SAT is that it has a large number of tunable parameters, making it difficult to determine the best parameters to use when given a new instance. To this end, we propose a set of performance metrics and a set of rules using these metrics that determine at run-time the best parameters to use for a specific instance. Our experimental results show that these rules are able to select the most suitable parameter set for each instance with very little overhead. Finally, we verify the performance of DLM-99-SAT by solving some benchmarks in SATLIB (SATisfiability problems LIBrary) and some of the most difficult but satisfiable DIMACS SAT benchmark problems, including par32-1-c to par32-4-c and hanoi4-simple.","PeriodicalId":194023,"journal":{"name":"Proceedings 11th International Conference on Tools with Artificial Intelligence","volume":"104 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127521464","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 15
HOT: heuristics for oblique trees HOT:斜树的启发式
Proceedings 11th International Conference on Tools with Artificial Intelligence Pub Date : 1999-11-08 DOI: 10.1109/TAI.1999.809771
V. Iyengar
{"title":"HOT: heuristics for oblique trees","authors":"V. Iyengar","doi":"10.1109/TAI.1999.809771","DOIUrl":"https://doi.org/10.1109/TAI.1999.809771","url":null,"abstract":"This paper presents a new method (HOT) of generating oblique decision trees. Oblique trees have been shown to be useful tools for classification in some problem domains, producing accurate and intuitive solutions. The method can be incorporated into a variety of existing decision tree tools and the paper illustrates this with two very distinct tree generators. The key idea is a method of learning oblique vectors and using the corresponding families of hyperplanes orthogonal to these vectors to separate regions with distinct dominant classes. Experimental results indicate that the learnt oblique hyperplanes lead to compact and accurate oblique trees. HOT is simple and easy to incorporate into most decision tree packages, yet its results compare well with much more complex schemes for generating oblique trees.","PeriodicalId":194023,"journal":{"name":"Proceedings 11th International Conference on Tools with Artificial Intelligence","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126522241","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 11
Towards a computationally intelligent lesson adaptation for a distance learning course 面向远程学习课程的计算智能课程适应
Proceedings 11th International Conference on Tools with Artificial Intelligence Pub Date : 1999-11-08 DOI: 10.1109/TAI.1999.809758
G. D. Magoulas, K. Papanikolaou, M. Grigoriadou
{"title":"Towards a computationally intelligent lesson adaptation for a distance learning course","authors":"G. D. Magoulas, K. Papanikolaou, M. Grigoriadou","doi":"10.1109/TAI.1999.809758","DOIUrl":"https://doi.org/10.1109/TAI.1999.809758","url":null,"abstract":"A neuro-fuzzy approach is introduced to implement lesson adaptation in a Web-based course. Several key points that affect the effectiveness of an adaptive learning environment are investigated the development of the educational material, the structure of the domain knowledge, the instructional design and the evaluation of the learner knowledge under uncertainty. The proposed approach allows the generation of the content of a hypermedia page from pieces of educational material based on goal-oriented teaching and making use of the background knowledge of the learner.","PeriodicalId":194023,"journal":{"name":"Proceedings 11th International Conference on Tools with Artificial Intelligence","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115153532","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 24
Augmented transition networks as video browsing models for multimedia databases and multimedia information systems 增强转换网络作为多媒体数据库和多媒体信息系统的视频浏览模型
Proceedings 11th International Conference on Tools with Artificial Intelligence Pub Date : 1999-11-08 DOI: 10.1109/TAI.1999.809783
Shu‐Ching Chen, S. Sista, M. Shyu, R. Kashyap
{"title":"Augmented transition networks as video browsing models for multimedia databases and multimedia information systems","authors":"Shu‐Ching Chen, S. Sista, M. Shyu, R. Kashyap","doi":"10.1109/TAI.1999.809783","DOIUrl":"https://doi.org/10.1109/TAI.1999.809783","url":null,"abstract":"In an interactive multimedia information system, users should have the flexibility to browse and choose various scenarios they want to see. This means that two-way communications should be captured by the conceptual model. Digital video has gained increasing popularity in many multimedia applications. Instead of sequential access to the video contents, the structuring and modeling of video data so that users can quickly and easily browse and retrieve interesting materials has become an important issue in designing multimedia information systems. An abstract semantic model called the augmented transition network (ATN), which can model video data and user interactions, is proposed in this paper. An ATN and its subnetworks can model video data based on different