ppxscal/embedding_network huggingface dataset:
Identifying Quotations in Reference Works and Primary Materials
Authors: Andrea Ernst-Gerlach, Gregory Crane
Venue: Proceedings of the 12th European conference on Research and Advanced Technology for Digital Libraries (2008)

Identifying quotations from reference works in primary materials is a very important feature for digital libraries. By adding corresponding citation links to the original text, we can help contextualize the source material. In this paper we introduce an algorithm for identifying citations automatically based on an analysis of the structure of quotations from three different reference works of Latin texts. An evaluation shows that this approach is capable of finding a large number of quotations with which no machine actionable citations are associated. Additionally this approach can be applied for quotations that have been altered in a range of ways from their source.
First-Order Model Checking Problems Parameterized by the Model
Authors: Barnaby Martin
Venue: Proceedings of the 4th conference on Computability in Europe: Logic and Theory of Algorithms (2008)

We study the complexity of the model checking problem, for fixed models A, over certain fragments $\mathcal{L}$ of first-order logic, obtained by restricting which of the quantifiers and boolean connectives we permit. These are sometimes known as the expression complexities of $\mathcal{L}$. We obtain various full and partial complexity classification theorems for these logics $\mathcal{L}$ as each ranges over models A, in the spirit of the dichotomy conjecture for the Constraint Satisfaction Problem --- which itself may be seen as the model checking problem for existential conjunctive positive first-order logic.
Niche Radius Adaptation with Asymmetric Sharing
Authors: Vincent Goes, Ofer M. Shir, Thomas Bäck
Venue: Proceedings of the 10th international conference on Parallel Problem Solving from Nature: PPSN X (2008)

In the field of Genetic Algorithms, niching techniques have been invented with the aim to induce speciation on multimodal fitness landscapes. Unfortunately, they often rely on a problem-dependent niche radius parameter. This is the niche radius problem. In recent research, the possibilities to transfer niching techniques to the field of Evolution Strategies (ES) have been studied. First attempts were carried out to learn a good value for the niche radius through self-adaptation. In this paper we introduce a new niching method for ES with self-adaptation of the niche radius: asymmetric sharing. It is a form of fitness sharing. In contrast to earlier studies, it does not depend on coupling the niche radius to other strategy parameters. Experimental results indicate that asymmetric sharing performs well in comparison to traditional sharing, without relying on problem-dependent parameters.
New Measure for Shape Elongation
Authors: Miloš Stojmenović, Joviša Žunić
Venue: Proceedings of the 3rd Iberian conference on Pattern Recognition and Image Analysis, Part II (2007)

Shape elongation is one of the basic shape descriptors that has a very clear intuitive meaning. That is reason for its applicability in many shape classification tasks. In this paper we define a new method for computing shape elongation for shapes with polygonal boundaries. The measure is the ratio of the maximal and minimal of the sums of squared lengths of the projections of all of the edges of the polygonal boundary onto a line which has a particular slope. We express the measure with a closed formula. This measure finds the elongation for shapes whose boundary is not extracted completely, which is impossible to achieve with existing area based measures.
Generating Fuzzy Equivalence Classes on RSS News Articles for Retrieving Correlated Information
Authors: Nathaniel Gustafson, Maria Soledad Pera, Yiu-Kai Ng
Venue: Proceedings of the international conference on Computational Science and Its Applications, Part II (2008)

Tens of thousands of news articles are posted on-line each day, covering topics from politics to science to current events. In order to better cope with this overwhelming volume of information, RSS (news) feeds are used to categorize newly posted articles. Nonetheless, most RSS users must filter through many articles within the same or different RSS feeds in order to locate articles pertaining to their particular interests. Due to the large number of news articles in individual RSS feeds, there is a need for further organizing articles to aid users in locating non-redundant, informative, and related articles of interest quickly. In this paper, we present a novel approach which uses the word-correlation factors in a fuzzy set information retrieval model to (i) filter out redundant news articles from RSS feeds, (ii) shed less-informative articles from the non-redundant ones, and (iii) cluster the remaining informative articles according to the fuzzy equivalence classes generated on the news articles. Our clustering approach requires little overhead or computational costs, and experimental results have shown that it outperforms other existing well-known clustering approaches.
Text Visualization for Visual Text Analytics
Authors: John Risch, Anne Kao, Stephen R. Poteet, Y. -J. Wu
Venue: Visual Data Mining: Theory, Techniques and Tools for Visual Analytics (2008)

