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Journal of Software 2009年第8期4卷 808-820页

作者： Guo, Song Keeney, John Lewis, David O'Sullivan, Declan Knowledge and Data Engineering Group School of Computer Science and Statistics Trinity College Dublin Dublin 2 Ireland

knowledge-based networking involves the forwarding of messages across a network based on semantics of the data and associated metadata of the message content. However such systems typically assume a common semantic model underpinning the routing which limits their ability to cope with heterogeneity. In contrast, the authors have developed a semantic-based publish/subscribe system that is unique in allowing several semantic models to support routing. This paper examines the content heterogeneity problem in a knowledge-based Network (KBN) implementation and evaluates a mechanism for efficiently and dynamically loading ontological mappings for use with distributed and heterogeneous knowledge-based applications. It compares a number of strategies that use pre-existing semantic mapping information stored in KBN routers. Evaluation results show that this mechanism can effectively solve the heterogeneity problem. © 2009 ACADEMY PUBLISHER.

关键词： Semantics

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Towards a modelization of the elusive concept of wisdom using fuzzy techniques

Towards a modelization of the elusive concept of wisdom usin...

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2012 Annual Meeting of the North American Fuzzy Information Processing Society, NAFIPS 2012

作者： Hoppe, Anett Tabacchi, Marco Data and Knowledge Engineering Group Faculty of Computer Science Otto-von-Guericke-University Germany Dipartimento di Matematica Ed Informatica Sezione di Informatica Università degli Studi di Palermo Italy

ISBN: (纸本)9781467323376

After having been a term of reflection in philosophy as well as psychology for ages, the fascination with human wisdom finally reaches the realms of computer science. In comparison to the first philosophical definition attempts, that date back to Aristotle (384BC - 322BC), the efforts in information science during the late 1980s seem quite recent. Nevertheless have there been astonishing new insights provided by cognitive science since those first formal modelizations were designed - findings that strongly suggest a reconsideration of our current formalization of wisdom in the computer science domain. We suggest to establish a new, integrated view on the concept of wisdom, using the insights of cognitive sciences. Furthermore, we discuss possible measures that are able to cover at least fundamental properties of wisdom including its vague aspects. © 2012 IEEE.

关键词： Philosophical aspects

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Agents deliberating over action proposals using the ProCLAIM model

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5th International Central and Eastern European Conference on Multi-Agent Systems

作者： Tolchinsky, Pancho Atkinson, Katie McBurney, Peter Modgil, Sanjay Cortes, Ulises Knowledge Engineering and Machine Learning Group Technical University of Catalonia Spain Department of Computer Science University of Liverpool Liverpool United Kingdom Advanced Computation Lab. Cancer Research UK

ISBN: (纸本)9783540752530

In this paper we propose a dialogue game for agents to deliberate over a proposed action. The agents' dialogue moves are defined by a structured set of argument schemes and critical questions (CQs). Thus, a dialogue move is an instantiated scheme (i.e. an argument) or a CQ (i.e. a challenge on the argument instantiated in the scheme). The proposed dialogue game formalises the protocol based exchange of arguments defined in the ProCLAIM model. This model provides a setting for agents to deliberate over whether, given the arguments for and against, a proposed action is justified or not.

关键词： Software agents

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Arabic Sentiment Analysis of Users’ Opinions of Governmental Mobile Applications

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computers, Materials & Continua 2022年第9期72卷 4675-4689页

作者： Mohammed Hadwan Mohammed A.Al-Hagery Mohammed Al-Sarem Faisal Saeed Department of Information Technology College of ComputerQassim UniversityBuraydah51452Saudi Arabia Department of Computer Science College of Applied SciencesTaiz UniversityTaizYemen Inteligent Analytic Group College of ComputerQassim UniversityBuraydah51452Saudi Arabia Department of Computer Science College of ComputerQassim UniversityBuraydah51452Saudi Arabia College of Computer Science and Engineering Taibah UniversityMedina42353Saudi Arabia Institute for Artificial Intelligence and Big Data Universiti Malaysia KelantanPengkalan ChepaKota Bharu16100KelantanMalaysia

Different types of pandemics that have appeared from time to time have changed many aspects of daily *** governments encourage their citizens to use certain applications to help control the spread of disease and to deliver other services during *** Saudi government has launched several mobile apps to control the pandemic and have made these apps available through Google Play and the app store.A huge number of reviews are written daily by users to express their opinions,which include significant information to improve these *** manual processing and extracting of information from users’reviews is an extremely difficult and time-consuming ***,the use of intelligent methods is necessary to analyse users’reviews and extract issues that can help in improving these *** research aims to support the efforts made by the Saudi government for its citizens and residents by analysing the opinions of people in Saudi Arabia that can be found as reviews on Google Play and the app store using sentiment analysis and machine learning *** the best of our knowledge,this is the first study to explore users’opinions about governmental apps in Saudi *** findings of this analysis will help government officers make the right decisions to improve the quality of the provided services and help application developers improve these applications by fixing potential issues that cannot be identified during application testing phases.A new dataset used for this research includes 8000 user reviews gathered from social media,Google Play and the app *** methods are applied to the dataset,and the results show that the k nearest neighbourhood(KNN)method generates the highest accuracy compared to other implemented methods.

