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作者： Agmon, Noa Agrawal, Vikas Aha, David W. Aloimonos, Yiannis Buckley, Donagh Doshi, Prashant Geib, Christopher Grasso, Floriana Green, Nancy Johnston, Benjamin Kaliski, Burt Kiekintveld, Christopher Law, Edith Lieberman, Henry Mengshoel, Ole J. Metzler, Ted Modayil, Joseph Oard, Douglas W. Onder, Nilufer O'Sullivan, Barry Pastra, Katerina Precup, Doina Ramachandran, Sowmya Reed, Chris Sariel-Talay, Sanem Selker, Ted Shastri, Lokendra Singh, Satinder Smith, Stephen F. Srivastava, Siddharth Sukthankar, Gita Uthus, David C. Williams, Mary-Anne Department of Computer Science University of Texas at Austin United States Center for Knowledge Driven Information Systems Infosys Labs India Adaptive Systems Section Naval Research Laboratory Washington DC United States Department of Computer Science University of Maryland College Park United States EMC's Center of Excellence in Ireland Research Europe at EMC Ireland Department of Computer Science University of Georgia United States School of Informatics University of Edinburgh United Kingdom Department of Computer Science University of Liverpool United Kingdom Department of Computer Science University of North Carolina Greensboro United States Faculty of Engineering and Information Technology University of Technology Sydney Australia VeriSign Inc. United States Department of Computer Science University of Texas at El Paso United States Machine Learning Department Carnegie Mellon University United States Massachusetts Institute of Technology Media Laboratory United States Carnegie Mellon University's Silicon Valley Campus United States Darrell W. Hughes Program for Religion and Science Dialogue Oklahoma City University United States Department of Computing Science University of Alberta Canada College of Information Studies Institute for Advanced Computer Studies University of Maryland College Park United States Department of Computer Science Michigan Technological University United States Department of Computer Science University College Cork Ireland Cognitive Systems Research Insitute Athens Greece School of Computer Science McGill University Canada Stottler Henke Inc. United States School of Computing University of Dundee United Kingdom Department of Computer Engineering Istanbul Technical University Turkey Convergence Lab Infosys Technologies Ltd. United States Department of Electrical Engineering and Computer Science University of Michigan Ann Arbor United States Robotics Institute Carnegie Mellon University United States University of Wisconsin

The AAAI-11 workshop program was held Sunday and Monday, August 7-18, 2011, at the Hyatt Regency San Francisco in San Francisco, California USA. The AAAI-11 workshop program included 15 workshops covering a wide range of topics in artificial intelligence. The titles of the workshops were Activity Context Representation: Techniques and Languages;Analyzing Microtext;Applied Adversarial Reasoning and Risk Modeling;Artificial Intelligence and Smarter Living: The Conquest of Complexity;Artifiicial Intelligence for Data Center management and Cloud Computing;Automated Action Planning for Autonomous Mobile Robots;Computational Models of Natural Argument;Generalized Planning;Human Computation;Human-Robot Interaction in Elder Care;Interactive Decision Theory and Game Theory, 2010;Language-Action Tools for Cognitive Artificial Agents: Integrating Vision, Action, and Language;Lifelong Learning from Sensorimotor Experience;Plan, Activity, and Intent Recognition;and Scalable Integration of Analytics and Visualization. This article presents short summaries of those events. Copyright © 2012, Association for the Advancement of Artificial Intelligence. All rights reserved.

关键词： Human robot interaction

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Extracting ambiguous sessions from real traffic with intrusion prevention systems

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International Journal of Network Security 2012年第5期14卷 243-250页

作者： Chen, I-Wei Lin, Po-Ching Cheng, Tsung-Huan Luo, Chi-Chung Lin, Ying-Dar Lai, Yuan-Cheng Lin, Frank C. Network Benchmarking Lab National Chiao Tung University R611 MISRC Building No.1001 DaXue Rd Hsinchu City 300 Taiwan Department of Computer Science and Information Engineering National Chung Cheng University Chiayi Taiwan Department of Computer Science National Chiao Tung University Hsinchu Taiwan Department of Information and Management National Taiwan University of Science and Technology Taipei Taiwan San Jose State University San Jose CA United States