granularities, such as scenes, shots and key frames. Multimedia input strings are used as inputs for ATNs. The details of how to use multimedia input strings to model video data are also discussed. Key frame selection is based on the temporal and spatial relations of semantic objects in each shot. These relations are captured from our proposed unsupervised video segmentation method, which considers the problem of partitioning each frame as a joint estimation of the partition and class parameter variables. Unlike existing semantic models, which only model multimedia presentation, multimedia database searching or browsing, ATNs together with multimedia input strings can model these three in one framework.","PeriodicalId":194023,"journal":{"name":"Proceedings 11th International Conference on Tools with Artificial Intelligence","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115190850","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 45
Fast and efficient searching of multimedia databases using holographic memory 利用全息存储器实现多媒体数据库的快速高效检索
Proceedings 11th International Conference on Tools with Artificial Intelligence Pub Date : 1999-11-08 DOI: 10.1109/TAI.1999.809824
P. Berra, P. Mitkas, Shengluan Zhong
{"title":"Fast and efficient searching of multimedia databases using holographic memory","authors":"P. Berra, P. Mitkas, Shengluan Zhong","doi":"10.1109/TAI.1999.809824","DOIUrl":"https://doi.org/10.1109/TAI.1999.809824","url":null,"abstract":"With the ever-expanding size of multimedia databases it is important to seek new technologies that improve the performance of systems that manage these databases. One such technology is holographic memory which has some very interesting attributes such as massive parallelism, high speed, and content searching. A volume holographic database system (VHDS) serves as a building block for a postulated terabyte electro-optical computer architecture (EOCA). Data mining and image management applications are considered for the EOCA. Using the associative processing capabilities of the holographic memory a number of queries can be completed in a matter of seconds for the entire terabyte database. These queries could take hours on sequential computers. However, the state of the art in holographic memory lags far behind electronic computing and thus considerably more research and development must be performed before these systems can realize their vast potential.","PeriodicalId":194023,"journal":{"name":"Proceedings 11th International Conference on Tools with Artificial Intelligence","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130280638","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
An unsupervised collaborative learning method to refine classification hierarchies 一种改进分类层次的无监督协作学习方法
Proceedings 11th International Conference on Tools with Artificial Intelligence Pub Date : 1999-11-08 DOI: 10.1109/TAI.1999.809797
Cédric Wemmert, P. Gançarski, J. Korczak
{"title":"An unsupervised collaborative learning method to refine classification hierarchies","authors":"Cédric Wemmert, P. Gançarski, J. Korczak","doi":"10.1109/TAI.1999.809797","DOIUrl":"https://doi.org/10.1109/TAI.1999.809797","url":null,"abstract":"This article deals with the design of a hybrid learning system. This system integrates different kinds of unsupervised learning methods and gives a set of class hierarchies as the result. The classes in these hierarchies are very similar. The method occurrences compare their results and automatically refine them to try to make them converge towards a unique hierarchy that unifies all the results. Thus, the system decreases the importance of the initial choices made when initializing an unsupervised learning (the choice of the method and its parameters) and to solve some of the limitations of the methods used such as an imposed number of classes, a non-hierarchical result, or the size of the hierarchy.","PeriodicalId":194023,"journal":{"name":"Proceedings 11th International Conference on Tools with Artificial Intelligence","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130232472","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 5
Signal trend identification with fuzzy methods 用模糊方法识别信号趋势
Proceedings 11th International Conference on Tools with Artificial Intelligence Pub Date : 1999-11-08 DOI: 10.1109/TAI.1999.809813
Xin Wang, T. Wei, J. Reifman, L. Tsoukalas
{"title":"Signal trend identification with fuzzy methods","authors":"Xin Wang, T. Wei, J. Reifman, L. Tsoukalas","doi":"10.1109/TAI.1999.809813","DOIUrl":"https://doi.org/10.1109/TAI.1999.809813","url":null,"abstract":"A fuzzy logic-based methodology for online signal trend identification is introduced. Although signal trend identification is complicated by the presence of noise, fuzzy logic can help capture important features of online signals and classify incoming power plant signals into increasing, decreasing and steady-state trend categories. In order to verify the methodology, a code named PROTREN is developed and tested using plant data. The results indicate that the code is capable of detecting transients accurately, identifying trends reliably, and not misinterpreting a steady-state signal as a transient one.","PeriodicalId":194023,"journal":{"name":"Proceedings 11th International Conference on Tools with Artificial Intelligence","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122519911","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 5
