ppxscal/embedding_network huggingface dataset:
Instance optimal query processing in spatial networks
Authors: Ke Deng, Xiaofang Zhou, Heng Tao Shen, Shazia Sadiq, Xue Li
Venue: The VLDB Journal &mdash; The International Journal on Very Large Data Bases (2009)

The performance optimization of query processing in spatial networks focuses on minimizing network data accesses and the cost of network distance calculations. This paper proposes algorithms for network k-NN queries, range queries, closest-pair queries and multi-source skyline queries based on a novel processing framework, namely, incremental lower bound constraint. By giving high processing priority to the query associated data points and utilizing the incremental nature of the lower bound, the performance of our algorithms is better optimized in contrast to the corresponding algorithms based on known framework incremental Euclidean restriction and incremental network expansion. More importantly, the proposed algorithms are proven to be instance optimal among classes of algorithms. Through experiments on real road network datasets, the superiority of the proposed algorithms is demonstrated.
Social network analysis in virtual environments
Authors: Devan Rosen, Margaret Corbit
Venue: Proceedings of the 20th ACM conference on Hypertext and hypermedia (2009)

Multi-user virtual environments (MUVEs) allow users to navigate and explore the environment as well as interact with other users. The interaction within these environments is often text-based using Internet relay chat (IRC) and related systems. IRC poses a difficulty for researchers looking to analyze and interpret the communicative interaction since data is stored in the form of chatlogs. The current research proposes and applies methodological procedures for the representation and analysis of interaction in MUVEs as social networks. A case study on SciCentr programs from Cornell University is used to elaborate methods and related findings.
Enumerating Unlabeled and Root Labeled Trees for Causal Model Acquisition
Authors: Yang Xiang, Zoe Jingyu Zhu, Yu Li
Venue: Proceedings of the 22nd Canadian Conference on Artificial Intelligence: Advances in Artificial Intelligence (2009)

To specify a Bayes net (BN), a conditional probability table (CPT), often of an effect conditioned on its n causes, needs to be assessed for each node. It generally has the complexity exponential on n. The non-impeding noisy-AND (NIN-AND) tree is a recently developed causal model that reduces the complexity to linear, while modeling both reinforcing and undermining interactions among causes. Acquisition of an NIN-AND tree model involves elicitation of a linear number of probability parameters and a tree structure. Instead of asking the human expert to describe the structure from scratch, in this work, we develop a two-step menu selection technique that aids structure acquisition.
The Design of Effective Simulation-Based Inquiry Learning Environments
Authors: Ton de Jong
Venue: Proceeding of the 2006 conference on Learning by Effective Utilization of Technologies: Facilitating Intercultural Understanding (2006)

Modern theories on learning and instruction call attention to learning environments that create constructivistic, situated, and collaborative learning experiences. Simulations offer specific features that enable self-directed, highly autonomous, high interaction learning. First, learning in these environments differs from learning in expository environments in that it puts a higher emphasis on inquiry processes such as hypothesis generation and testing and on regulative processes such as planning and monitoring. Second, these environments offer specific opportunities to situate learning in realistic settings, but they also offer the possibility to adapt reality to support learning. Third, inquiry learning presents opportunities for negotiation and collaboration. This presentation will set out characteristics of simulations discuss characteristic inquiry processes and associated problems, and examine what is needed to design effective inquiry learning environments.
A Class of New Large-Update Primal-Dual Interior-Point Algorithms for $\emph{P}_\ast(\kappa)$ Linear Complementarity Problems
Authors: Huaping Chen, Mingwang Zhang, Yuqin Zhao
Venue: Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part III (2009)