关键词： Arabic sentiment analysis software quality user satisfaction improving online governmental services machine learning intelligent systems mobile app

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Towards Target-Dependent Sentiment Classification in News Articles 16th

Towards Target-Dependent Sentiment Classification in News Ar...

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16th International Conference on Diversity, Divergence, Dialogue, iConference 2021

作者： Hamborg, Felix Donnay, Karsten Gipp, Bela Department of Computer Science University of Konstanz Konstanz Germany Heidelberg Academy of Sciences and Humanities Heidelberg Germany Department of Political Science University of Zurich Zurich Switzerland Data and Knowledge Engineering University of Wuppertal Wuppertal Germany

ISBN: (纸本)9783030713041

Extensive research on target-dependent sentiment classification (TSC) has led to strong classification performances in domains where authors tend to explicitly express sentiment about specific entities or topics, such as in reviews or on social media. We investigate TSC in news articles, a much less researched domain, despite the importance of news as an essential information source in individual and societal decision making. This article introduces NewsTSC, a manually annotated dataset to explore TSC on news articles. Investigating characteristics of sentiment in news and contrasting them to popular TSC domains, we find that sentiment in the news is expressed less explicitly, is more dependent on context and readership, and requires a greater degree of interpretation. In an extensive evaluation, we find that the current state-of-the-art in TSC performs worse on news articles than on other domains (average recall AvgRec= 69.8 on NewsTSC compared to AvgRev= [75.6, 82.2 ] on established TSC datasets). Reasons include incorrectly resolved relation of target and sentiment-bearing phrases and off-context dependence. As a major improvement over previous news TSC, we find that BERT’s natural language understanding capabilities capture the less explicit sentiment used in news articles. © 2021, Springer Nature Switzerland AG.

关键词： Decision making

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Ubiquitous data

Ubiquitous data

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作者： Hotho, Andreas Pedersen, Rasmus Ulslev Wurst, Michael University Kassel Depart. of Electrical Engineering/Computer Science Knowledge and Data Engineering Group Germany Copenhagen Business School Dept. of Informatics Embedded Software Lab. Copenhagen Denmark Technical University Dortmund Computer Science LS8 44221 Dortmund Germany

ISBN: (纸本)3642163912

Ubiquitous knowledge discovery systems must be captured from many different perspectives. In earlier chapters, aspects like machine learning, underlying network technologies etc. were described. An essential component, which we shall discuss now, is still missing: Ubiquitous data. While data themselves are a central part of the knowledge discovery process, in a ubiquitous setting new challenges arise. In this context, the emergence of data itself plays a large role, therefore we label this part of KDubiq systems ubiquitous data. It clarifies the KDubiq challenges related to the multitude of available data and what we must do before we can tap into this rich information source. © 2010 Springer-Verlag.

关键词： Taps

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CoSimLex: A resource for evaluating graded word similarity in context 12

CoSimLex: A resource for evaluating graded word similarity i...

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12th International Conference on Language Resources and Evaluation, LREC 2020

作者： Armendariz, Carlos S. Purver, Matthew Ulcar, Matej Pollak, Senja Ljubešic, Nikola Robnik-Šikonja, Marko Granroth-Wilding, Mark Vaik, Kristiina Cognitive Science Research Group Queen Mary University of London London United Kingdom Department of Knowledge Technologies Jožef Stefan Institute Ljubljana Slovenia University of Ljubljana Faculty of Computer and Information Science Slovenia Department of Computer Science University of Helsinki Finland Department of Data Analysis Texta Estonia

ISBN: (纸本)9791095546344

State of the art natural language processing tools are built on context-dependent word embeddings, but no direct method for evaluating these representations currently exists. Standard tasks and datasets for intrinsic evaluation of embeddings are based on judgements of similarity, but ignore context;standard tasks for word sense disambiguation take account of context but do not provide continuous measures of meaning similarity. This paper describes an effort to build a new dataset, CoSimLex, intended to fill this gap. Building on the standard pairwise similarity task of SimLex-999, it provides context-dependent similarity measures;covers not only discrete differences in word sense but more subtle, graded changes in meaning;and covers not only a well-resourced language (English) but a number of less-resourced languages. We define the task and evaluation metrics, outline the dataset collection methodology, and describe the status of the dataset so far. © European Language Resources Association (ELRA), licensed under CC-BY-NC

关键词： Semantics

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Parallel SimRank computation on large graphs with iterative aggregation

Parallel SimRank computation on large graphs with iterative ...

