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8th Asia-Pacific Web Conference, APWeb 2006: Frontiers of WWW Research and Development

作者： Liang, Bangyong Tang, Jie Li, Juanzi Wang, Kehong Knowledge Engineering Group Department of Computer Science Tsinghua University 100084 Beijing China

ISBN: (纸本)3540311424

This paper addresses the issue of ontology caching on semantic web. The Semantic Web is an extension of the current web in which information is given well-defined meaning, better enabling computers and people to work in cooperation. Ontology serves as the metadata for defining the information on semantic web. Ontology based semantic information retrieval (semantic retrieval) is becoming more and more important. Many research and industrial works have been made so far on semantic retrieval. Ontology based retrieval improves the performance of search engine and web mining. In semantic retrieval, a great number of accesses to ontologies usually lead the ontology servers to be very low efficient. To address this problem, it is indeed necessary to cache concepts and instances when ontology server is running. Existing caching methods from database community can be used in the ontology cache. However, they are not sufficient for dealing with the problem. In the task of caching in database, usually the most frequently accessed data are cached and the recently less frequently accessed data in the cache are removed from it. Different from that, in ontology base, data are organized as objects and relations between objects. User may request one object, and then request another object according to a relation of that object. He may also possibly request a similar object that has not any relations to the object. Ontology caching should consider more factors and is more difficult. In this paper, ontology caching is formalized as a problem of classification. In this way, ontology caching becomes independent from any specific semantic web application. An approach is proposed by using machine learning methods. When an object (e.g. concept or instance) is requested, we view its similar objects as candidates. A classification model is then used to predict whether each of these candidates should be cached or not. Features in classification models are defined. Experimental results indicat

关键词： Data structures

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A collaborative filtering tag recommendation system based on graph

A collaborative filtering tag recommendation system based on...

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International Workshop on Discovery Challenge, DC 2009 at the European Conference on Machine Learning and Principles and Practice of knowledge Discovery in Databases, ECML PKDD 2009

作者： Zhang, Yuan Zhang, Ning Tang, Jie Knowledge Engineering Group Department of Computer Science and Technology Tsinghua University Beijing China

With the rapid development of web2.0 technologies, tagging become much more important today to organize information and help users search the information they need with social bookmarking tools. In order to finish the second task of ECML PKDD challenge 2009, we propose a graph-based collaborative filtering tag recommendation system. We also refer to an algorithm called FolkRank, which is an adaptation of the famous Page Rank. We evaluate and compare these two approaches and show that a combination of these two methods will perform better results for our task.

关键词： Collaborative filtering

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A tag recommendation system based on contents

A tag recommendation system based on contents

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International Workshop on Discovery Challenge, DC 2009 at the European Conference on Machine Learning and Principles and Practice of knowledge Discovery in Databases, ECML PKDD 2009

作者： Zhang, Ning Zhang, Yuan Tang, Jie Knowledge Engineering Group Department of Computer Science and Technology Tsinghua University Beijing China

Social bookmarking tools become more and more popular nowadays and tagging is used to organize information and allow users to recall or search the resources. Users need to type the tags whenever they post a resource, so that a good tag recommendation system can ease the process of finding some useful and relevant keywords for users. Researchers have made lots of relevant work for recommendation system, but those traditional collaborative systems do not fit to our tag recommendation. In this paper, we present two different methods: a simple language model and an adaption of topic model. We evaluate and compare these two approaches and show that a combination of these two methods will perform better results for the task one of PKDD Challenge 2009.

关键词： Recommender systems

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Intelligent waste classification approach based on improved multi-layered convolutional neural network

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Multimedia Tools and Applications 2024年第36期83卷 84095-84120页

作者： Chhabra, Megha Sharan, Bhagwati Elbarachi, May Kumar, Manoj Department of Computer Science & amp Engineering School of Engineering & ampTechnology Sharda University UP Gr. Noida India School of Engineering and Sciences Department of Computer Science and Engineering SRM University-AP Andhra Pradesh Amaravati India Head of School of Computer Science University of Wollongong in Dubai Dubai Knowledge Park Dubai United Arab Emirates School of Computer Science University of Wollongong in Dubai Dubai Knowledge Park Dubai United Arab Emirates MEU Research Unit Middle East University Amman11831 Jordan

