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Initial explorations on using CRFs for turkish named entity recognition

Initial explorations on using CRFs for turkish named entity ...

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24th International Conference on Computational Linguistics, COLING 2012

作者： Şseker, Gökhan Akin Eryǐgit, Güļsen ITU Informatics Institute Graduate Program in Computer Science Istanbul Technical University Istanbul 34469 Turkey Department of Computer Engineering Istanbul Technical University Istanbul 34469 Turkey

This paper reports the highest results (95% in MUC and 92% in CoNLL metric) in the literature for Turkish named entity recognition;more specifically for the task of detecting person, location and organization entities in general news texts. We give an in depth analysis of the previous reported results and make comparisons with them whenever possible. We use conditional random fields (CRFs) as our statistical model. The paper presents initial explorations on the usage of rich morphological structure of the Turkish language as features to CRFs together with the use of some basic and generative gazetteers. © 2012 The COLING.

关键词： Random processes

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Feasibility study of using social networks platform for learning support: An example of Facebook

Feasibility study of using social networks platform for lear...

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20th International Conference on computers in Education, ICCE 2012

作者： Chan, Chien-Lung Fu, Wen-Erh Lai, K. Robert Tseng, Shu-Fen Department of Information Management Yuan Ze University Taiwan Department of Computer Science and Engineering Yuan Ze University Taiwan Graduate Program in Social Informatics Yuan Ze University Taiwan

ISBN: (纸本)9789810746490

In this study, we explored the students' computer-supported collaborative learning behavior based on the Facebook platform. Sixty two senior college students major in Information Management took Decision Support System (DSS) class. Besides the lectures and class discussion, the students participated in the DSS Facebook for collaborative learning. We found that students' characteristics (e.g., gender and mindset of learning) are important factors to affect their Facebook usage behavior and learning performance. The students using DSS Facebook more often get better performance in their final projects, learning satisfaction and the online communication behavior survey. We also found that gender affects the usage of social networks platform. For instance, male students use social networks platform several times per week and get better performance in online communication, learning satisfaction and creativity self-efficacy.

关键词： Decision support systems

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Using Hybrid Methods for Relevance Assessment in TREC Crowd'12 21

Using Hybrid Methods for Relevance Assessment in TREC Crowd'...

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21st Text REtrieval Conference, TREC 2012

作者： Harris, Christopher Srinivasan, Padmini Informatics Program The University of Iowa Iowa CityIA52242 United States Computer Science Department The University of Iowa Iowa CityIA52242 United States

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With a Little Help from the Crowd: Receiving Unauthorized Academic Assistance through Online Labor Markets

With a Little Help from the Crowd: Receiving Unauthorized Ac...

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IEEE International Conference on and IEEE International Confernece on Social Computing (SocialCom) Privacy, Security, Risk and Trust (PASSAT)

作者： Christopher G. Harris Padmini Srinivasan Informatics Program The University of Iowa Iowa City Iowa Informatics Program and Computer Science Department The University of Iowa Iowa City Iowa

Although a vast majority of crowd sourcing tasks are for ethical purposes, the anonymity and global reach of online labor markets also create a clearinghouse for unethical crowd sourcing tasks. Recent studies show a majority of students have engaged in academic dishonesty using the Internet, and a growing number find this behavior is acceptable. We conduct a study to see if crowd workers will provide solutions to exams and homework assignments, and knowingly permit these solutions to be used for this purpose. For those who don't agree, we examine if additional financial incentives can entice them. Our findings indicate most crowd workers are willing to permit the use of their work, however, for those that are unwilling, additional financial incentives have little effect on altering their decision.

关键词： Collaboration Educational institutions computer aided instruction Ethics IP networks Internet computer science

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Proposal and development of the Web services input validation model

Proposal and development of the Web services input validatio...

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IEEE Symposium on Network Operations and Management

作者： Rafael Bosse Brinhosa Carla Merkle Westphall Carlos Becker Westphall Post Graduation Program in Computer Science (PPGCC) Department of Informatics and Statistics (INE) Federal University of Santa Catarina Florianopolis Brazil

The SOA architecture primarily based on Web services is experiencing a steady adoption, although its growth was lower than expected when it was launched, mainly because of security related concerns. Web services inherited many well-known security problems of Web applications and brought new ones. Major data breaches today are consequences of bad input validation at the application level. This paper presents a way to implement an input validation model for Web services which can be used to prevent cross-site scripting and SQL injection through the use of predefined models which specify valid inputs. The proposed WSIVM (Web Services Input Validation Model) consists of an XML schema, an XML specification, and a module for performing input validation according to the schema. A case study showing the effectiveness and performance of this mechanism is also presented.