False Positives (FP) and False Negatives (FN) are com-mon in every Intrusion Prevention System (IPS). None of the systems could judge better than others all the time. This work proposes a system of Ambiguous Session Extraction (ASE) to create a pool of ambiguous traffic traces. Traffic traces or sessions are called "ambiguous", meaning they cause potential FNs (abbreviated as P-FNs) and potential FPs (abbreviated as P-FPs) to IPSes. IPS developers can use these ambiguous traffic traces to im-prove the accuracy of their products. The key objective here is to design the ASE system to extract the traces as complete and pure as possible, which gives IPS develop-ers resources for further analysis. First, the ASE captures real traffic and replays captured traffic traces to multiple IPSes. By comparing the logs of IPSes, we might find that some sessions are logged or not logged only at a cer-tain IPS. The former is P-FPs, while the latter is P-FNs to that IPS. The ASE then starts to extract ambiguous traffic from replayed traffic traces. IPS developers can fur-ther analyse the extracted traffic traces and confirm that some are FNs or FPs. To completely and purely extract an ambiguous session, the ASE uses an association mech-anism based on anchor packets, five tuples and time, and similarity for the first packet, first connection, and whole session, respectively. It calculates the degree of similarity among packets to extract an ambiguous session contain-ing multiple connections. We define variation and com-pleteness/purity as the indexes to evaluate the ASE. The experiments demonstrate that 95% of extracted sessions have low variation, and the average completeness/purity is around 80%. We also present two case studies, one is a P-FN and the other is a P-FP, found by the ASE and confirmed by the IPS developers to be an FN and an FP, respectively.

关键词： Extraction

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A trust model for capability delegation in federated policy systems

A trust model for capability delegation in federated policy ...

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6th International Conference on Risks and Security of Internet and Systems, CRiSIS 2011

作者： Feeney, Kevin Foley, Simon N. Brennan, Rob Intelligent Systems Lab Knowledge and Data Engineering Group Trinity College Dublin Ireland FAME Department of Computer Science University College Cork Ireland

ISBN: (纸本)9781457718915

Federated policy systems are required to support the emergent complexity and organizational heterogeneity of modern Internet service delivery. This paper presents a distributed policy management approach which utilizes a flexible, tree-based capability authority model to partition and delegate federated capabilities or services. A trust management model and a delegation logic is defined which supports secure decentralized policy reasoning and addresses performance overheads due to distributed rule evaluation, threats from malformed or malicious federated principals and allows flexibility with respect to delegation chain reduction or capability authority re-partitioning. The system is evaluated through a security analysis and a prototype implementation of a federated policy engineering framework based on this logic is described. This framework is based on public key certificates and an extension to the Keynote Trust management language. It provides practical management services such as key discovery and certificate revocation in addition to the core capability delegation function. © 2011 IEEE.

关键词： computer circuits

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Enhancing search results with semantic annotation using augmented browsing

Enhancing search results with semantic annotation using augm...

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22nd International Joint Conference on Artificial Intelligence, IJCAI 2011

作者： Dai, Hong-Jie Tsai, Wei-Chi Tsai, Richard Tzong-Han Hsu, Wen-Lian Department of Computer Science National Tsing-Hua University Taiwan Intelligent Agent Systems Lab. Institute of Information Science Academia Sinica Taiwan Department of Computer Science and Engineering Yuan Ze University Taiwan

ISBN: (纸本)9781577355120

In this paper, we describe how we integrated an artificial intelligence (AT) system into the PubMed search website using angmented browsing technology. Our system dynamically enriches the PubMed search results displayed in a user's browser with semantic annotation provided by several natural language processing (NLP) subsystems, including a sentence splitter, a part-of-speech tagger, a named entity recognizer, a section categorizer and a gene normalizer (GN). After our system is installed, the PubMed search results page is modified on the fly to categorize sections and provide additional information on gene and gene products identified by our NLP subsystems. In addition, GN involves three main steps: candidate ID matching, false positive filtering and disambiguation, which are highly dependent on each other. We propose a joint model using a Markov logic network (MLN) to model the dependencies found in GN. The experimental results show that our joint model outerforms a baseline system that executes the three steps separately. The developed system is available at https://***/site/pubmedannotationtool4ijcai/home.

关键词： Genes

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Improving stock market prediction by integrating both market news and stock prices

Improving stock market prediction by integrating both market...