A class of polynomial primal-dual interior-point algorithms for P * (&kappa;) linear complementarity problems (LCPs) are presented. We generalize Ghami et al.'s[A polynomial-time algorithm for linear optimization based on a new class of kernel functions(2008)] algorithm for linear optimization (LO) problem to P * (&kappa;) LCPs. Our analysis is based on a class of finite kernel functions which have the linear and quadratic growth terms. Since P*(&kappa;) LCP is a generalization of LO problem, we lose the orthogonality of the vectors dx and ds. So our analysis is different from the one in Ghami et al's algorithm. Despite this, the favorable complexity result is obtained, namely, $O((1 + 2\kappa)n^{\frac{1}{1+p}}\log n \log(n/\epsilon))$, which is better than the usual large-update primal-dual algorithm based on the classical logarithmic barrier function for P * (&kappa;) LCP.
Dynamic visual tracking control of a mobile robot with image noise and occlusion robustness
Authors: Chi-Yi Tsai, Kai-Tai Song
Venue: Image and Vision Computing (2009)

This paper presents a robust visual tracking control design for a nonholonomic mobile robot equipped with a tilt camera. This design aims to allow the mobile robot to keep track of a dynamic moving target in the camera's field-of-view; even though the target is temporarily fully occluded. To achieve this, a control system consisting of a visual tracking controller (VTC) and a visual state estimator (VSE) is proposed. A novel visual interaction model is derived to facilitate the design of VTC and VSE. The VSE is responsible for estimating the optimal target state and target image velocity in the image space. The VTC then calculates the corresponding command velocities for the mobile robot to work in the world coordinates. The proposed VSE not only possesses robustness against the image noise, but also overcomes the temporary occlusion problem. Computer simulations and practical experiments of a mobile robot to track a moving target have been carried out to validate the performance and robustness of the proposed system.
Square-root Householder subspace tracking
Authors: Peter Strobach
Venue: Numerische Mathematik (2009)

A class of singular value decomposition (SVD)-type subspace trackers based on the overdetermined row-Householder principle is introduced. These algorithms are maximally fast with a dominant operations count of 3Nr multiplications per time update. They can be regarded as square-root forms of previously introduced conventional fast subspace trackers and offer interesting features such as perfectly orthonormal basis estimates, lowest dynamic range requirements, and highest numerical robustness and stability. Several variants of the method are proposed and studied experimentally.
WordNet-based semantic relatedness measures in automatic speech recognition for meetings
Authors: Michael Pucher
Venue: Proceedings of the 45th Annual Meeting of the ACL on Interactive Poster and Demonstration Sessions (2007)

This paper presents the application of WordNet-based semantic relatedness measures to Automatic Speech Recognition (ASR) in multi-party meetings. Different word-utterance context relatedness measures and utterance-coherence measures are defined and applied to the rescoring of N-best lists. No significant improvements in terms of Word-Error-Rate (WER) are achieved compared to a large word-based n-gram baseline model. We discuss our results and the relation to other work that achieved an improvement with such models for simpler tasks.
K-means in space: a radiation sensitivity evaluation
Authors: Kiri L. Wagstaff, Benjamin Bornstein
Venue: Proceedings of the 26th Annual International Conference on Machine Learning (2009)

Spacecraft increasingly employ onboard data analysis to inform further data collection and prioritization decisions. However, many spacecraft operate in high-radiation environments in which the reliability of dataintensive computation is not known. This paper presents the first study of radiation sensitivity for k-means clustering. Our key findings are 1) k-means data structures differ in sensitivity, which is not determined solely by the amount of memory exposed; 2) no special radiation protection is needed below a data-set-dependent radiation threshold, enabling the use of faster, smaller, and cheaper onboard memory; and 3) subsampling improves radiation tolerance slightly, but the use of kd-trees unfortunately reduces tolerance. Our conclusions can help tailor k-means for use in future high-radiation environments.
Parallel/High-Performance Object-Oriented Scientific Computing: Today's Research, Tomorrow's Practice
Authors: Kei Davis, Jörg Striegnitz
Venue: Object-Oriented Technology. ECOOP 2008 Workshop Reader: ECOOP 2008 Workshops Paphos, Cyprus, July 7-11, 2008 Final Reports (2008)

