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8th International Workshop on Machine Learning, ICML 1991

作者： Whitehall, Bradley L. Lu, Stephen C-Y. Knowledge-Based Engineering Systems Research Laboratory University of Illinois UrbanaIL61801 United States Department of Mechanical and Industrial Engineering Beckman Institute for Advanced Science and Technology United States Department of Computer Science Beckman Institute for Advanced Science and Technology United States

ISBN: (纸本)1558602003

A knowledge-based learning system is developed to demonstrate that intelligently selecting a subset of examples based on domain knowledge for rule induction can be more productive than using all provided examples. knowledge-based learning uses an incomplete domain theory and examples to induce knowledge missing in the theory. knowledge-based learning systems determine where knowledge is missing in a domain theory, select a relevant subset of examples to use in induction, and induce new rules or modify existing rules. © ICML *** rights reserved

关键词： Learning systems

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Empowered service delegation with attribute encryption for distributed cloud computing

Empowered service delegation with attribute encryption for d...

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International Conference on Current Trends in engineering and Technology (ICCTET)

作者： S. S. Aravinth B. Rajkumar M. Ramkumar M. Anitha S. Elangodi Department of Computer Science and Engineering Knowledge Institute of Technology India

Cloud computing has emerged as one of the most influential paradigms in the IT industry. In this, new computing technology requires users to entrust their valuable data to cloud providers, there have been increasing security and privacy concerns on outsourced data. Several schemes employing attribute-based encryption (ABE) have been proposed for access control of outsourced data in cloud computing. The most[1][2] of them suffer from inflexibility in implementing complex access control policies. In this paper, allowing cloud service providers (CSPs), which are not in the same trusted domains as enterprise users, to take care of confidential data, may raise potential security and privacy issues. To keep the sensitive user data confidential against untrusted CSPs, a Natural way is to apply cryptographic approaches, by disclosing Decryption keys only to authorized users. But also provide full delegation, and scalability, so as to best serve the needs of accessing data anytime and anywhere, delegating within enterprises, and achieving a dynamic set of users. [3][4]HASBE employs multiple value assignments for access expiration time to deal with user revocation more efficiently than existing schemes. It can be providefine-grained access control and full delegation. Finally, we propose a scalable revocation scheme by delegating to the CSP most of the computing tasks in revocation, to achieve a dynamic set of users efficiently.

关键词： Access control Cloud computing Encryption Ciphers computer science

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Proximity-based rocchio's model for pseudo relevance 12

Proximity-based rocchio's model for pseudo relevance

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35th Annual ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2012

作者： Miao, Jun Huang, Jimmy Xiangji Ye, Zheng Information Retrieval and Knowledge Management Research Lab. Department of Computer Science and Engineering York University Toronto ON Canada Information Retrieval and Knowledge Management Research Lab. School of Information Technology York University Toronto ON Canada

ISBN: (纸本)9781450316583

Rocchio's relevance feedback model is a classic query expansion method and it has been shown to be effective in boosting information retrieval performance. The selection of expansion terms in this method, however, does not take into account the relationship between the candidate terms and the query terms (e.g., term proximity). Intuitively, the proximity between candidate expansion terms and query terms can be exploited in the process of query expansion, since terms closer to query terms are more likely to be related to the query topic. In this paper, we study how to incorporate proximity information into the Rocchio's model, and propose a proximity-based Rocchio's model, called PRoc, with three variants. In our PRoc models, a new concept (proximity-based term frequency, ptf) is introduced to model the proximity information in the pseudo relevant documents, which is then used in three kinds of proximity measures. Experimental results on TREC collections show that our proposed PRoc models are effective and generally superior to the state-of-the-art relevance feedback models with optimal parameters.A direct comparison with positional relevance model (PRM) on the GOV2 collection also indicates our proposed model is at least competitive to the most recent progress. © 2012 ACM.

关键词： knowledge management

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Examination of multi-objective optimization method for global search using DIRECT and GA

Examination of multi-objective optimization method for globa...

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Congress on Evolutionary Computation

作者： Luyi Wang Hiroyuki Ishida Tomoyuki Hiroyasu Mitsunori Miki Department of Knowledge Engineering and Computer Science Doshisha University Japan

A number of multi-objective genetic algorithms (MOGAs) have been developed to obtain Pareto optimal solutions for multi-objective optimization problems. However, as these methods involve probabilistic algorithms, there is no guarantee that the global search will be conducted in the design variable space. In such cases, there are unsearched areas in the design variable space, and the obtained Pareto solutions may not be truly optimal. In this paper, we propose an optimization method called NSDIRECT-GA to conduct a global search over the design variable space as much as possible, which improves the reliability of the obtained Pareto solutions. The effectiveness of NSDIRECT-GA was examined through numerical experiments. NSDIRECT-GA can obtain not only Pareto solutions, but also grasp the landscape of the search space, which results in higher reliability of the obtained solutions compared to MOGAs.

