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Sentiment propagation via implicature constraints

Sentiment propagation via implicature constraints

引用

14th Conference of the European Chapter of the Association for Computational Linguistics 2014, EACL 2014

作者： Deng, Lingjia Wiebe, Janyce Intelligent Systems Program University of Pittsburgh United States Department of Computer Science University of Pittsburgh United States

ISBN: (纸本)9781632663962

Opinions may be expressed implicitly via inference over explicit sentiments and events that positively/negatively affect entities (goodFor/badFor events). We investigate how such inferences may be exploited to improve sentiment analysis, given goodFor/badFor event information. We apply Loopy Belief Propagation to propagate sentiments among entities. The graph-based model improves over explicit sentiment classification by 10 points in precision and, in an evaluation of the model itself, we find it has an 89% chance of propagating sentiments correctly. © 2014 Association for Computational Linguistics.

关键词： Sentiment analysis

来源：评论

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A Conceptual Framework for Inferring Implicatures 5

A Conceptual Framework for Inferring Implicatures

引用

5th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis, WASSA 2014 at the 52nd Annual Meeting of the Association for Computational Linguistics, ACL 2014

作者： Wiebe, Janyce Deng, Lingjia Department of Computer Science University of Pittsburgh United States Intelligent Systems Program University of Pittsburgh United States

ISBN: (纸本)9781941643112

While previous sentiment analysis research has concentrated on the interpretation of explicitly stated opinions and attitudes, this work addresses a type of opinion implicature (i.e., opinion-oriented default inference) in real-world text. This work describes a rule-based conceptual framework for representing and analyzing opinion implicatures. In the course of understanding implicatures, the system recognizes implicit sentiments (and beliefs) toward various events and entities in the sentence, often of mixed polarities;thus, it produces a richer interpretation than is typical in opinion analysis. © 2014 Proceedings of the Annual Meeting of the Association for Computational Linguistics. All rights reserved.

关键词： Sentiment analysis

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An Investigation for Implicatures in Chinese : Implicatures in Chinese and in English are similar ! 5

An Investigation for Implicatures in Chinese : Implicatures ...

引用

5th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis, WASSA 2014 at the 52nd Annual Meeting of the Association for Computational Linguistics, ACL 2014

作者： Deng, Lingjia Wiebe, Janyce Intelligent Systems Program University of Pittsburgh United States Department of Computer Science University of Pittsburgh United States

ISBN: (纸本)9781941643112

Implicit opinions are commonly seen in opinion-oriented documents, such as political editorials. Previous work have utilized opinion inference rules to detect implicit opinions evoked by events that positively/negatively affect entities (good- For/badFor) to improve sentiment analysis for English text. Since people in different languages may express implicit opinions in different ways, in this work we investigate implicit opinions expressed via goodFor/badFor events in Chinese. The positive results have provided evidences that such implicit opinions and inference rules are similar in Chinese and in English. Moreover, we have observed cases where the inferences are blocked. © 2014 Proceedings of the Annual Meeting of the Association for Computational Linguistics. All rights reserved.

关键词： Sentiment analysis

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An optimization-based framework to learn conditional random fields for multi-label classification 14

An optimization-based framework to learn conditional random ...

引用

14th SIAM International Conference on Data Mining, SDM 2014

作者： Naeini, Mahdi Pakdaman Batal, Iyad Liu, Zitao Hong, Charmgil Hauskrecht, Milos Intelligent Systems Program University of Pittsburgh United States General Electric Global Research Center United States Department of Computer Science University of Pittsburgh United States

ISBN: (纸本)9781510811515

This paper studies multi-label classification problem in which data instances are associated with multiple, possibly high-dimensional, label vectors. This problem is especially challenging when labels are dependent and one cannot decompose the problem into a set of independent classification problems. To address the problem and properly represent label dependencies we propose and study a pairwise conditional random Field (CRF) model. We develop a new approach for learning the structure and parameters of the CRF from data. The approach maximizes the pseudo likelihood of observed labels and relies on the fast proximal gradient descend for learning the structure and limited memory BFGS for learning the parameters of the model. Empirical results on several datasets show that our approach outperforms several multi-label classification baselines, including recently published state-of-the-art methods. Copyright © SIAM.

关键词： Random processes

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Designing engaging camera based mobile games for implicit heart rate monitoring

Designing engaging camera based mobile games for implicit he...