This study aims to improve the performance of organic to recyclable waste through deep learning techniques. Negative impacts on environmental and Social development have been observed relating to the poor waste segregation schemes. Separating organic waste from recyclable waste can lead to a faster and more effective recycling process. Manual waste classification is a time-consuming, costly, and less accurate recycling process. Automated segregation in the proposed work uses Improved Deep Convolutional Neural Network (DCNN). The dataset of 2 class category with 25077 images is divided into 70% training and 30% testing images. The performance metrics used are classification Accuracy, Missed Detection Rate (MDR), and False Detection Rate (FDR). The results of Improved DCNN are compared with VGG16, VGG19, MobileNetV2, DenseNet121, and EfficientNetB0 after transfer learning. Experimental results show that the image classification accuracy of the proposed model reaches 93.28%. © The Author(s) 2024.

关键词： Convolutional neural networks

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NEI:A framework for dynamic news event exploration and visualization 14

NEI:A framework for dynamic news event exploration and visua...

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7th International Symposium on Visual Information Communication and Interaction, VINCI 2014

作者： Guo, Xiaofei Li, Juanzi Yang, Ruibing Ma, Xiaoli Knowledge Engineering Group Department of Computer Science and Technology Tsinghua University 10084 China

ISBN: (纸本)9781450327657

Nowadays, there are many events reported by News Media everyday, which contains a massive number of news. People are getting more and more interested in understanding how an event evolves after it happens. News related to the same event or similar events usually has more common entities and stronger topic correlations, which is a new perspective to study news event. Due to the complexity of event evolving process, event visualization has been a big challenge for a long time. In this paper, we design a novel four-phase framework NEI(News Event Insight) that focuses on visualizing a news event properly and clearly, namely (1)Entity Topic Modeling. We extract topics and entities through timeline. (2)Temporal Topic Correlation Analysis. Based on the topic modeling result, we design two methods to select hot topics and build links for them. (3)Keyword Extraction. Specially, we combine string frequency with syntax features and use language models to acquire candidate keywords for representing topics. (4)Visualization. Visualization demonstrates the quantifying properties of topics related to a certain event. A case study shows our framework achieves promising results on both single event and similar events. Copyright 2014 ACM.

关键词： Visualization

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Sentential paraphrase generation for agglutinative languages using SVM with a string kernel 28

Sentential paraphrase generation for agglutinative languages...

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28th Pacific Asia Conference on Language, Information and Computation, PACLIC 2014

作者： Park, Hancheol Gweon, Gahgene Choi, Ho-Jin Heo, Jeong Ryu, Pum-Mo Department of Knowledge Service Engineering KAIST Japan Department of Computer Science KAIST Japan Knowledge Mining Research Team ETRI Japan

ISBN: (纸本)9786165518871

Paraphrase generation is widely used for various natural language processing (NLP) applications such as question answering, multi-document summarization, and machine translation. In this study, we identify the problems occurring in the process of applying existing probabilistic model-based methods to agglutinative languages, and provide solutions by reflecting the inherent characteristics of agglutinative languages. More specifically, we propose and evaluate a sentential paraphrase generation (SPG) method for the Korean language using Support Vector Machines (SVM) with a string kernel. The quality of generated paraphrases is evaluated using three criteria: (1) meaning preservation, (2) grammaticality, and (3) equivalence. Our experiment shows that the proposed method outperformed a probabilistic model-based method by 12%, 16%, and 17%, respectively, with respect to the three criteria. Copyright 2014 by Hancheol Park, Gahgene Gweon, Ho-Jin Choi, Jeong Heo, and Pum-Mo Ryu.

关键词： Support vector machines

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Adaptive tourism modeling and socialization system

Adaptive tourism modeling and socialization system

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2009 IEEE International Conference on Social Computing, SocialCom 2009

作者： Coelho, Bruno Martins, Constantino Almeida, Ana GECAD - Knowledge Engineering and Decision Support Group Computer Science Department Institute of Engineering Porto Portugal

ISBN: (纸本)9780769538235

This paper presents an undertaken research work about the development of an Adaptive Tourism Modeling System which attempts to correctly model a tourism web application user profile. This paper will follow the methodology used behind the concept of the application, 'User Modeling as a process', which consists of three specific modules in order to achieve a clear user modeling technology. The user representation module devises a collection of knowledge representation formalisms that co-exist in order to constitute the system's view of the user;the user reasoning module is responsible for the execution of several inference tasks as well as the generation of possibly new and valuable information about the user, using the latter module. The user concept that comes out of these two modules will ultimately be used by various kinds of application-level systems, namely a recommender system, therefore instantiating a project-dependent third module. © 2009 IEEE.