While object-oriented programming has been embraced in industry, particularly in the form of C++, Java, and Python, its acceptance by the parallel scientific programming community is for various reasons incomplete. Nonetheless, various factors practically dictate the use of language features that provide higher level abstractions than do C or older FORTRAN standards. These include increasingly complex physics models, numerical algorithms, and hardware (e.g. deep memory hierarchies, ever-increasing numbers of processors, and the advent of multi- and many-core processors and heterogeneous architectures). Our emphases are on identifying specific problems impeding greater acceptance and widespread use of object-oriented programming in scientific computing; proposed and implemented solutions to these problems; and new or novel frameworks, approaches, techniques, or idioms for parallel/high-performance object-oriented scientific computing.
EulerView: article organisation within the ACM classification
Authors: Rosario De Chiara, Andrew Fish
Venue: Proceedings of the 2008 IEEE Symposium on Visual Languages and Human-Centric Computing (2008)

EulerView is a resource management tool which supports operations, such as intersection, on categories. We relate EulerView displays to sets of paths in the transitive closure of the directed dual graph of an Euler diagram, and provide methods for transforming hierarchies with symbolic links into an EulerView display. Linking the display directly to the file system enabled the export of both the directory structure and resource placement which enables users to build small manageable views of their categorisation structure within which to place resources and then export this onto the larger file system. Using the transformation methods developed, we consider the importation of ACM classification into EulerView, enabling users to categorise and store resources such as articles within the imported ACM classification. EulerView is tailored to be appropriate for the ACM CCS application, and new techniques for focus and navigation within EulerView are developed.
Multi-Object Tracking Based on Particle Filter and Data Association in Color Image Sequences
Authors: Ayoub Al-Hamadi, Saira Saleem Pathan, Bernd Michaelis
Venue: Proceedings of the International Conference on Computer Vision and Graphics: Revised Papers (2008)

Robust tracking of multi-objects is still challenging in real scenarios such as crowed scenes. In this paper a novel method in color image sequences is proposed for tracking multiple objects in non-cooperative situations. A system of independent particle filters with an adaptive motion model is used which tracks the moving objects under complex situations. Besides, in order to handle the conflicted situations, an integrated data association technique is exploited which adjusts the particle filters accordingly. Results have shown the good performance of the proposed method on various complex-situation image sequences.
Front-End Vision and Multi-Scale Image Analysis: Multi-scale Computer Vision Theory and Applications, written in Mathematica, 1st edition
Authors: B.M. Romeny
Venue:  (2009)

Front-End Vision and Multi-Scale Image Analysis is a tutorial in multi-scale methods for computer vision and image processing. It builds on the cross fertilization between human visual perception and multi-scale computer vision (`scale-space') theory and applications. The multi-scale strategies recognized in the first stages of the human visual system are carefully examined, and taken as inspiration for the many geometric methods discussed. All chapters are written in Mathematica, a spectacular high-level language for symbolic and numerical manipulations. The book presents a new and effective approach to quickly mastering the mathematics of computer vision and image analysis. The typically short code is given for every topic discussed, and invites the reader to spend many fascinating hours `playing' with computer vision. Front-End Vision and Multi-Scale Image Analysis is intended for undergraduate and graduate students, and all with an interest in computer vision, medical imaging, and human visual perception.
An efficient rigorous approach for identifying statistically significant frequent itemsets
Authors: Adam Kirsch, Michael Mitzenmacher, Andrea Pietracaprina, Geppino Pucci, Eli Upfal, Fabio Vandin
Venue: Proceedings of the twenty-eighth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems (2009)