引用

32nd Annual ACM Conference on Human Factors in Computing systems, CHI EA 2014

作者： Han, Teng Canny, John Shi, Lanfei Wang, Jingtao Xiao, Xiang Intelligent Systems Program University of Pittsburgh Pittsburgh PA 15260 United States Computer Science Division UC Berkeley Berkeley CA 94720 United States Computer Science University of Pittsburgh Pittsburgh PA 15260 United States

ISBN: (纸本)9781450324748

Heart rate monitoring is widely used in clinical care, fitness training, and stress management. However, tracking individuals' heart rate faces two major challenges, namely equipment availability and user motivation. In this paper, we present a novel technique, LivePulse Games (LPG), to measure users' heart rate in real time by having them play casual games on unmodified mobile phones. With LPG, heart rate is calculated by detecting changes in transparency of users' fingertips via a mobile device's built-in camera. More importantly, LPG integrate users' camera lens covering actions as an essential control mechanism for game play, and detect heart rate implicitly from intermittent lens covering actions. We explore the design space and trade-offs of LPG through three rounds of interactive design and report the preliminary results from a 12-subject user study.

关键词： Serious games

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An empirical evaluation of costs and benefits of simplifying Bayesian networks by removing weak arcs 27

An empirical evaluation of costs and benefits of simplifying...

引用

27th International Florida Artificial Intelligence Research Society Conference, FLAIRS 2014

作者： Ratnapinda, Parot Druzdzel, Marek J. Decision Systems Laboratory School of Information Sciences and Intelligent Systems Program University of Pittsburgh PittsburghPA15260 United States Faculty of Computer Science Bialystok University of Technology Wiejska 45A Bialystok15-351 Poland

We report the results of an empirical evaluation of structural simplification of Bayesian networks by removing weak arcs. We conduct a series of experiments on six networks built from real data sets selected from the UC Irvine Machine Learning Repository. We systematically remove arcs from the weakest to the strongest, relying on four measures of arc strength, and measure the classification accuracy of the resulting simplified models. Our results show that removing up to roughly 20 percent of the weakest arcs in a network has minimal effect on its classification accuracy. At the same time, structural simplification of networks leads to significant reduction of both the amount of memory taken by the clique tree and the amount of computation needed to perform inference. Copyright © 2014, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Bayesian networks

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Integrating knowledge tracing and item response theory: A tale of two frameworks 22

Integrating knowledge tracing and item response theory: A ta...

引用

Workshop of the 22nd Conference on User Modeling, Adaptation, and Personalization, UMAP 2014 - Co-located with the 22nd Conference on User Modeling, Adaptation, and Personalization, UMAP 2014

作者： Khajah, Mohammad M. Huang, Yun González-Brenes, José P. Mozer, Michael C. Brusilovsky, Peter Department of Computer Science Institute of Cognitive Science University of Colorado BoulderCO80309-0430 United States Intelligent Systems Program University of Pittsburgh PittsburghPA15260 United States Digital Data Analytics and Adaptive Learning Pearson Research and Innovation Network PhiladelphiaPA19103 United States

Traditionally, the assessment and learning science commu-nities rely on different paradigms to model student performance. The assessment community uses Item Response Theory which allows modeling different student abilities and problem difficulties, while the learning science community uses Knowledge Tracing, which captures skill acquisition. These two paradigms are complementary - IRT cannot be used to model student learning, while Knowledge Tracing assumes all students and problems are the same. Recently, two highly related models based on a principled synthesis of IRT and Knowledge Tracing were introduced. However, these two models were evaluated on different data sets, using different evaluation metrics and with different ways of splitting the data into training and testing sets. In this paper we reconcile the models' results by presenting a unified view of the two models, and by evaluating the models under a common evaluation metric. We find that both models are equivalent and only differ in their training procedure. Our results show that the combined IRT and Knowledge Tracing models offer the best of assessment and learning sciences - high prediction accuracy like the IRT model, and the ability to model student learning like Knowledge Tracing.