Ontology based personalized search 基于本体的个性化搜索
Proceedings 11th International Conference on Tools with Artificial Intelligence Pub Date : 1999-11-08 DOI: 10.1109/TAI.1999.809829
A. Pretschner, Susan Gauch
{"title":"Ontology based personalized search","authors":"A. Pretschner, Susan Gauch","doi":"10.1109/TAI.1999.809829","DOIUrl":"https://doi.org/10.1109/TAI.1999.809829","url":null,"abstract":"With the exponentially growing amount of information available on the Internet, the task of retrieving documents of interest has become increasingly difficult. Search engines usually return more than 1,500 results per query, yet out of the top twenty results, only one half turn out to be relevant to the user. One reason for this is that Web queries are in general very short and give an incomplete specification of individual users' information needs. This paper explores ways of incorporating users' interests into the search process to improve the results. The user profiles are structured as a concept hierarchy of 4,400 nodes. These are populated by 'watching over a user's shoulder' while he is surfing. No explicit feedback is necessary. The profiles are shown to converge and to reflect the actual interests quite well. One possible deployment of the profiles is investigated: re-ranking and filtering search results. Increases in performance are moderate but noticeable and show that fully automatic creation of large hierarchical user profiles is possible.","PeriodicalId":194023,"journal":{"name":"Proceedings 11th International Conference on Tools with Artificial Intelligence","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132399473","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 375
Autonomous filter engine based on knowledge acquisition from the Web 基于Web知识获取的自主过滤引擎
Proceedings 11th International Conference on Tools with Artificial Intelligence Pub Date : 1999-11-08 DOI: 10.1109/TAI.1999.809817
L. Lancieri, Pierre Agostini, Nicolas Saillard, Samuel Legouix
{"title":"Autonomous filter engine based on knowledge acquisition from the Web","authors":"L. Lancieri, Pierre Agostini, Nicolas Saillard, Samuel Legouix","doi":"10.1109/TAI.1999.809817","DOIUrl":"https://doi.org/10.1109/TAI.1999.809817","url":null,"abstract":"For a long time filtering data has been a very important matter. With the growth of the Internet this question has become more and more pressing. Everyone knows that finding information is not always very easy, because of the large amount of data that the network contains. More generally, our concern here is not only to find what is interesting to download but also to avoid what is unsuitable. One of the different ways recently explored to address the question of filtering and rating information is to apply the studies done in the field of linguistic and artificial intelligence to the Web. In this context, we would like to show that it is possible to build an easy going and low cost tool to compare information. This tool will use automatically extracted and selected Web contents to build a specialized knowledge database that can easily be adapted to any subject in any language.","PeriodicalId":194023,"journal":{"name":"Proceedings 11th International Conference on Tools with Artificial Intelligence","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132403678","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Using parallel techniques to improve the computational efficiency of evidential combination 利用并行技术提高证据组合的计算效率
Proceedings 11th International Conference on Tools with Artificial Intelligence Pub Date : 1999-11-08 DOI: 10.1109/TAI.1999.809766
X. Hong, K. Adamson, Weiru Liu
{"title":"Using parallel techniques to improve the computational efficiency of evidential combination","authors":"X. Hong, K. Adamson, Weiru Liu","doi":"10.1109/TAI.1999.809766","DOIUrl":"https://doi.org/10.1109/TAI.1999.809766","url":null,"abstract":"This paper presents a method of partitioning a Markov tree of belief functions into clusters so as to efficiently implement parallel belief function propagations on the basis of the local computation technique. Our method initially represents computations of combining evidence on all nodes in a Markov tree as parallelism instances, then balances the computation load among these instances, and finally partitions them into clusters which can be mapped onto a set of processors in a PowerPC network. The advantage of our method is that the maximum parallelization can still be achieved, even with limited processor availability.","PeriodicalId":194023,"journal":{"name":"Proceedings 11th International Conference on Tools with Artificial Intelligence","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132603359","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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