ppxscal/embedding_network huggingface dataset:
Relating content through web usage
Authors: Ricardo Baeza-Yates
Venue: Proceedings of the 20th ACM conference on Hypertext and hypermedia (2009)

Relating content is important in any document base, for example to automatically create hyperlinks. Classical techniques to relate Web content include text mining and link analysis. However, a more powerful source for semantically connecting two Web pages is user behavior. In this short summary we categorize existing approaches that use what people do in the Web to relate content and we discuss the issues and the research problems associated with this idea.
Any identifiable knowledge structures from traversal behavior in hypertext environment?
Authors: Perwaiz B. Ismaili
Venue: Proceedings of the 8th WSEAS international conference on Artificial intelligence, knowledge engineering and data bases (2009)

In this paper, we introduce "Knowledge Diagraph Contribution" (KDC) analysis as a novel categorical time-series method in observing underlying knowledge structure of experts by exploiting varying hypertext (web) presentation formats and knowledge domains. The navigation behaviors were studied by designing hypertext presentation format and text that adheres to content design principles inspired by discourse and text comprehension scholars. As a continuation of previous study by Ismaili & Golden [1], twenty undergraduate Psychology students from University of Texas at Dallas participated in this study. Students traversed through different Hypertext (web) presentation formats while reading content from three different knowledge domains controlled for micro (web-page, web-site) and macro (consistent semantic connections across knowledge domains) characteristics. The influences of expertise and web traversal behavior in deriving underlying knowledge structures are presented using KDC analysis. In addition, previously reported Classical data analysis (ANOVA) are compared with KDC analysis in highlighting quantitative and qualitative differences of these derived latent knowledge structures.
Dynamic fringe-saving A*
Authors: Xiaoxun Sun, William Yeoh, Sven Koenig
Venue: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2 (2009)

Fringe-Saving A* is an incremental version of A* that repeatedly finds shortest paths from a fixed start cell to a fixed goal cell in a known gridworld in case the traversability of cells changes over time. It restores the content of the OPEN and CLOSED lists of A* at the point in time when an A* search for the current search problem could deviate from the A* search for the previous search problem. Thus, Fringe-Saving A* reuses the beginning of the previous A* search that is identical to the current A* search. In this paper, we generalize the correctness proof of Fringe-Saving A* to cover the case where the goal cell changes over time in addition to the traversability of cells. We then apply Fringe-Saving A* to the problem of moving an agent along a shortest path from its current cell to a fixed destination cell in a known gridworld, where the shortest path is replanned whenever the traversability of cells changes. Our experimental results show that the resulting Dynamic Fringe-Saving A* algorithm can outperform both repeated A* searches and D* Lite (a state-of-the-art incremental version of A*) in highly dynamic gridworlds, with runtime savings of up to a factor of about 2.5.
A secure unidirectional proxy re-encryption using identity and secret key exchange
Authors: Edna Milgo
Venue: Proceedings of the 47th Annual Southeast Regional Conference (2009)

Proxy re-encryption, abbreviated as PRE, is a cryptosystem which allows the proxy to re-encrypt a cirphertext without accessing the underlying message. The re-encryption protocol should be key independent to avoid compromising the private keys of the sender and the recipient. PRE should also be secure from signature re-usability, where unreliable proxies store and re-use the signatures without the authorization of the signature bearer. This is achieved by ensuring that PRE algorithm is unidirectional, key independent and the signature is dynamic. The proposed approach uses identity and secret key to prevent plain text and collusion attacks while ensuring that the delegator approves every signature used on his behalf. The algorithm used to generate the private/public keys is different from that generating the secret key. The proposed approach is secure even in unreliable proxies.
Proactive information caching for efficient resource discovery in a self-structured grid
Authors: Amos Brocco, Apostolos Malatras, Béat Hirsbrunner
Venue: Proceedings of the 2009 workshop on Bio-inspired algorithms for distributed systems (2009)

