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 relate...
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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.
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 problem...
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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.
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 methodo...
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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 info...
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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 th...
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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.
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 networ...
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This work addresses the instability in asynchronous data parallel optimization. It does so by introducing a novel distributed optimizer which is able to efficiently optimize a centralized model under communication con...
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We consider k mobile agents initially located at distinct nodes of an undirected graph (on n nodes, with edge lengths). The agents have to deliver a single item from a given source node s to a given target node t. The...
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Nowadays, people need to work hard to afford their life and this results in people to live under the stress of the modern life style. This pressure of the modern life style might cause problems and accidents, for exam...
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Agents in reinforcement learning tasks may learn slowly in large or complex tasks - transfer learning is one technique to speed up learning by providing an informative prior. How to best enable transfer between tasks ...
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