The termvisual text analytics describes a class of information analysis techniques and processes that enable knowledge discovery via the use of interactive graphical representations of textual data. These techniques enable discovery and understanding via the recruitment of human visual pattern recognition and spatial reasoning capabilities. Visual text analytics is a subclass of visual data mining / visual analytics, which more generally encompasses analytical techniques that employ visualization of non-physically-based (or "abstract") data of all types. Text visualization is a key component in visual text analytics. While the term "text visualization" has been used to describe a variety of methods for visualizing both structured and unstructured characteristics of text-based data, it is most closely associated with techniques for depicting the semantic characteristics of the free-text components of documents in large document collections. In contrast with text clustering techniques which serve only to partition text corpora into sets of related items, these so-called semantic mapping methods also typically strive to depict detailed inter- and intra-set similarity structure. Text analytics software typically couples semantic mapping techniques with additional visualization techniques to enable interactive comparison of semantic structure with other characteristics of the information, such as publication date or citation information. In this way, value can be derived from the material in the form of multidimensional relationship patterns existing among the discrete items in the collection. The ultimate goal of these techniques is to enable human understanding and reasoning about the contents of large and complexly related text collections.
Video Distribution Under Multiple Constraints
Authors: Boaz Patt-Shamir, Dror Rawitz
Venue: Proceedings of the 2008 The 28th International Conference on Distributed Computing Systems (2008)

We consider the optimization problem of providing a set of videostreams to a set of clients, where each stream has costs in m possible measures (such as communication bandwidth, processing bandwidth etc.), and each client has its own utility function for each stream. We assume that the server has a budget cap on each of the m cost measures; each client has an upper bound on the utility that can be derived from it, and potentially also upper bounds in each of the m cost measures. The task is to choose which streams the server will provide, and out of this set, which streams each client will receive. The goal is to maximize the overall utility subject to the budget constraints. We give an efficient approximation algorithm with approximation factor of O(m) with respect to the optimal possible utility for any input, assuming that clients have only a bound on their maximal utility. If, in addition, each client has at most m_c capacity constraints, then the approximation factor increases by another factor of O(m_clogn), where n is the input length. We also consider the special case of "small" streams, namely where each stream has cost of at most O(1/log n) fraction of the budget cap, in each measure. For this case we present an algorithm whose approximation ratio is O(\log n).
Overshoot Effect in Stiffness Perception Tasks during Hand Motion with Haptic Device
Authors: Marco Vicentini, Debora Botturi
Venue: Proceedings of the 6th international conference on Haptics: Perception, Devices and Scenarios (2008)

This study is concerned with the overshoot effect in a task of surface differentiation when both surface stiffness and impact velocity are varied. Psychophysical experiments are conducted using virtual surfaces rendered with a force-feedback device with velocity as visual constraint. We test the force constancy hypothesis formulated by Walker and Tan [12][1] which states that users maintain constant penetration force while exploring haptic virtual surfaces. Data collected during stroking surfaces of varying stiffness partially support this hypothesis and allow to consider the relevance of the impact velocity factor. Our results clearly show that changes in impact velocity affects surface penetration. Our findings underscore the importance of better understanding the interplay of the human perceptual parameters in a haptic framework. Future work will focus on the development of compensation rules for ensuring perceptual accuracy of anatomic haptic virtual environments. This will ensure accurate simulation of the haptic interaction between surgical tools and body organs.
The University of Évora's Participation in QA@CLEF-2007
Authors: José Saias, Paulo Quaresma
Venue: Advances in Multilingual and Multimodal Information Retrieval: 8th Workshop of the Cross-Language Evaluation Forum, CLEF 2007, Budapest, Hungary, September 19-21, 2007, Revised Selected Papers (2008)

The University of Évora participation in QA@CLEF-2007 was based on the Senso question answer system. This system uses an ontology with semantic information to support some operations. The full text collection is indexed and for each question a search is performed for documents that may have one answer. There is an ad-hoc module and a logic-programming based module that look for answers. The solution with the highest weight is then returned. The results indicate that the system is more suitable for the definition question type.
Modelling Attacker's Knowledge for Cascade Cryptographic Protocols
Authors: Nazim Benassa
Venue: Proceedings of the 1st international conference on Abstract State Machines, B and Z (2008)

We address the proof-based development of cryptographic protocols satisfying security properties. Communication channels are supposed to be unsafe. Analysing cryptographic protocols requires precise modelling of the attacker's knowledge. In this paper we use the event B modelling language to model the knowledge of the attacker for a class of cryptographic protocols called cascade protocols. The attacker's behaviour conforms to the Dolev-Yao model. In the Dolev-Yao model, the attacker has full control of the communication channel, and the cryptographic primitives are supposed to be perfect.
A content-based approach for document representation and retrieval
Authors: Antonio M. Rinaldi
Venue: Proceeding of the eighth ACM symposium on Document engineering (2008)