As advances in technology allow for the collection, storage, and analysis of vast amounts of data, the task of screening and assessing the significance of discovered patterns is becoming a major challenge in data mining applications. In this work, we address significance in the context of frequent itemset mining. Specifically, we develop a novel methodology to identify a meaningful support threshold s* for a dataset, such that the number of itemsets with support at least s* represents a substantial deviation from what would be expected in a random dataset with the same number of transactions and the same individual item frequencies. These itemsets can then be flagged as statistically significant with a small false discovery rate. Our methodology hinges on a Poisson approximation to the distribution of the number of itemsets in a random dataset with support at least s, for any s greater than or equal to a minimum threshold smin. We obtain this result through a novel application of the Chen-Stein approximation method, which is of independent interest. Based on this approximation, we develop an efficient parametric multi-hypothesis test for identifying the desired threshold s*. A crucial feature of our approach is that, unlike most previous work, it takes into account the entire dataset rather than individual discoveries. It is therefore better able to distinguish between significant observations and random fluctuations. We present extensive experimental results to substantiate the effectiveness of our methodology.
What Do You Mean by to Help Learning of Metacognition?
Authors: Michiko Kayashima, Akiko Inaba, Riichiro Mizoguchi
Venue: Proceeding of the 2005 conference on Artificial Intelligence in Education: Supporting Learning through Intelligent and Socially Informed Technology (2005)

Several computer-based learning support systems and methods help learners to master metacognitive activity. Which systems and methods are designed to eliminate which difficulties associated with the learning of metacognitive activity through its clear specification? We adopt a method in our research that supports learning by eliminating salient difficulties. We believe that it is possible to eliminate or decrease them through appropriate design only after specifying those difficulties associated with learning. In this study, we analyze difficulties in performing cognitive activity, distinguish factors of difficulty from other factors, and construct our framework, which represents difficulties in performing metacognitive activity. Finally, we organize existing support systems and methods based on that framework.
Raising the level of abstraction in the development of GMF-based graphical model editors
Authors: Dimitrios S. Kolovos, Louis M. Rose, Richard F. Paige, Fiona A. C. Polack
Venue: Proceedings of the 2009 ICSE Workshop on Modeling in Software Engineering (2009)

The Eclipse Graphical Modeling Framework (GMF) provides substantial infrastructure and tooling for developing diagram-based editors for modelling languages atop the Eclipse platform. It is widely accepted that implementing a visual editor using the built-in GMF facilities is a particularly complex and error-prone task and requires a steep learning curve. We present an approach that raises the level of abstraction at which a visual editor is specified. The approach uses annotations at the metamodel level. Annotations are used for producing the required low-level intermediate GMF models necessary for generating an editor via model-to-model transformations.
Synthesizing executable programs from requirements
Authors: Benjamin Goldberg
Venue:  (2008)

Automatic generation of correct software from requirements has long been a &ldquo;holy grail&rdquo; for system and software development. According to this vision, instead of implementing a system and then working hard to apply testing and verification methods to prove system correctness, a system is rather built correctly by construction. This problem, referred to as synthesis, is undecidable in the general case. However, by restricting the domain to decidable subsets, it is possible to bring this vision one step closer to reality. The focus of our study is reactive systems, or non-terminating programs that continuously receive input from an external environment and produce output responses. Reactive systems are often safety critical and include applications such as anti-lock braking systems, auto-pilots, and pacemakers. One of the challenges of reactive system design is ensuring that the software meets the requirements under the assumption of unpredictable environment input. The behavior of many of these systems can be expressed as regular languages over infinite strings, a domain in which synthesis has yielded successful results. We present a method for synthesizing executable reactive systems from formal requirements. The object-oriented requirements language of Live Sequence Charts (LSCs) is considered. We begin by establishing a mapping between various subsets of the language and finite-state formal models. We also consider LSCs which can express time constraints over a dense-time domain. From one of these models, we show how to formulate a winning strategy that is guaranteed to satisfy the requirements, provided one exists. The strategy is realized in the form of a controller which guides the system in choosing only non-violating behaviors. We describe an implementation of this work as an extension of an existing tool called the Play-Engine.
Understanding factors affecting e-reverse auction use: An integrative approach
Authors: Cigdem A. Gumussoy, Fethi Calisir
Venue: Computers in Human Behavior (2009)