The cornerstone of successful deployment of large scale grid systems depends on efficient resource discovery mechanisms. In this respect, this paper presents a grid information system supported by a self-structured overlay topology and proactive information caching. The proposed approach features an ant-inspired self-organized overlay construction that maintains a bounded diameter overlay, and a selective flooding based discovery algorithm that exploit local caches to reduce the number of visited nodes. The caches are periodically exchanged between neighboring nodes using an epidemic replication mechanism that is based on a gossiping algorithm, thus allowing nodes to have a more general view of the network and its resources. We conducted extensive experimentation that provides evidence that the average number of hops required to efficiently locate resources is limited and that our framework performs well with respect to hit rate and network overhead.
A time series representation model for accurate and fast similarity detection
Authors: Francesco Gullo, Giovanni Ponti, Andrea Tagarelli, Sergio Greco
Venue: Pattern Recognition (2009)

Similarity search and detection is a central problem in time series data processing and management. Most approaches to this problem have been developed around the notion of dynamic time warping, whereas several dimensionality reduction techniques have been proposed to improve the efficiency of similarity searches. Due to the continuous increasing of sources of time series data and the cruciality of real-world applications that use such data, we believe there is a challenging demand for supporting similarity detection in time series in a both accurate and fast way. Our proposal is to define a concise yet feature-rich representation of time series, on which the dynamic time warping can be applied for effective and efficient similarity detection of time series. We present the Derivative time series Segment Approximation (DSA) representation model, which originally features derivative estimation, segmentation and segment approximation to provide both high sensitivity in capturing the main trends of time series and data compression. We extensively compare DSA with state-of-the-art similarity methods and dimensionality reduction techniques in clustering and classification frameworks. Experimental evidence from effectiveness and efficiency tests on various datasets shows that DSA is well-suited to support both accurate and fast similarity detection.
Enriching spoken language translation with dialog acts
Authors: Vivek Kumar, Rangarajan Sridhar, Shrikanth Narayanan, Srinivas Bangalore
Venue: Proceedings of the 46th Annual Meeting of the Association for Computational Linguistics on Human Language Technologies: Short Papers (2008)

Current statistical speech translation approaches predominantly rely on just text transcripts and do not adequately utilize the rich contextual information such as conveyed through prosody and discourse function. In this paper, we explore the role of context characterized through dialog acts (DAs) in statistical translation. We demonstrate the integration of the dialog acts in a phrase-based statistical translation framework, employing 3 limited domain parallel corpora (Farsi-English, Japanese-English and Chinese-English). For all three language pairs, in addition to producing interpretable DA enriched target language translations, we also obtain improvements in terms of objective evaluation metrics such as lexical selection accuracy and BLEU score.
A 1-Local Asymptotic 13/9-Competitive Algorithm for&#x00a0;Multicoloring Hexagonal Graphs
Authors: Yong Zhang, Francis Y. L. Chin, Hong Zhu
Venue: Algorithmica (2009)

In the frequency allocation problem, we are given a mobile telephone network, whose geographical coverage area is divided into cells, wherein phone calls are serviced by assigning frequencies to them so that no two calls emanating from the same or neighboring cells are assigned the same frequency. The problem is to use the frequencies efficiently, i.e., minimize the span of frequencies used. The frequency allocation problem can be regarded as a multicoloring problem on a weighted hexagonal graph. In this paper, we give a 1-local asymptotic 4/3-competitive distributed algorithm for multicoloring a triangle-free hexagonal graph, which is a special case of hexagonal graph. Based on this result, we then propose a 1-local asymptotic13/9-competitive algorithm for multicoloring the (general-case) hexagonal graph, thereby improving the previous 1-local 3/2-competitive algorithm.
A Fuzzy Logic Fish School Model
Authors: Juan Carlos González, Christianne Dalforno, Remo Suppi, Emilio Luque
Venue: Proceedings of the 9th International Conference on Computational Science: Part I (2009)