关键词： Optimization Distance measurement Optimization methods Algorithm design and analysis Reliability Reliability engineering Evolutionary computation

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Conceptual modeling: Past, present and the continuum of the future

Conceptual modeling: Past, present and the continuum of the ...

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作者： Roussopoulos, Nick Karagiannis, Dimitris Department of Computer Science University of Maryland College Park MD 20742 United States Department of Knowledge and Business Engineering University of Vienna Brünner Strasse 72 1210 Vienna Austria

ISBN: (纸本)3642024629

In this paper we give a brief history on conceptual modeling in computer science and we discuss state-of-the-art approaches. It is claimed that a number of problems remain to be solved. "Schema-first" is no longer a viable approach to meet the data needs in the dynamic world of the internet and web services. This is also true for the "schema-later" approach simply because data and data sources constantly change in depth and breadth and can neither wait for the schema to be completed nor for the data to be collected. As a solution we advocate for a new "schema-during" approach, in which the process of Conceptual Modeling is in a continuum with the operations in the database. © 2009 Springer Berlin Heidelberg.

关键词： Web services

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Clonal Selection Based Memetic Algorithm for Job Shop Scheduling Problems

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Journal of Bionic engineering 2008年第2期5卷 111-119页

作者： Jin-hui Yang Liang Sun Heow Pueh Lee Yun Qian Yan-chun Liang College of Computer Science and Technology Jilin University Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education Changchun 130012 P. R. China Institute of High Performance Computing Singapore 117528 Singapore Department of Mechanical Engineering National University of Singapore Singapore 117576 Singapore Institute of Electric and Information Engineering Beihua University Jilin 13202 l P. R. China

A clonal selection based memetic algorithm is proposed for solving job shop scheduling problems in this paper. In the proposed algorithm, the clonal selection and the local search mechanism are designed to enhance exploration and exploitation. In the clonal selection mechanism, clonal selection, hypermutation and receptor edit theories are presented to construct an evolutionary searching mechanism which is used for exploration. In the local search mechanism, a simulated annealing local search algorithm based on Nowicki and Smutnicki＇s neighborhood is presented to exploit local optima. The proposed algorithm is examined using some well-known benchmark problems. Numerical results validate the effectiveness of the proposed algorithm.

关键词： job shop scheduling problem clonal selection algorithm simulated annealing global search local search

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Semi-supervised Multi-kernel Extreme Learning Machine

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Procedia computer science 2018年 129卷 305-311页

作者： Adnan OM Abuassba Zhang Dezheng Zahid Mahmood Department of Computer Science and Communication Engineering University of Science and Technology and Beijing Key Laboratory of Knowledge Engineering for Materials Science Beijing 100083 China

Extreme learning machine (ELM) is a single hidden layer feed forward neural network (SLFN). It expanded to semi-supervised ELM (SSELM) to deal with unlabeled data problem. In such a problem, labeled data is either rare or not cheap. Although SSELM has a good generalization performance, it might be influenced by heterogeneous data from different sources. It is discernible that unbalanced data issue inflicts obstacles in real-world applications including medical diagnostics and credit card fraud detection. To deal with this issue in this paper, we introduce a multi-kernel semi-supervised ELM (MKSSELM). It is more flexible to deal with discrete data from various sources. It matches diverse information from disparate sources and it shows distinction among the data. Instead of using one kernel, we optimize both ELM structural parameters and kernel combination weights. The optimization process accomplished by commanding an L1-norm as a regulation term. Meanwhile, a non-negative constraint on the kernel combination weights is used. The validity of MKSSELM algorithm is confirmed through classification results on real-world benchmark datasets. The proposed algorithm achieved better or comparable results with respect to previous approaches.

关键词： Classification Kernel Learning Semi-supervised Learning Multi-Kernel Learning Extreme Learning Machine

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Thermal radiation effect on SiC-Co 3 O 4 +Diamond/H 2 O trihybrid nanofluid with Stefan blowing and LTNE effects using classical and modified Hamilton-crosser models

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Journal of Radiation Research and Applied sciences 2025年第3期18卷

