ppxscal/embedding_network huggingface dataset:
Emerging Technologies of Text Mining: Techniques and Applications
Authors: Hercules Antonio Do Prado, Edilson Ferneda
Venue:  (2007)

Massive amounts of textual data make up most organizations stored information. Therefore, there is increasingly high demand for a comprehensive resource providing practical hands-on knowledge for real-world applications. Emerging Technologies of Text Mining: Techniques and Applications provides the most recent technical information related to the computational models of the text mining process, discussing techniques within the realms of classification, association analysis, information extraction, and clustering. Offering an innovative approach to the utilization of textual information mining to maximize competitive advantage, Emerging Technologies of Text Mining: Techniques and Applications will provide libraries with the defining reference on this topic.
Spatially Smooth Subspace Face Recognition Using LOG and DOG Penalties
Authors: Wangmeng Zuo, Lei Liu, Kuanquan Wang, David Zhang
Venue: Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part III (2009)

Subspace face recognition methods have been widely investigated in the last few decades. Since the pixels of an image are spatially correlated and facial images are generally considered to be spatially smoothing, several spatially smooth subspace methods have been proposed for face recognition. In this paper, we first survey the progress and problems in current spatially smooth subspace face recognition methods. Using the penalized subspace learning framework, we then proposed two novel penalty functions, Laplacian of Gaussian (LOG) and Derivative of Gaussian (DOG), for subspace face recognition. LOG and DOG penalties introduce a scale parameter, and thus are more flexible in controlling the degree of smoothness. Experimental results indicate that the proposed methods are effective for face recognition, and achieve higher recognition accuracy than the original subspace methods.
Motion vector processing using bidirectional frame difference in motion compensated frame interpolation
Authors: Ai-Mei Huang, Truong Nguyen
Venue: Proceedings of the 2008 International Symposium on a World of Wireless, Mobile and Multimedia Networks (2008)

In this paper, we address the potential issues in bidirectional motion compensated frame interpolation when the received motion vector field is directly used. Based on this motion vector analysis, we therefore propose using bidirectional motion vector processing method to eliminate the ghost artifacts around the moving objects. The artifacts caused by large motion vector magnitude can be effectively removed by correcting motion vectors bidirectionally. Moreover, since the proposed motion vector selection process chooses the best motion vector from adjacent motion vectors, the computational complexity can be greatly reduced comparing to motion estimation. We also demonstrate how to obtain clearer object edges by allowing displacement adjustment during the bidirectional motion vector processing. Experimental results show that the proposed algorithm outperforms other methods in terms of visual quality.
Designing explanation-oriented languages
Authors: Eric Walkingshaw
Venue: Proceedings of the 2008 IEEE Symposium on Visual Languages and Human-Centric Computing (2008)

We are developing a new paradigm of explanation-oriented languages whose objective is not only to describe the computation of values, but also to provide explanations of how and why those values are obtained. We have begun exploring this approach in the design of a visual notation for strategies in game theory. We plan to apply these ideas to other domains of public interest to both benefit those domains and to expand and solidify the theory behind explanation-oriented design.
A Model for Describing and Annotating Documents
Authors: Nicolas Dessaigne, José Martinez
Venue: Proceeding of the 2006 conference on Information Modelling and Knowledge Bases XVII (2006)

This paper introduces a model designed to describe and annotate documents. This model is mostly indebted to the standard Entity-Relationship approach and the ODMG data model, plus it has specific features related to information evolution and flexibility requirements. It has not been implemented as a brand new environment but mapped to existing ones. Realational database management systems have been chosen as target implementation in order to respond to scalability demands.
Proximal regularization for online and batch learning
Authors: Chuong B. Do, Quoc V. Le, Chuan-Sheng Foo
Venue: Proceedings of the 26th Annual International Conference on Machine Learning (2009)

Many learning algorithms rely on the curvature (in particular, strong convexity) of regularized objective functions to provide good theoretical performance guarantees. In practice, the choice of regularization penalty that gives the best testing set performance may result in objective functions with little or even no curvature. In these cases, algorithms designed specifically for regularized objectives often either fail completely or require some modification that involves a substantial compromise in performance. We present new online and batch algorithms for training a variety of supervised learning models (such as SVMs, logistic regression, structured prediction models, and CRFs) under conditions where the optimal choice of regularization parameter results in functions with low curvature. We employ a technique called proximal regularization, in which we solve the original learning problem via a sequence of modified optimization tasks whose objectives are chosen to have greater curvature than the original problem. Theoretically, our algorithms achieve low regret bounds in the online setting and fast convergence in the batch setting. Experimentally, our algorithms improve upon state-of-the-art techniques, including Pegasos and bundle methods, on medium and large-scale SVM and structured learning tasks.
Joint trajectory tracking and recognition based on bi-directional nonlinear learning
Authors: Zhaohua Hu, Xin Fan, Yaoliang Song, Dequn Liang
Venue: Image and Vision Computing (2009)