This paper summarizes our work on fuzzy modeling for an Individual-oriented Model (IoM). Our model is particularly geared toward simulating the movement of fish schools, derived from the model by Huth and Wissel. The background and motivation for the problem as well as a description of biological model are given here. A fuzzy logic implementation is discussed based on the mathematical model proposed. Finally, the experiments performed to demonstrate that our model represents the real behavior of fish schools. Keywords: Fuzzy Logic, Individual-oriented Models (IoM), Fish School.
Neighborhood hypergraphs of digraphs and some matrix permutation problems
Authors: Vladimir Gurvich, Igor E. Zverovich
Venue: Discrete Applied Mathematics (2009)

Given a digraph D, the set of all pairs (N^-(v),N^+(v)) constitutes the neighborhood dihypergraph N(D) of D. The Digraph Realization Problem asks whether a given dihypergraph H coincides with N(D) for some digraph D. This problem was introduced by Aigner and Triesch [M. Aigner, E. Triesch, Reconstructing a graph from its neighborhood lists, Combin. Probab. Comput. 2 (2) (1993) 103-113] as a natural generalization of the Open Neighborhood Realization Problem for undirected graphs, which is known to be NP-complete. We show that the Digraph Realization Problem remains NP-complete for orgraphs (orientations of undirected graphs). As a corollary, we show that the Matrix Skew-Symmetrization Problem for square {0,1,-1} matrices (a"i"j=-a"j"i) is NP-complete. This result can be compared with the known fact that the Matrix Symmetrization Problem for square 0-1 matrices (a"i"j=a"j"i) is NP-complete. Extending a negative result of Fomin, Kratochvil, Lokshtanov, Mancini, and Telle [F.V. Fomin, J. Kratochvil, D. Lokshtanov, F. Mancini, J.A. Telle, On the complexity of reconstructing H-free graphs from their star systems, Manuscript (2007) 11 pp] we show that the Digraph Realization Problem remains NP-complete for almost all hereditary classes of digraphs defined by a unique minimal forbidden subdigraph. Finally, we consider the Matrix Complementation Problem for rectangular 0-1 matrices, and prove that it is polynomial-time equivalent to graph isomorphism. A related known result is that the Matrix Transposability Problem is polynomial-time equivalent to graph isomorphism.
Probabilistic-fuzzy inference procedures for knowledge-based systems
Authors: Anna Walaszek-Babiszewska
Venue: Proceedings of the 10th WSEAS international conference on Mathematical and computational methods in science and engineering (2008)

This paper presents a proposition of the knowledge representation and the inference procedure including two types of uncertainty: probabilistic and fuzzy. Added weights to the fuzzy rule-based model state probabilities of fuzzy events in antecedents and consequents. The exemplary calculations are presented.
CE in Engineering Education: An Observation from the Experience
Authors: Teruaki Ito
Venue: Proceeding of the 2006 conference on Leading the Web in Concurrent Engineering: Next Generation Concurrent Engineering (2006)

Concurrent Engineering is one of the key issues of manufacturing to be competitive in the global market place. Even though the major goal of CE would be to reduce the production lead time and to increase of quality of products, its basic idea includes several important engineering elements, such as the clear goal setting, the effective communication strategy in team working, or the problem solving approaches to apply to real problems, which should be taught in engineering education. Reviewing the two examples of engineering education classes from two different institutions, where the author has been involved as a teaching staff, this paper discusses the major factors of success in these classes. This paper shows how these important elements of CE are taught in these classes, and clarifies why the success of these classes has been made.
Detection of chain structures embedded in multidimensional symbolic data
Authors: Atsushi Nagoya, Yujiro Ono, Manabu Ichino
Venue: Pattern Recognition Letters (2009)

The detection of meaningful geometrical structures in multidimensional data is of major interest in data analysis and data mining. In this paper, we will first present the notion of a locally monotonic chain structure based on the Cartesian system model (CSM) which is the mathematical model to manipulate symbolic data. The locally monotonic chain structures include not only monotonic chain structures but also various complex structures organized by several monotonic chains. Then, secondly, we will describe a method to detect the locally monotonic chain structures of objects embedded in multidimensional symbolic data. We will illustrate the usefulness of our method by using both several artificially generated data sets and a real data set.
Computational complexities of axiomatic extensions of monoidal t-norm based logic
Authors: Moataz Saleh El-Zekey, Wafik Boulos Lotfallah, Nehad Nashaat Morsi
Venue: Soft Computing - A Fusion of Foundations, Methodologies and Applications (2009)