Using electronic-reverse auction (e-reverse auction) offers many advantages to companies such as price reduction, decrease in cycle time, standardization, and transparency in purchasing process. Despite its great advantages, some users do not want to use e-reverse auction technology for the procurement of products or services. This study aims to understand factors affecting e-reverse auction usage in companies by integrating three important theories. Key constructs of technology acceptance model (TAM), theory of planned behavior (TPB), and innovation diffusion theory (IDT) are integrated to explain behavioral intention to use and actual use of e-reverse auction. Using LISREL 8.54, data collected from 156 employees working in the procurement department of companies in 40 different countries were used to test the proposed research model. Results indicated that, 76% of employees' intention to use e-reverse auction is explained by subjective norms, perceived behavioral control, and perceived usefulness. Among them, subjective norms have the strongest effect. Besides, actual use of e-reverse auction is directly predicted by behavioral intention to use. We conclude with managerial implications and recommendations for possible future research.
The integration of asynchronous and synchronous communication support in cooperative systems
Authors: Andrea Kienle
Venue: Proceeding of the 2006 conference on Cooperative Systems Design: Seamless Integration of Artifacts and Conversations -- Enhanced Concepts of Infrastructure for Communication (2006)

This paper presents the design and a first evaluation of the cooperative system KOLUMBUS 2 that integrates synchronous and asynchronous communication support and the joint work on material. The design is theory driven and bases on context-oriented communication theory and media synchronicity theory. The evaluation revealed mixed acceptance. While the design of KOLUMBUS chat with references, clipboard and list of topics was widely accepted problems occurred with the integration. Based on these results ideas for further improvements are shown.
Processes of Emergence of Systems and Systemic Properties: Towards a General Theory of Emergence, Proceedings of the International Conference, Castel Ivano,Italy, 18-20 Ocotber 2007
Authors: Gianfranco Minati, Mario Abram, Eliano Pessa
Venue:  (2009)

This book contains the Proceedings of the 2007 Conference of the Italian Systems Society. Papers deal with the interdisciplinary study of processes of emergence, considering theoretical aspects and applications from physics, cognitive science, biology, artificial intelligence, economics, architecture, philosophy, music and social systems. Such an interdisciplinary study implies the need to model and distinguish, in different disciplinary contexts, the establishment of structures, systems and systemic properties. Systems, as modelled by the observer, not only possess properties, but are also able to make emergent new properties; while current disciplinary models of emergence are based on theories of phase transitions, bifurcations, dissipative structures, multiple systems and organization.The present volume focuses on both generalizing those disciplinary models and identifying correspondences and new more general approaches. The general conceptual framework of the book relates to the attempt to build a general theory of emergence as a general theory of change, corresponding to Von Bertalanffy's project for a general system theory.
Multi-domain sentiment classification
Authors: Shoushan Li, Chengqing Zong
Venue: Proceedings of the 46th Annual Meeting of the Association for Computational Linguistics on Human Language Technologies: Short Papers (2008)

This paper addresses a new task in sentiment classification, called multi-domain sentiment classification, that aims to improve performance through fusing training data from multiple domains. To achieve this, we propose two approaches of fusion, feature-level and classifier-level, to use training data from multiple domains simultaneously. Experimental studies show that multi-domain sentiment classification using the classifier-level approach performs much better than single domain classification (using the training data individually).
Teach Yourself VISUALLY Flash CS3 Professional
Authors: Sherry Kinkoph Gunter
Venue:  (2007)

Clear, step-by-step screen shots arranged in two-page lessons show you how to tackle more than 140 Flash CS3 Professional tasks. No long-winded explanations, just easy, visual directions for performing such necessary operations as creating objects, symbols, and instances; controlling playback with the Timeline; adding interactivity with buttons; organizing project assets with the Library; creating animation with tweens; and adding sound and video . Helpful sidebars offer practical tips and tricks, and its all presented for the visual learner.