Motion trajectory is one of the most important cues for tracking and behavior recognition and can be widely applied to numerous fields. However, it is a difficult problem to directly model the spatio-temporal variations of trajectories due to their high dimensionality and nonlinearity. In this paper, we propose a joint trajectory tracking and recognition algorithm by combining a generative model derived from a bi-directional deep neural network (called ''autoencoder'') into a Bayesian estimation framework. The ''autoencoder'' network embeds high-dimensional trajectories into a two-dimensional plane based on a peculiar training rule and learns a trajectory generative model by its inverse mapping. A set of plausible trajectories can be generated by the trajectory generative model. In the tracking process, the samples from the plausible trajectory set are weighted by a mixed likelihood and are resampled to obtain the target state estimation at each time step in spirit of the particle filtering. The trajectory identity is inferred by evaluating the improved Hausdorff distance between the estimated trajectory up to now and the truncated reference trajectories. Moreover, the trajectory recognition results are also used to guide the trajectory tracking for the next time. The experiments on tracking and recognizing handwritten digits show that the proposed approach can achieve both robust tracking and exact recognition in background clutter and partial occlusion.
Software Process Maturity and the Success of Free Software Projects
Authors: Martin Michlmayr
Venue: Proceeding of the 2005 conference on Software Engineering: Evolution and Emerging Technologies (2005)

The success of free software and open source projects has increased interest in utilizing the open source model for mature software development. However, the ad hoc nature of open source development may result in poor quality software or failures for a number of volunteer projects. In this paper, projects from SourceForge are assessed to test the hypothesis that there is a relationship between process maturity and the success of free software and open source projects. This study addresses the question of whether the maturity of particular software processes differs in successful and unsuccessful projects. Processes are identified that are key factors in successful free software projects. The insights gained from this study can be applied as to improve the software process used by free software projects.
Children designing together on a multi-touch tabletop: an analysis of spatial orientation and user interactions
Authors: Jochen Rick, Amanda Harris, Paul Marshall, Rowanne Fleck, Nicola Yuill, Yvonne Rogers
Venue: Proceedings of the 8th International Conference on Interaction Design and Children (2009)

Applications running on multi-touch tabletops are beginning to be developed to enable children to collaborate on a variety of activities, from photo sharing to playing games. However, little is know as to how children work together on such interactive surfaces. We present a study that investigated groups of children's use of a multitouch tabletop for a shared-space design task, requiring reasoning and compromise. The OurSpace application was designed to allow children to arrange the desks in their classroom and allocate students to seats around those desks. A number of findings are reported, including a comparison of single versus multiple touch, equity of participation, and an analysis of how a child's tabletop position affects where he or she touches. A main finding was that children used all of the tabletop surface, but took more responsibility for the parts of the design closer to their relative position.
A sensor middleware and agent-based communication platform for supply-chain management
Authors: Klaas Thoelen, Sam Michiels, Wouter Joosen, Koen Vangheluwe, Katja Verbeeck
Venue: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2 (2009)

We present a supply-chain management system that supports transportation of cargo containers and monitors the quality of control during transport. Our system primarily focuses on the non-trivial challenges related to the interoperability between supply chain actors and their respective WSNs. It was developed by combining an end-to-end WSN middleware with an agent-based communication platform. The overall goal of the system is to offer different actors in the supply chain an easy way of handling services and continuous monitoring traces of containers along their path.
Multifaceted Outcome of Collaborative Learning: Call for Divergent Evaluation
Authors: Naomi Miyake
Venue: Proceeding of the 2005 conference on Towards Sustainable and Scalable Educational Innovations Informed by the Learning Sciences: Sharing Good Practices of Research, Experimentation and Innovation (2005)