We study the computational complexity of some axiomatic extensions of the monoidal t-norm based logic (MTL), namely NM corresponding to the logic of the so-called nilpotent minimum t-norm (due to Fodor in Fuzzy Sets Syst 69:141&#x2013;156, 1995); and SMTL corresponding to left-continuous strict t-norms, introduced by Esteva (and others) (Fuzzy Sets Syst 132(1):107&#x2013;112, 2002; 136(3):263&#x2013;282, 2003). In particular, we show that the sets of 1-satisfiable and positively satisfiable formulae of both NM and SMTL are NP-complete, while the set of 1-tautologies of NM and the set of positive tautologies of both NM and SMTL are co-NP-complete. The set of 1-tautologies of SMTL is only shown to be co-NP-hard, and it remains open if this set is in co-NP. Also, some results on the relations between these sets are obtained. We point out that results about 1-satisfiability and 1-tautology for NM are already well-known. However, in this paper, those results are proved in different ways.
Enriching Specifications for Re-Usable Adaptive Learning Design
Authors: Katerina Georgouli, Pedro Guerreiro
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)

We present the conceptual framework and vocabulary of a new notation system called Adaptive Hypermedia Metadata, based on research in Adaptive Educational Hypermedia and IMS Learning Design specifications. It incorporates new structures to promote adaptivity in the existing engineering approaches, concerning specifications and standards for re-usable learning design. These structures enrich current learning modelling languages in order to support adaptivity at the instructional level and at the pedagogical level.
On sampling-based approximate spectral decomposition
Authors: Sanjiv Kumar, Mehryar Mohri, Ameet Talwalkar
Venue: Proceedings of the 26th Annual International Conference on Machine Learning (2009)

This paper addresses the problem of approximate singular value decomposition of large dense matrices that arises naturally in many machine learning applications. We discuss two recently introduced sampling-based spectral decomposition techniques: the Nystr&ouml;m and the Column-sampling methods. We present a theoretical comparison between the two methods and provide novel insights regarding their suitability for various applications. We then provide experimental results motivated by this theory. Finally, we propose an efficient adaptive sampling technique to select informative columns from the original matrix. This novel technique outperforms standard sampling methods on a variety of datasets.
Web Ontology Segmentation: Extraction, Transformation, Evaluation
Authors: Julian Seidenberg
Venue: Modular Ontologies: Concepts, Theories and Techniques for Knowledge Modularization (2009)

In this chapter we present an algorithm for extracting relevant segments out of large description logic ontologies for the purposes of increasing tractability for both humans and computers. We offer several variations on this algorithm for different purposes. The segments are not mere fragments, but stand alone as ontologies in their own right. This technique takes advantage of the detailed semantics captured within an OWL ontology to produce highly relevant segments. However, extracted segments make no guarantee for preserving the semantics of the complete ontology.
Government outreach to the U.S. Spanish-speaking community uses social media
Authors: Thomas Skirbunt, Leilani Martinez, Darlene Meskell
Venue: Proceedings of the 10th Annual International Conference on Digital Government Research: Social Networks: Making Connections between Citizens, Data and Government (2009)

Case study of the use of social media by GobiernoUSA.gov, the official Spanish-language portal of the U.S. government, to reach the Spanish-speaking community in the United States with government news and information.
Structural modelling and integrative analysis of microelectromechanical systems product using graph theoretic approach
Authors: A. Amalin Prince, V. P. Agrawal
Venue: Microsystem Technologies (2009)