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16th ACM SIGKDD International Conference on knowledge Discovery and data Mining, KDD-2010

作者： He, Guoming Feng, Haijun Li, Cuiping Chen, Hong Key Lab. of Data Engineering and Knowledge Engineering of Ministry of Education China Department of Computer Science Renmin University of China China No. 59 Zhongguancun Street Haidian District Beijing China

ISBN: (纸本)9781450300551

Recently there has been a lot of interest in graph-based analysis. One of the most important aspects of graph-based analysis is to measure similarity between nodes in a graph. SimRank is a simple and influential measure of this kind, based on a solid graph theoretical model. However, existing methods on SimRank computation suffer from two limitations: 1) the computing cost can be very high in practice;and 2) they can only be applied on static graphs. In this paper, we exploit the inherent parallelism and high memory bandwidth of graphics processing units (GPU) to accelerate the computation of SimRank on large graphs. Furthermore, based on the observation that SimRank is essentially a first-order Markov Chain, we propose to utilize the iterative aggregation techniques for uncoupling Markov chains to compute SimRank scores in parallel for large graphs. The iterative aggregation method can be applied on dynamic graphs. Moreover, it can handle not only the link-updating problem but also the node-updating problem. Extensive experiments on synthetic and real data sets verify that the proposed methods are efficient and effective. © 2010 ACM.

关键词： Graphics processing unit

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CNME: A system for Chinese news meta-data extraction 5th

CNME: A system for Chinese news meta-data extraction

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5th Joint International Conference on Semantic Technology, JIST 2015

作者： Xia, Junbo Xie, Fei Zhang, Mengdi Su, Yu Luan, Huanbo Knowledge Engineering Group Department of Computer Science and Technology Tsinghua University Beijing100084 China Communication Technology Bureau Xinhua News Agency Beijing100803 China

ISBN: (纸本)9783319316758

News mining has gained increasing attention because of the overwhelming news produced everyday. Lots of news portals such as Sina (http://***) and Chinanews (http://***. com) develop tools to manage the billions of news and provide services to meet all kinds of needs. News analysis applications conduct news mining work and reveal valuable information. What they all need is news metadata, the fundamental element to support news analysis work. To extract and maintain meta-data of news becomes an important and challenging task. In this paper, we present a system specialized for Chinese news metadata extraction. It can identify 28 kinds of meta-data and provides not only a pipeline to extract them but also a systematic way for management. It facilitates the organizing and conducting of news mining processes and improves efficiency by avoiding duplication of work. More specifically, it introduces an innovative way to categorize news based on words’ ability to represent category. It also adapts existing methods to extract keywords, entities and event elements. Integration of our system on news mining applications has proved its valuable contribution for news analysis work. © Springer International Publishing Switzerland 2016.

关键词： Metadata

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Resampling routine on heterogeneous networked-based environment

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Journal of the Indian Society of Remote Sensing 2002年第1-2期30卷 7-13页

作者： Gupta, P. Khanna, V. Onong, T. Rao, Thirunadha Dube, N. Dhar, D. Ramakrishnan, R. Majumder, K.L. Department of Computer Science and Engineering Indian Institute of Technology Kanpur - 208016 India Image Processing and Data Product Group Space Applications Centre Ahmedabad - 380 053 India

In this paper, we have described a model to parallelize the resampling routine, which is used in the geometric correction of data provided by remote sensing satellites. Our model is a typical master-slave model consisting of N machines termed as hosts out of which one is designated as the master. The input image data resides on the master. Processing of the input image data is done in parallel on the N machines. Issues related to load-balancing and various error conditions that may occur during execution like one of the machines going down have been studied and are incorporated in the model. It also provides the flexibility to add or delete the hosts during the execution of the resampling routine. The serial version of this routine involves huge amount of computations and takes substantial amount of time even for an image of 473 MB. We have implemented our model with the help of PVM which is most often used in distributed computing environment. Our approach has been tested for geometric correction on LISS-III 4 band data of size 473 MB. It is found that if one uses 2. 3 or 4 hosts the overall execution time is reduced by 33%, 42% and 49%, respectively.

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