Collaborative learning is a complex process with the potential to yield a variety of positive outcomes, particularly when supported by rich, well-designed uses of technology. The students are expected to learn not just the in-depth contents but also their integration through collaborative learning experiences. In addition, many collaborative learning practices expect the students to gain learning skills as well. These three different learning outcomes are compared in detail in this paper for three successful students observed in a highly collaborative, technology-supported college class. The comparison reveals that each acquired knowledge and skills in a unique way in addition to their basic learning. One student developed a solid, balanced understanding of all the learning materials, another integrated his choice of materials to attain insights into the topic of the class, and another student was very successful in strengthening a learning skill. This multifaceted pattern of outcomes reveals the richness of successful collaborative learning and compels us to explore divergent evaluation methods in learning-science research.
Supervised learning from multiple experts: whom to trust when everyone lies a bit
Authors: Vikas C. Raykar, Shipeng Yu, Linda H. Zhao, Anna Jerebko, Charles Florin, Gerardo Hermosillo Valadez, Luca Bogoni, Linda Moy
Venue: Proceedings of the 26th Annual International Conference on Machine Learning (2009)

We describe a probabilistic approach for supervised learning when we have multiple experts/annotators providing (possibly noisy) labels but no absolute gold standard. The proposed algorithm evaluates the different experts and also gives an estimate of the actual hidden labels. Experimental results indicate that the proposed method is superior to the commonly used majority voting baseline.
Introduction to the bio-entity recognition task at JNLPBA
Authors: Jin-Dong Kim, Tomoko Ohta, Yoshimasa Tsuruoka, Yuka Tateisi, Nigel Collier
Venue: Proceedings of the International Joint Workshop on Natural Language Processing in Biomedicine and its Applications (2004)

We describe here the JNLPBA shared task of bio-entity recognition using an extended version of the GENIA version 3 named entity corpus of MEDLINE abstracts. We provide background information on the task and present a general discussion of the approaches taken by participating systems.
Macworld Digital Photography Superguide Book - Second Edition, 2nd edition
Venue:  (2007)

Take Home a Photography Expert Nobody spends more time with Apple's computers and software than the writers and editors at Macworld, the world's foremost Mac authority in print and on the Web. Every year Macworld publishes huge amounts of photo-related advice including tips for shooting, managing, editing, and printing digital photos. Now this wealth of information is available all in one place, updated for iPhoto '08 and organized in an easy-to-follow guide. The Digital Photography Superguide is bursting with the latest insight and advice for every aspect of digital photography on the Mac. If you're shopping for a new camera, you'll find useful advice about picking the right one for your needs. Once you have a camera, this book will help you take better pictures with shooting tips and tricks from professional photographers. As your photo collection grows use this book to stay organized and to help bring out the best in your photos with iPhoto '08, Apple's excellent photo manager and editor. We've also got tips to help you print your pictures yourself, scan old negatives and slide, get the best results from an online photo service, and have fun with your photos with unusual photo projects, Web galleries, and more. You'll also learn the best ways to back up your photos so you don't ever lose precious memories. If you love using your Mac and your digital camera, this is the book for you. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
The equivalence of two graph polynomials and a symmetric function
Authors: Criel Merino, Steven d. Noble
Venue: Combinatorics, Probability and Computing (2009)

The U-polynomial, the polychromate and the symmetric function generalization of the Tutte polynomial, due to Stanley, are known to be equivalent in the sense that the coefficients of any one of them can be obtained as a function of the coefficients of any other. The definition of each of these functions suggests a natural way in which to strengthen them, which also captures Tutte's universal V-function as a specialization. We show that the equivalence remains true for the strong functions, thus answering a question raised by Dominic Welsh.
External monitoring of endpoint configuration compliance
Authors: Darrell M. Kienzle, Ryan K. Persaud, Matthew C. Elder
Venue: Proceedings of the 5th Annual Workshop on Cyber Security and Information Intelligence Research: Cyber Security and Information Intelligence Challenges and Strategies (2009)

We describe a system for externally monitoring endpoint configuration compliance of an end user system that provides a high assurance monitoring function and data. Typical approaches to monitoring for endpoint configuration compliance rely on the integrity of the endpoint's operating system and do not protect the monitoring function from subversion or spoofing by threats from within the monitored system. Our approach utilizes (1) a virtual machine architecture on the endpoint system to protect the monitoring function and (2) virtual machine introspection of the end user's environment. In this paper we describe our approach to external monitoring of endpoint configuration compliance, present the technical details of our monitoring system, and discuss some of the issues associated with external monitoring.
About Application and Implementation of Semantic Meta Parsing
Authors: Gregers Koch
Venue: Proceeding of the 2005 conference on New Trends in Software Methodologies, Tools and Techniques: Proceedings of the fourth SoMeT_W05 (2005)

This paper contains a description of our method of semantic meta parsing, and the method is implemented as a Prolog program. For comparison, we present briefly Johnson and Kay's method of semantic abstraction [9]. The two methods are compared by application on a sample problem from Hans Kamp's Discourse Representation Theory (DRT) [10].
Connecting the social and technical aspects of computing with visualization
Authors: Erik H. Trainer
Venue: Proceedings of the 2008 IEEE Symposium on Visual Languages and Human-Centric Computing (2008)