关键词： Security Service oriented architecture XML Simple object access protocol Standards

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A multivariate probabilistic method for comparing two clinical datasets 12

A multivariate probabilistic method for comparing two clinic...

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2nd ACM SIGHIT International Health informatics Symposium, IHI'12

作者： Sverchkov, Yuriy Visweswaran, Shyam Clermont, Gilles Hauskrecht, Milos Cooper, Gregory F. Intelligent Systems Program University of Pittsburgh Pittsburgh PA 15260 United States Department of Biomedical Informatics University of Pittsburgh Pittsburgh PA 15260 United States Department of Computer Science University of Pittsburgh Pittsburgh PA 15260 United States Department of Critical Care Medicine University of Pittsburgh Pittsburgh PA 15260 United States

ISBN: (纸本)9781450307819

We present a novel method for obtaining a concise and mathematically grounded description of multivariate differences between a pair of clinical datasets. Often data collected under similar circumstances reect fundamentally different patterns. For example, information about patients undergoing similar treatments in different intensive care units (ICUs), or within the same ICU during different periods, may show systematically different outcomes. In such circumstances, the multivariate probability distributions induced by the datasets would differ in selected ways. To capture the probabilistic relationships, we learn a Bayesian network (BN) from the union of the two datasets. We include an indicator variable that represents the dataset from which a given patient record is obtained. We then extract the relevant conditional distributions from the network by finding the conditional probabilities that differ most when condi- tioning on the indicator variable. Our work is a form of explanation that bears some similarity to previous work on BN explanation;however, while previous work has mostly focused on justifying inference, our work is aimed at explaining multivariate differences between distributions. Copyright © 2012 ACM.

关键词： Bayesian networks

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Reports of the AAAI 2011 conference workshops

Reports of the AAAI 2011 conference workshops

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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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Non parametric cell nuclei segmentation based on a tracking over depth from 3D fluorescence confocal images

Non parametric cell nuclei segmentation based on a tracking ...

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IEEE International Symposium on Biomedical Imaging

作者： Thierry Pécot Shantanu Singh Enrico Caserta Kun Huang Raghu Machiraju Gustavo Leone Human Cancer Genetics Program Computer Science and Engineering Ohio State University Columbus OH USA Biomedical Informatics Ohio State University Columbus OH USA Computer Science and Engineering Ohio State University Columbus OH USA Human Cancer Genetics Program Department of Molecular Genetics Ohio State University Columbus OH USA

3D cell nuclei segmentation from fluorescence microscopy images is a key application in many biological studies. We propose a new, fully automated and non parametric method that takes advantage of the resolution anisotropy in fluorescence microscopy. The cell nuclei are first detected in 2D at each image plane and then tracked over depth through a graph based decision to recover their 3D profiles. As the tracking fails to separate very close cell nuclei along depth, we also propose a corrective step based on an intensity projection criterion. Experimental results on real data demonstrate the efficacy of the proposed method.

关键词： Image resolution Image segmentation Microscopy Histograms Biology Robustness Entropy

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Code Compression in ARM Embedded Systems Using Multiple Dictionaries

Code Compression in ARM Embedded Systems Using Multiple Dict...

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IEEE International Conference on Computational science and Engineering, CSE

作者： Wanderson Roger Azevedo Dias Edward David Moreno Institute of Computing-IComp Post-graduate Program in Informatics-PPGI Federal University of Amazonas Manaus Amazonas Brazil Center for Exact Sciences and Technology-CCET Department of Computer Science-DComp Federal University of Sergipe Aracaju Sergipe Brazil

This paper presents a new code compression method where we use different dictionaries, all of them are based in traditional Huffman algorithm. Our method reduces code size by up to 34.5% (including all extra costs) and presents an improvement of almost 7% over the traditional Huffman method. We performed simulations using Simple Scalar and analyzes using the applications from benchmark MiBench and use the embedded processor ARM.

关键词： Dictionaries Embedded systems Analytical models Benchmark testing Memory management Decoding Energy consumption

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The university of iowa at TREC 2011: Microblogs, medical records and crowdsourcing

The university of iowa at TREC 2011: Microblogs, medical rec...

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20th Text REtrieval Conference, TREC 2011

作者： Bhattacharya, Sanmitra Harris, Christopher G. Mejova, Yelena Yang, Chao Srinivasan, Padmini Computer Science Department University of Iowa IA United States Informatics Program University of Iowa IA United States

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