Micro-electromechanical systems (MEMS) as an enabling technology is seen to play a more and more important role for the main stream of industry of the future by broadening its applications to information, communications and bio technologies. Development of MEMS devices, however, still relies on knowledge and experience of MEMS experts due to the design and fabrication process complexity. It is difficult to understand the trade-offs inherent in the system and achieve an optimal structure without any MEMS-related insight. An attempt is made to develop an integrated systems model for the complete structure of the MEMS product system in terms of its constituents and interactions between the constituents. The hierarchical tree structures of the MEMS system and its subsystems are presented up to component level. For characterization, analysis and identification of MEMS product system, three different mathematical models say graph theoretic model, matrix model and permanent model are presented. These models are associated with graph theory, matrix method and variable permanent function by considering the various subsystems, subsubsystems up to component level, their connectivity and interdependency of the MEMS product system. The developed methodology is explained with an example. The proposed modeling and analysis is extendable to the subsystems and the component level. An overall structural analysis can be carried out by following a &#x2018;top-down&#x2019; approach or &#x2018;bottom-up&#x2019; approach. Understanding of MEMS product structure will help in the improvement of performance, cost, design time, and so on.
Global Exponential Stability of Impulsive Fuzzy Cellular Neural Networks with Delays and Reaction-Diffusion Terms
Authors: Xiaobo Li, Haijun Jiang
Venue: Proceedings of the 6th International Symposium on Neural Networks on Advances in Neural Networks (2009)

In this paper, we investigate a class of impulsive fuzzy cellular neural networks with delays and reaction-diffusion terms. By applying Lyapunov functional method and using inequality techniques, some sufficient conditions ensuring the global exponential stability of equilibrium point for impulsive fuzzy cellular neural networks with delays and reaction-diffusion terms are established. An illustrative example is given in the end to guarantee the validity of our theory.
Test-driven goal-directed debugging in spreadsheets
Authors: Robin Abraham, Martin Erwig
Venue: Proceedings of the 2008 IEEE Symposium on Visual Languages and Human-Centric Computing (2008)

We present an error-detection and -correction approach for spreadsheets that automatically generates questions about input/output pairs and, depending on the feedback given by the user, proposes changes to the spreadsheet that would correct detected errors. This approach combines and integrates previous work on automatic test-case generation and goal-directed debugging. We have implemented this method as an extension to MS Excel. We carried out an evaluation of the system using spreadsheets seeded with faults using mutation operators. The evaluation shows among other things that up to 93% of the first-order mutants and 98% of the second-order mutants were detected by the system using the automatically generated test cases.
Argument Schemes and Critical Questions for Decision Aiding Process
Authors: Wassila Ouerdane, Nicolas Maudet, Alexis Tsoukias
Venue: Proceeding of the 2008 conference on Computational Models of Argument: Proceedings of COMMA 2008 (2008)

Our ambition in this paper is to begin to specify in argumentative terms (some of) the steps involved in a decision-aiding process. To do that, we make use of the popular notion of argument schemes, and specify the related critical questions. A hierarchical structure of argument schemes allows to decompose the process into several distinct steps---and for each of them the underlying premises are made explicit, which allows in turn to identify how these steps can be dialectically defeated via critical questions. This work initiates a systematic study which aims at constituting a significant step forward for forthcoming decision-aiding tools. The kind of system that we foresee and sketch here would allow: (i) to present a recommendation that can be explicitly justified; (ii) to revise any piece of reasoning involved in this process, and be informed of the consequences of such moves; and possibly (iii) to stimulate the client by generating contradictory arguments.
A feature based approach to leveraging context for classifying newsgroup style discussion segments
Authors: Yi-Chia Wang, Mahesh Joshi, Carolyn Penstein Rosé
Venue: Proceedings of the 45th Annual Meeting of the ACL on Interactive Poster and Demonstration Sessions (2007)

On a multi-dimensional text categorization task, we compare the effectiveness of a feature based approach with the use of a state-of-the-art sequential learning technique that has proven successful for tasks such as "email act classification". Our evaluation demonstrates for the three separate dimensions of a well established annotation scheme that novel thread based features have a greater and more consistent impact on classification performance.