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22nd International Conference on Database and Expert Systems Applications, DEXA 2011

作者： Li, Xiaodong Wang, Chao Dong, Jiawei Wang, Feng Deng, Xiaotie Zhu, Shanfeng Department of Computer Science City University Hong Kong Hong Kong Shanghai Key Lab of Intelligent Information Processing School of Computer Science Fudan University Shanghai 200433 China School of Computer State Key Lab of Software Engineering Wuhan University Wuhan 430072 China Department of Computer Science University of Liverpool Liverpool United Kingdom

ISBN: (纸本)9783642230905

Stock market is an important and active part of nowadays financial markets. Addressing the question as to how to model financial information from two sources, we focus on improving the accuracy of a computer aided prediction by combining information hidden in market news and stock prices in this study. Using the multi-kernel learning technique, a system is presented that makes predictions for the Hong Kong stock market by incorporating those two information sources. Experiments were conducted and the results have shown that in both cross validation and independent testing, our system has achieved better directional accuracy than those by the baseline system that is based on single one information source, as well as by the system that integrates information sources in a simple way. © 2011 Springer-Verlag Berlin Heidelberg.

关键词： Forecasting

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Mean first-passage time for random walks on undirected networks

Mean first-passage time for random walks on undirected netwo...

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作者： Zhang, Zhongzhi Julaiti, Alafate Hou, Baoyu Zhang, Hongjuan Chen, Guanrong School of Computer Science Fudan University Shanghai 200433 China Shanghai Key Lab of Intelligent Information Processing Fudan University Shanghai 200433 China Department of Mathematics College of Science Shanghai University Shanghai 200444 China Department of Electronic Engineering City University of Hong Kong Hong Kong Hong Kong

In this paper, by using two different techniques we derive an explicit formula for the mean first-passage time (MFPT) between any pair of nodes on a general undirected network, which is expressed in terms of eigenvalues and eigenvectors of an associated matrix similar to the transition matrix. We then apply the formula to derive a lower bound for the MFPT to arrive at a given node with the starting point chosen from the stationary distribution over the set of nodes. We show that for a correlated scale-free network of size N with a degree distribution P(d) ∼ d-γ, the scaling of the lower bound is N1-1/γ. Also, we provide a simple derivation for an eigentime identity. Our work leads to a comprehensive understanding of recent results about random walks on complex networks, especially on scale-free networks. © 2011 EDP sciences, SIF, Springer-Verlag Berlin Heidelberg.

关键词： Complex networks

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Entity Disambiguation Using a Markov-Logic Network 5

Entity Disambiguation Using a Markov-Logic Network

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5th International Joint Conference on Natural Language Processing, IJCNLP 2011

作者： Dai, Hong-Jie Tsai, Richard Tzong-Han Hsu, Wen-Lian Department of Computer Science National Tsing Hua University 300 No. 101 Section 2 Kuang-Fu Road Hsinchu Taiwan Intelligent Agent Systems Lab. Institute of Information Science Academia Sinica 128 Academia Road Sec.2 Nankang Taipei Taiwan Department of Computer Science and Engineering Yuan Ze University 135 Yuan-Tung Road Chungli Taoyuan Taiwan

ISBN: (纸本)9789744665645

Entity linking (EL) is the task of linking a textual named entity mention to a knowledge base entry. It is a difficult task involving many challenges, but the most crucial problem is entity ambiguity. Traditional EL approaches usually employ different constraints and filtering techniques to improve performance. However, these constraints are executed in several different stages and cannot be used interactively. In this paper, we propose several disambiguation formulae/features and employ a Markov logic network to model interweaved constraints found in one type of EL, gene mention linking. To assess our systems effectiveness in different applications, we adopt two evaluation schemes: article-wide and instance-based precision/recall/F-measure. Experimental results show that our system outperforms the baseline systems and state-of-the-art systems under both evaluation schemes. © 2011 AFNLP

关键词： computer circuits

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Color-mood-aware clothing re-texturing

Color-mood-aware clothing re-texturing

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12th International Conference on computer-Aided Design and computer Graphics, CAD/Graphics 2011

作者： Shen, Jianbing Sun, Hanqiu Mao, Xiaoyang Guo, Yanwen Jin, Xiaogang Beijing Laboratory of Intelligent Information Technology School of Computer Science Beijing Institute of Technology Beijing 100081 China Department of Computer Science and Engineering Chinese University of Hong Kong Hong Kong Hong Kong University of Yamanashi Japan National Key Lab. for Novel Software Technology Nanjing University China State Key Lab. of CAD and CG Zhejiang University Hangzhou 310027 China