Our work has studied software developers with traditional backgrounds in distributed settings. In the future, projects will involve even more diverse sets of individuals, especially if the goal is to eventually include end-users in the development process. However, there exists a computational, and necessarily economic, divide. End-users come from different disciplines and socio-economic backgrounds. As such, they have unequal access to social and technical resources.
Action Generator Based on Primitive Actions and Individual Properties
Authors: Jun-Hyuk Lee, Geun-Jae Jung, Jong-Hee Park
Venue: Proceedings of the Third KES International Symposium on Agent and Multi-Agent Systems: Technologies and Applications (2009)

This paper presents a method of how to simulate various human actions. Actions are formed in the Action Hierarchy, and are reified in terms of expanding the hierarchy. While inheritance, super classes provide overall information of actions, and sub classes are used as the actual functions of actions. Primitive actions as leaves of the action hierarchy are proposed for an atomic action to be shared in several actions, and used as key frame. The Action Generator guarantees to return accurate primitive actions to an agent based on the Action Library and the Action Hierarchy, and also provides individual patterns of actions.
Efficiently sampling exchangeable Cuadras-Augé copulas in high dimensions
Authors: Jan-Frederik Mai, Matthias Scherer
Venue: Information Sciences: an International Journal (2009)

An n-dimensional random vector is constructed whose survival copula is given by a copula that was first presented in Cuadras and Auge [C.M. Cuadras, J. Auge, A continuous general multivariate distribution and its properties, Communications in Statistics - Theory and Methods 10 (4) (1981) 339-353]. This construction adds a Poisson subordinator as mixing variable to initially independent exponentially distributed random variables. It is shown how the choice of Poisson process relates to the parameter of the induced Cuadras-Auge copula. Based on this construction, a sampling algorithm for this multivariate distribution is presented which has average computational efficiency O(nloglogn).
Single Trial Evoked Potentials Estimation by Using Wavelet Enhanced Principal Component Analysis Method
Authors: Ling Zou, Zhenghua Ma, Shuyue Chen, Suolan Liu, Renlai Zhou
Venue: Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part III (2009)

In this paper we present a new wavelet denoising (WD) enhanced principal component analysis (PCA) method (wPCA) to reduce the number of trials required for the efficient extraction of brain event related potentials (ERPs). First, the ERPs are extracted with wavelet transform, giving us an enhanced version of the raw data. Next, the principal components (PCs) with most of the total variance are considered to be part of the ERP subspace. Lastly, the ERPs are reconstructed from the selected PCs. Simulation and experimental results show that the wPCA method provides better performance than either WD or PCA method.
Advanced Policy Explanations on the Web
Authors: P. A. Bonatti, D. Olmedilla, J. Peer
Venue: Proceeding of the 2006 conference on ECAI 2006: 17th European Conference on Artificial Intelligence August 29 -- September 1, 2006, Riva del Garda, Italy (2006)

The frameworks for protecting security and privacy can be effective only if common users---with no training in computer science or logic---increase their awareness and control over the policy applied by the systems they interact with. Towards this end, we introduce a mechanism for answering why, why-not, how-to, and what-if queries on rule-based policies for trust negotiation. Our framework is lightweight and scalable but it fulfills the main goals of modern explanation facilities. We adopt a novel tabled explanation structure, that simultaneously shows local and global (intra-proof and inter-proof) information, thereby facilitating navigation. Answers are focussed by removing irrelevant parts with suitable heuristics.
INSPEC2T: Inexpensive Spectrometer Color Camera Technology
Authors: W. J. Scheirer, S. R. Kirkbride, T. E. Boult
Venue: Proceedings of the 2008 IEEE Workshop on Applications of Computer Vision (2008)

Modern spectrometer equipment tends to be expensive, thus increasing the cost of emerging systems that take advantage of spectral properties as part of their operation. This paper introduces a novel technique that exploits the spectral response characteristics of a traditional sensor (i.e. CMOS or CCD) to utilize it as a low-cost spectrometer. Using the raw Bayer pattern data from a sensor, we estimate the brightness and wavelength of the measured light at a particular point. We use this information to support wide dynamic range, high noise tolerance, and, if sampling takes place on a slope, sub-pixel resolution. Experimental results are provided for both simulation and real data. Further, we investigate the potential of this low-cost technology for spoof detection in biometric systems. Lastly, an actual hardware systhsis is conducted to show the ease with which this algorthim can be implemented onto an FPGA.