作者： Ahmed M. Galal Mostafa Mohamed Okasha Dana Mohammad Khidhi Kholoud Saad Albalawi Nouf Abdulrahman Alqahtani Mustafa Bayram Munawar Abbas Ilyas Khan Department of Mechanical Engineering College of Engineering in Wadi Alddawasir Prince Sattam bin Abdulaziz University Saudi Arabia Production Engineering and Mechanical Design Department Faculty of Engineering Mansoura University P.O 35516 Mansoura Egypt Department of Mechanical Engineering College of Engineering Northern Border University Arar Saudi Arabia Department of Petroleum Engineering College of Engineering Knowledge University Erbil 44001 Iraq Department of Petroleum Engineering Al-Kitab University Altun Kupri Iraq Department of Mathematics and Statistics College of Science Imam Mohammad Ibn Saud Islamic University (IMSIU) Riyadh Saudi Arabia Department of Computer Engineering Biruni University 34010 Istanbul Turkey Department of Mathematics Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Chennai 602105 Tamil Nadu India Department of Mathematics The Islamia University of Bahawalpur Bahawalpur 63100 Pakistan Department of Mathematical Sciences Saveetha School of Engineering SIMATS Chennai Tamil Nadu India Department of Mathematics College of Science Al-Zulfi Majmaah University Al-Majmaah 11952 Saudi Arabia

This study proposes to examine the effects of Stefan blowing and thermal radiation on the Marangoni convective velocity of a trihybrid nanofluid across a disk by using LTNE (local thermal non-equilibrium) effect and heat generation. Thermal and mass transfer properties are studied utilizing the Cattaneo-Christov mass and heat flux model. Nanoparticles of silicon carbide ( S i C ) , cobalt oxide ( C o 3 O 4 ) , and diamond ( N D ) dissolved in water ( H 2 O ) make up the trihybrid nanofluid flow model. In this work, the trihybrid nanofluid's rate of heat transfer based on diamond − S i C − C o 3 O 4 / water is investigated by c contrasting the improved model with the Hamilton-Crosser model in its classical form. Thermal transmission efficiency in nuclear reactors, energy storage devices, and microelectronic cooling is improved by the investigation of Cattaneo-Christov flux in trihybrid nanofluids with LTNE effects. The design of effective cooling mechanisms in the automotive and aerospace industries is also aided by the optimization of thermal conductivity predictions through the use of classical and improved Hamilton-Crosser models. The system of PDEs is converted into a non-linear ODE system by applying the required transformations. The Bvp4c method is applied to solve this problem mathematically. When the values of the thermal and solutal relaxation parameters increase, the thermal and solutal distributions decrease.

关键词： Cattaneo-christove heat and mass flux model Trihybrid nanofluid Classical and modified Hamilton-crosser models Stefan blowing impacts

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An influence analysis of the number of members on the quality of knowledge in a collective

An influence analysis of the number of members on the qualit...

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作者： Nguyen, Ngoc Thanh Nguyen, Van Du Hwang, Dosam Division of Knowledge and System Engineering for ICT Faculty of Information Technology Ton Duc Thang University Ho Chi Minh City Viet Nam Faculty of Computer Science and Management Wroclaw University of Science and Technology Poland Department of Computer Engineering Yeungnam University Korea Republic of

Collective knowledge is understood as the common knowledge state of a collective consisting of autonomous units. The knowledge states referred from these autonomous units to some degree reflect the real knowledge state of a subject in the real world, but it is not known to what degree because of incompleteness and uncertainty. Although collective knowledge determination is an important task because these knowledge states can be different from each other, there exists another important issue with its quality. The quality of collective knowledge is based on the difference between the real knowledge state and the collective knowledge. In this study, we investigate the influence of the number of collective members on the quality of collective knowledge. Through experimental analysis, the larger collective we use, the better the quality of collective knowledge will be. In other words, the large number of collective members positively affects the quality of collective knowledge. Besides, some theorems about the relationship between the collective knowledge and the knowledge states in a collective, the influence of adding or removing members on the quality of collective knowledge are also proved. © 2017 - IOS Press and the authors. All rights reserved.

关键词： Quality control

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Acupuncture and Tuina knowledge Graph for Ancient Literature of Traditional Chinese Medicine

Acupuncture and Tuina Knowledge Graph for Ancient Literature...

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2021 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2021

作者： Han, Xiaosong Li, Xiaoran Liang, Yanchun Wang, Xinghao Xu, Dong Guan, Renchu Jilin University Key Laboratory for Symbol Computation and Knowledge Engineering of National Education Ministry College of Computer Science and Technology Changchun China University of Missouri Christopher S. Bond Life Sciences Center Department of Electrical Engineering and Computer Science Columbia United States

ISBN: (纸本)9781665401265

The Traditional Chinese Medicine's ancient literature recorded the massive medical theories and abundant medical experiences. To better understand and utilize, the knowledge from the literature, the Acupuncture and Tuina knowledge Graph is proposed in this paper. Meanwhile, a deep learning network is established for acupuncture and tuina-related entity recognition and entity-relationship extraction. Finally, the trained network is able to reach an 82%+ F1-score for NER and 70%+ F1-score for relationship extraction. © 2021 IEEE.

关键词： Acupuncture

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