In the last few years, the problem of defining efficient techniques for knowledge representation is becoming a challenging topic in both academic and industrial community. The large amount of available data creates several problems in terms of information overload. In this framework, we assume that new approaches for knowledge definition and representation may be useful, in particular the ones based on the concept of ontology. In this paper we propose a suitable model for knowledge representation purposes using linguistic concepts and properties. We implement our model in a system which, using novel techniques and metrics, analyzes documents from a semantic point of view using as context of interest the Web. Experiments are performed on a test set built using a directory service to have information about analyzed documents. The obtained results compared with other similar systems show an effective improvement.
From Mirroring to Guiding: A Review of State of the Art Technology for Supporting Collaborative Learning
Authors: Amy Soller, Alejandra Martínez, Patrick Jermann, Martin Muehlenbrock
Venue: International Journal of Artificial Intelligence in Education (2005)

We review a representative selection of systems that support the management of collaborative learning interaction, and characterize them within a simple classification framework. The framework distinguishes between mirroring systems, which display basic actions to collaborators, metacognitive tools, which represent the state of interaction via a set of key indicators, and coaching systems, which offer advice based on an interpretation of those indicators. The reviewed systems are further characterized by the type of interaction data they assimilate, the processes they use for deriving higher-level data representations, the variables or indicators that characterize these representations, and the type of feedback they provide to students and teachers. This overview of technological capabilities is designed to lay the groundwork for further research into which technological solutions are appropriate for which learning situations.
Label ranking by learning pairwise preferences
Authors: Eyke Hüllermeier, Johannes Fürnkranz, Weiwei Cheng, Klaus Brinker
Venue: Artificial Intelligence (2008)

Preference learning is an emerging topic that appears in different guises in the recent literature. This work focuses on a particular learning scenario called label ranking, where the problem is to learn a mapping from instances to rankings over a finite number of labels. Our approach for learning such a mapping, called ranking by pairwise comparison (RPC), first induces a binary preference relation from suitable training data using a natural extension of pairwise classification. A ranking is then derived from the preference relation thus obtained by means of a ranking procedure, whereby different ranking methods can be used for minimizing different loss functions. In particular, we show that a simple (weighted) voting strategy minimizes risk with respect to the well-known Spearman rank correlation. We compare RPC to existing label ranking methods, which are based on scoring individual labels instead of comparing pairs of labels. Both empirically and theoretically, it is shown that RPC is superior in terms of computational efficiency, and at least competitive in terms of accuracy.
Optically Interconnected Parallel Computing Systems
Authors: Masatoshi Ishikawa, Neil McArdle
Venue: Computer (1998)

Researchers have developed an architecture for high-speed computation, image processing, and robotic vision systems that uses both the programmability of mature electronic technology and the density and parallelism of high-speed optical interconnects.
Target Track System Design Based on SVM and AdaBoost
Authors: Hua-jun Song, Mei-li Shen, Wei-feng Liu
Venue: Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 4 - Volume 04 (2008)

It is very important to target detecting hardware and algorithm design in the field of target tracking field. A kind of detection algorithm using SVM (support vector machine) and AdaBoost which selects representative Harr characters is proposed. SVM uses selected Harr wavelet characters as input data in training and classifying procedure. In order to accelerate SVM classify and detect speed, the cascade method is also been used. Moreover, Hardware system design is also a key to decrease algorithm time. This paper introduces construct, theory and mainly chipset function of hardware system in brief. In the end, experiment result shows that this system not only improves the tracking precision but also detecting speed and meets the real time and high precision requirement of target tracking system.
Efficient Tracking as Linear Program on Weak Binary Classifiers
Authors: Michael Grabner, Christopher Zach, Horst Bischof
Venue: Proceedings of the 30th DAGM symposium on Pattern Recognition (2008)

This paper demonstrates how a simple, yet effective, set of features enables to integrate ensemble classifiers in optical flow based tracking. In particular, gray value differences of pixel pairs are used for generating binary weak classifiers, forming the respective object representation. For the tracking step an affine motion model is proposed. By using hinge loss functions, the motion estimation problem can be formulated as a linear program. Experiments demonstrate robustness of the proposed approach and include comparisons to conventional tracking methods.
Finding Arbitrary Shaped Clusters for Character Recognition
Authors: Noha A. Yousri, Mohamed. S. Kamel, Mohamed. A. Ismail
Venue: Proceedings of the 5th international conference on Image Analysis and Recognition (2008)