关键词： Students

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The bregman variational dual-tree framework

The bregman variational dual-tree framework

引用

29th Conference on Uncertainty in Artificial Intelligence, UAI 2013

作者： Amizadeh, Saeed Thiesson, Bo Hauskrecht, Milos Intelligent Systems Program University of Pittsburgh Pittsburgh PA 15213 United States Department of Computer Science Aalborg University Aalborg Denmark Department of Computer Science University of Pittsburgh Pittsburgh PA 15213 United States

Graph-based methods provide a powerful tool set for many non-parametric frameworks in Machine Learning. In general, the memory and computational complexity of these methods is quadratic in the number of examples in the data which makes them quickly in-feasible for moderate to large scale datasets. A significant effort to find more efficient solutions to the problem has been made in the literature. One of the state-of-the-art methods that has been recently introduced is the Variational Dual-Tree (VDT) framework. Despite some of its unique features, VDT is currently restricted only to Euclidean spaces where the Euclidean distance quantifies the similarity. In this paper, we extend the VDT framework beyond the Euclidean distance to more general Bregman divergences that include the Euclidean distance as a special case. By exploiting the properties of the general Bregman divergence, we show how the new framework can maintain all the pivotal features of the VDT framework and yet significantly improve its performance in non-Euclidean domains. We apply the proposed framework to different text categorization problems and demonstrate its benefits over the original VDT.

关键词： Graphic methods

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Implementation of Rössler chaotic system through inherent exponential nonlinearity of a diode with two-channel chaotic synchronization applications

Implementation of Rössler chaotic system through inherent e...

引用

International Conference on intelligent Control and Information Processing (ICICIP)

作者： S. Larptwee W. San-Um Engineering Program and Basic Science Department Faculty of Engineering Thai-Nichi Institute of Technology Thailand Intelligent Electronic Systems Research laboratory and Computer Engineering Department Faculty of Engineering Thai-Nichi Institute of Technology Bangkok Thailand

ISBN: (纸本)9781467362481

This paper presents a new Rössler chaotic system using exponential nonlinearity and its application to two-channel synchronization. The proposed chaotic system exhibits a chaotic attractor that resembles the original Rössler system with only six-term in three-dimensional ordinary equation systems using the exponential nonlinearity. Chaotic dynamics are described in terms of equilibria, Jacobian matrix, time domain waveforms, chaotic attractors, and bifurcation diagram. The circuit implementation is relatively compact and simple sine the exponential nonlinearity can be achieved by an inherent nonlinearity of single diode. An application to a two-channel secure communication are also demonstrated, showing a fast, low-error and robust synchronization processes.

关键词： Chaotic communication Synchronization Equations Transmitters Receivers Mathematical model

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A spectral learning approach to knowledge tracing 6

A spectral learning approach to knowledge tracing

引用

6th International Conference on Educational Data Mining, EDM 2013

作者： Falakmasir, Mohammad H. Pardos, Zachary A. Gordon, Geoffrey J. Brusilovsky, Peter Intelligent Systems Program University of Pittsburgh 210 South Bouquet Street PittsburghPA United States Computer Science AI Lab Massachusetts Institute of Technology 77 Massachusetts Ave CambridgeMA02139 United States Machine Learning Department Carnegie Mellon University 5000 Forbes Avenue PittsburghPA15213 United States School of Information Sciences University of Pittsburgh 135 North Bellefield Ave. PittsburghPA15260 United States

ISBN: (纸本)9780983952527

Bayesian Knowledge Tracing (BKT) is a common way of determining student knowledge of skills in adaptive educational systems and cognitive tutors. The basic BKT is a Hidden Markov Model (HMM) that models student knowledge based on five parameters: prior, learn rate, forget, guess, and slip. Expectation Maximization (EM) is often used to learn these parameters from training data. However, EM is a time-consuming process, and is prone to converging to erroneous, implausible local optima depending on the initial values of the BKT parameters. In this paper we address these two problems by using spectral learning to learn a Predictive State Representation (PSR) that represents the BKT HMM. We then use a heuristic to extract the BKT parameters from the learned PSR using basic matrix operations. The spectral learning method is based on an approximate factorization of the estimated covariance of windows from students’ sequences of correct and incorrect responses;it is fast, local-optimum-free, and statistically consistent. In the past few years, spectral techniques have been used on real-world problems involving latent variables in dynamical systems, computer vision, and natural language processing. Our results suggest that the parameters learned by the spectral algorithm can replace the parameters learned by EM;the results of our study show that the spectral algorithm can improve knowledge tracing parameter-fitting time significantly while maintaining the same prediction accuracy, or help to improve accuracy while still keeping parameter-fitting time equivalent to EM. © 2013 International Educational Data Mining Society. All rights reserved.

关键词： Students

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