ISBN: (纸本)9780769544977

In this paper, we present a novel color-mood-aware technique to re-texture clothing in a photograph. An efficient classification algorithm is developed to classify clothing textures using color mood scheme. To re-texture the clothing, our approach first computes the gradient maps for the cloth region to be replaced and then calculates the texture distortion coordinates on the projected cloth region according to the gradient maps. After the user selects a target clothing texture from the classified clothing texture database, the lighting and shading effects on the original photograph is transferred using the HSV color space. Experimental results show that the proposed approach successfully re-textures the clothes in photographs while preserving the geometry and lighting features. © 2011 IEEE.

关键词： Color

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Providing feedback on emotional experiences and decision making

Providing feedback on emotional experiences and decision mak...

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AFRICON Conference

作者： Jana Machajdik Julian Stöttinger Ester Danelova Martin Pongratz Lukas Kavicky Roberto Valenti Allan Hanbury Computer Vision Lab Vienna University of Technology Austria Dept. of Information Engineering and Computer Science University of Trento Italy Department of Psychology Masaryk University Institute of Computer Technology Vienna University of Technology Intelligent System Lab Amsterdam University of Amsterdam Information Retrieval Facility Vienna Austria

We present a novel lifelog system concept created to provide a human user with feedback on their conscious and unconscious emotional reactions and encourage the process of self-reflection by looking into an affective mirror. The emotion of the user is deduced from biometric data and enhanced by affective sound analysis and facial expression recognition of faces of the weares conversational partners. These high-level analyses also offer information about the social context of the user. All of the recorded data is processed using a novel modification of the spreading-activation theory which is used to model human-like associative thinking.

关键词： Humans Visualization Sensors Heart rate Skin Mirrors Biomedical measurements

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Reports of the AAAI 2010 fall symposia

Reports of the AAAI 2010 fall symposia

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作者： Azevedo, Roger Biswas, Gautam Bohus, Dan Carmichael, Ted Finlayson, Mark A. Hadzikadic, Mirsad Havasi, Catherine Horvitz, Eric Kanda, Takayuki Koyejo, Oluwasanmi Lawless, William F. Lenat, Doug Meneguzzi, Felipe Mutlu, Bilge Oh, Jean Pirrone, Roberto Raux, Antoine Sofge, Donald A. Sukthankar, Gita Van Durme, Benjamin Yorke-Smith, Neil Department of Educational and Counseling Psychology McGill University Canada Center for Intelligent Systems Vanderbilt University United States Microsoft Research Redmond United States Department of Software and Information Systems University of North Carolina Charlotte United States Complex Systems Institute United States Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology United States Media Lab. Massachusetts Institute of Technology United States ATR Intelligent Robotics and Communication Laboratories Kyoto Japan Department of Electrical and Computer Engineering University of Texas Austin United States Department of Mathematics Paine College Augusta GA United States Cycorp Austin TX United States Robotics Institute Carnegie Mellon University United States Department of Computer Sciences University of Wisconsin Madison United States University of Palermo Italy Honda Research Institute United States Navy Center for Applied Research in Artificial Intelligence Naval Research Laboratory Washington DC United States Department of Electrical Engineering and Computer Science University of Central Florida United States Department of Computer Science Johns Hopkins University United States American University of Beirut Lebanon SRI International's Artificial Intelligence Center United States

The Association for the Advancement of Artificial Intelligence (AAAI) presented the 2010 Fall Symposium Series on November 11-13, 2010. The eight symposia included Cognitive and Metacognitive Educational Systems, Commonsense knowledge, Complex Adaptive Systems: Resilience, Robustness, and Evolvability, Computational Models of Narrative, Dialog with Robots, Manifold Learning and Its Applications, Proactive Assistant Agents and Quantum Informatics for Cognitive, Social, and Semantic Processes. Cognitive and Metacognitive Educational Systems aimed to provide a comprehensive definition of metacognitive educational systems that is inclusive of the theoretical, architectural, and educational aspects of this field. The AAAI Commonsense knowledge Fall Symposium had the goal of bringing together the diverse elements of this community whose work benefits from or contributes to the representation of general knowledge about the world. One of the specific goals of Proactive symposium was to gather the researchers from various projects in assistant agents to share their wisdom in retrospect.

关键词： Semantics

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