Several supervised and unsupervised methods have been applied to the field of character recognition. In this research we focus on the unsupervised methods used to group similar characters together. Instead of using the traditional clustering algorithms, which are mainly restricted to globular-shaped clusters, we use an efficient distance based clustering that identifies the natural shapes of clusters according to their densities. Thus, in the case of character recognition, where it is natural to have different writing styles for the same character, the algorithm can be used to discover the continuity between character feature vectors, which cannot be discovered by traditional algorithms. This paper |introduces the use of an algorithm that efficiently finds arbitrary-shaped clusters of characters, and compares it to related algorithms. Two character recognition data sets are used to illustrate the efficiency of the suggested algorithm.
Improving the Integration of Neuro-Symbolic Rules with Case-Based Reasoning
Authors: Jim Prentzas, Ioannis Hatzilygeroudis, Othon Michail
Venue: Proceedings of the 5th Hellenic conference on Artificial Intelligence: Theories, Models and Applications (2008)

In this paper, we present an improved approach integrating rules, neural networks and cases, compared to a previous one. The main approach integrates neurules and cases. Neurules are a kind of integrated rules that combine a symbolic (production rules) and a connectionist (adaline unit) representation. Each neurule is represented as an adaline unit. The main characteristics of neurules are that they improve the performance of symbolic rules and, in contrast to other hybrid neuro-symbolic approaches, they retain the modularity of production rules and their naturalness in a large degree. In the improved approach, various types of indices are assigned to cases according to different roles they play in neurule-based reasoning, instead of one. Thus, an enhanced knowledge representation scheme is derived resulting in accuracy improvement. Experimental results demonstrate its effectiveness.
Realization Theory for Discrete-Time Semi-algebraic Hybrid Systems
Authors: Mihály Petreczky, René Vidal
Venue: Proceedings of the 11th international workshop on Hybrid Systems: Computation and Control (2008)

We present realization theory for a class of autonomous discrete-time hybrid systems called semi-algebraic hybrid systems. These are systems in which the state and output equations associated with each discrete state are defined by polynomial equalities and inequalities. We first show that these systems generate the same output as semi-algebraic systems and implicit polynomial systems. We then derive necessary and almost sufficient conditions for existence of an implicit polynomial system realizing a given time-series data. We also provide a characterization of the dimension of a minimal realization as well as an algorithm for computing a realization from a given time-series data.
Gem #16: pragma no_return
Authors: Bob Duff
Venue: ACM SIGAda Ada Letters (2008)

Ada Gem #16 -- Pragma No_Return may be used to mark procedures that cannot return normally.
Beyond Frontier Exploration
Authors: Arnoud Visser, Xingrui-Ji, Merlijn Ittersum, Luis A. González Jaime, Laurenţiu A. Stancu
Venue: RoboCup 2007: Robot Soccer World Cup XI (2008)

This article investigates the prerequisites for a global exploration strategy in an unknown environment on a virtual disaster site. Assume that a robot equipped with a laser range scanner can build a detailed map of a previous unknown environment. The remaining question is how to use this information on this map for further exploration.On a map several interesting locations can be present where the exploration can be continued, referred as exploration frontiers. Typically, a greedy algorithm is used for the decision which frontier to explore next. Such a greedy algorithm only considers interesting locations locally, focused to reduce the movement costs. More sophisticated algorithms also take into account the information that can be gained along each frontier. This shifts the problem to estimate the amount of unexplored area behind the frontiers on the global map. Our algorithm exploits the long range of current laser scanners. Typically, during the previous exploration a small number of laser rays already passed the frontier, but this number is too low to have major impact on the generated map. Yet, the few rays through a frontier can be used to estimate the potential information gain from unexplored area beyond the frontier.
A Copper Bullet for Software Quality Improvement
Authors: Michael Blaha
Venue: Computer (2004)

Fred Brooks long ago observed that there is no silver bullet to improve software quality. However, there are copper bullets--lesser steps that improve quality over time. One of these is the notion of software engineering, the practice of thinking carefully before immersing yourself in the minutia of coding.The author offers a summary of his experience indicating that database reverse engineering offers a quality improvement strategy that could benefit the entire software community. 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
An Agent Based Multifactor Biometric Security System
Authors: Girija Chetty, Dharmendra Sharma, Bala M. Balachandran
Venue: Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part III (2008)

A novel agent based protocol for computer and network security based on multifactor fusion of passwords and facial biometrics for user authentication is proposed in this paper. The protocol uses multiple factors for authentication involving a combination of passwords and face biometric template on the smart card and the user workstation. The biometric match is performed by a module running on the user's workstation, authenticated by a mobile agent coming from a reliable server. The proposed protocol uses the current cryptographic tokens without requiring any hardware or software changes.