关键词： Recommender systems

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Certificate management system using blockchain 11th

Certificate management system using blockchain

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11th International Conference on Soft Computing and Pattern Recognition, SoCPaR 2019, and 11th World Congress on Nature and Biologically Inspired Computing, NaBIC 2019

作者： Endurthi, Anjaneyulu Khare, Akhil Computer Science and Engineering Department Rajiv Gandhi University of Knowledge Technologies BasarTelangana India Computer Science and Engineering Department MVSR Engineering College HyderabadTelangana India

ISBN: (纸本)9783030493448

Overcoming the problems of existing file storage and sharing approaches, this paper gives an efficient way of storing and sharing the files using blockchain and smart contracts. As an example, Managing student’s information and sharing them or giving access to unauthorized people in a much secured way is one of the major responsibilities of any university or organization. Instead of storing the certificates in a normal database, blockchain technology can be used to store the certificates. In our approach, the certificates and other documents will be uploaded to the blockchain and will be shared securely when any third party needs to access the certificates. The university administrator has ultimate rights to upload student’s certificates and managing them. Students can view their documents and certificates;other unauthorized people (third party/organization/employer/others) can access the files after taking permission of the college administrator. These types of approaches are very useful in this era where efficient storage and sharing the files plays a crucial role. The feature which differentiates our approach of certificate management system from existing certificate management system is, our system is decentralized, cryptographically secure, immutable and efficient. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021.

关键词： Smart contract

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Security Issues and Defensive Approaches in Deep Learning Frameworks

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Tsinghua science and Technology 2021年第6期26卷 894-905页

作者： Hongsong Chen Yongpeng Zhang Yongrui Cao Jing Xie Department of Computer Science University of Science and Technology Beijing(USTB)Beijing 100083China Beijing Key Laboratory of Knowledge Engineering for Materials Science Beijing 100083China Department of Computer Science and Technology University of Science and Technology Beijing(USTB)Beijing 100083China Defense Electronics Institute China Industrial Control System Cyber Emergency Response TeamBeijing 100040China

Deep learning frameworks promote the development of artificial intelligence and demonstrate considerable potential in numerous ***,the security issues of deep learning frameworks are among the main risks preventing the wide application of *** on deep learning frameworks by malicious internal or external attackers would exert substantial effects on society and *** start with a description of the framework of deep learning algorithms and a detailed analysis of attacks and vulnerabilities in *** propose a highly comprehensive classification approach for security issues and defensive approaches in deep learning frameworks and connect different attacks to corresponding defensive ***,we analyze a case of the physical-world use of deep learning security *** addition,we discuss future directions and open issues in deep learning *** hope that our research will inspire future developments and draw attention from academic and industrial domains to the security of deep learning frameworks.

关键词： adversarial examples deep learning frameworks defensive approaches security issues

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ExerLink: Enabling pervasive social exergames with heterogeneous exercise devices 12

ExerLink: Enabling pervasive social exergames with heterogen...

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10th International Conference on Mobile Systems, Applications, and Services, MobiSys'12

作者： Park, Taiwoo Hwang, Inseok Lee, Uichin Lee, Sunghoon Ivan Yoo, Chungkuk Lee, Youngki Jang, Hyukjae Choe, Sungwon Peter Park, Souneil Song, Junehwa Department of Computer Science KAIST Korea Republic of Department of Knowledge Service Engineering KAIST Korea Republic of Computer Science Department UCLA United States

ISBN: (纸本)9781450313018

We envision that diverse social exercising games, or exergames, will emerge, featuring much richer interactivity with immersive game play experiences. Further, the recent advances of mobile devices and wireless networking will make such social engagement more pervasive - people carry portable exergame devices (e.g., jump ropes) and interact with remote users anytime, anywhere. Towards this goal, we explore the potential of using heterogeneous exercise devices as game controllers for a multi-player social exergame;e.g., playing a boat paddling game with two remote exercisers (one with a jump rope, and the other with a treadmill). In this paper, we propose a novel platform called ExerLink that converts exercise intensity to game inputs and intelligently balances intensity/delay variations for fair game play experiences. We report the design considerations and guidelines obtained from the design and development processes of game controllers. We validate the efficacy of game controllers and demonstrate the feasibility of social exergames with heterogeneous exercise devices via extensive human subject studies. © 2012 ACM.

关键词： Rope

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