ppxscal/embedding_network huggingface dataset:
Database management issues in the web environment
Authors: J. F. Aldana Montes, A. C. Gómez Lora, N. Moreno Vergara, M. M. Roldán Garcia
Venue: Effective databases for text & document management (2003)

The focus of this chapter is on the progressive adaptation of database techniques to Web usage in a way quite similar to the evolution from integrated file management systems to database management systems. We review related and open issues, such as the semi-structured data and XML, integrity problem, query optimization problem, and integration issues in both the Web and Semantic Web environments. The representation of meta-information along with data opens up a new way to automatically process Web information due to the use of explicit semantic information. We hope that researchers will take into account traditional database techniques and how they can assist new Web technologies. In this sense, the amalgamation of Web and database technology appears to be very promising.
Improving TCP Startup Performance Using Active Measurements: Algorithm and Evaluation
Authors: Ningning Hu, Peter Steenkiste
Venue: Proceedings of the 11th IEEE International Conference on Network Protocols (2003)

TCP Slow Start exponentially increases the congestion window size to detect the proper congestion window for a network path. This often results in significant packet loss, while breaking off Slow Start using a limited slow start threshold may lead to an overly conservative congestion window size. This problem is especially severe in high speed networks. In this paper we present a new TCP startup algorithm, called Paced Start, that incorporates an available bandwidth probing technique into the TCP startup algorithm. Paced Start is based on the observation that when we view the TCP startup sequence as a sequence of packet trains, the difference between the data packet spacing and the acknowledgement spacing can yield valuable information about the available bandwidth. Slow Start ignores this information, while Paced Start uses it to quickly estimate the proper congestion window for the path. For most flows, Paced Start transitions into congestion avoidance mode faster thanSlow Start, has a signi.cantly lower packet loss rate, and avoids the timeout that is often associated with Slow Start. This paper describes the Paced Start algorithm and uses simulation and real system experiments to characterize its properties.
Theoretical Foundations for Distributed Work: Multilevel, Incentive Theories to Address Current Dilemmas
Authors: Bret Swan, France Belanger, Mary Beth Watson-Manheim
Venue: Proceedings of the Proceedings of the 37th Annual Hawaii International Conference on System Sciences (HICSS'04) - Track 1 - Volume 1 (2004)

Distributed work literature has sought to explain why and under what conditions workers choose to use distributed work arrangements, but often has resulted in contradictions and dilemmas. The literature has reached the point where significant progress can be made by applying existing organizational theories to explain past distributed work dilemmas and to serveas a foundation for future research. We propose a multilevel conceptual framework integratingconstructs from several well-established incentive-related organizational theories:: Hertzberg's theories on explicit and implicit motivation, expectancy theory, managerial control theory, group process theories, socio-technical systems theory, and resource allocation theories. From this integrated conceptual framework, we derive functional models to explain why workers do not take advantage of distributed work arrangements in two high tech sales organizations. Results illustrate the compounding effects of multiple incentives and disincentives over time and across levels of analysis. This theory-based conceptual framework extends both the distributed work and incentive literatures helping them overcome dilemmas existing between research and practice.
Towards an attentive robotic dialog partner
Authors: Torsten Wilhelm, Hans-Joachim Böhme, Horst-Michael Gross
Venue: Proceedings of the 5th international conference on Multimodal interfaces (2003)

This paper describes a system developed for a mobile service robot which detects and tracks the position of a user's face in 3D-space using a vision (skin color) and a sonar based component. To make the skin color detection robust under varying illumination conditions, it is supplied with an automatic white balance algorithm. The hypothesis of the user's position is used to orient the robot's head towards the current user allowing it to grab high resolution images of his face suitable for verifying the hypothesis and for extracting additional information.
Entropy Formulation for Parabolic Degenerate Equations with General Dirichlet Boundary Conditions and Application to the Convergence of FV Methods
Authors: Anthony Michel, Julien Vovelle
Venue: SIAM Journal on Numerical Analysis (2003)

This paper is devoted to the analysis and the approximation of parabolic hyperbolic degenerate problems defined on bounded domains with nonhomogeneous boundary conditions. It consists of two parts. The first part is devoted to the definition of an original notion of entropy solutions to the continuous problem, which can be adapted to define a notion of measure-valued solutions, or entropy process solutions. The uniqueness of such solutions is established. In the second part, the convergence of the finite volume method is proved. This result relies on (weak) estimates and on the theorem of uniqueness of the first part. It also entails the existence of a solution to the continuous problem.
Curricular projects of the ACM two-year college education committee
Authors: Robert D. Campbell, Elizabeth K. Hawthorne, Karl J. Klee
Venue: ACM SIGCSE Bulletin (2003)

This poster presentation showcases the recent accomplishments of the Two-Year College Education Committee, a standing committee of the ACM Education Board.
An authentication scheme for mobile satellite communication systems
Authors: Min-Shiang Hwang, Chao-Chen Yang, Cheng-Yeh Shiu
Venue: ACM SIGOPS Operating Systems Review (2003)

This paper discusses the security aspects of a registration protocol in a mobile satellite communication system. We propose a new mobile user authentication and data encryption scheme for mobile satellite communication systems. The scheme can remedy a replay attack.
Mobile agent based pervasive systems manager for enterprise network
Authors: Sandeep Adwankar, Venu Vasudevan
Venue: Proceedings of the 2003 ACM symposium on Applied computing (2003)

Mobile wireless devices are rapidly becoming part of the personal computing with advances in the broadband wireless networks. These devices though, have serious resource constraints to perform truly complex enterprise tasks such as managing an enterprise network. A distributed adaptive systems infrastructure is needed to enable these mobile devices as extensions of the enterprise-computing platform. This paper presents a pervasive systems manager that enables mobile devices to manage mid sized enterprise networks from anywhere, anytime. Mobile agents based pervasive systems manager allows device to initiate complex customized management actions. The paper describes architecture, implementation and experimental results of management action initiation, execution and dispatch of the enterprise systems management information to mobile devices.
Log Correlation for Intrusion Detection: A Proof of Concept
Authors: Cristina Abad, Jed Taylor, Cigdem Sengul, William Yurcik, Yuanyuan Zhou, Ken Rowe
Venue: Proceedings of the 19th Annual Computer Security Applications Conference (2003)

Intrusion detection is an important part of networked-systems security protection. Although commercial productsexist, finding intrusions has proven to be a difficult task withlimitations under current techniques. Therefore, improvedtechniques are needed. We argue the need for correlatingdata among different logs to improve intrusion detectionsystems accuracy. We show how different attacks are reflected in different logs and argue that some attacks are notevident when a single log is analyzed. We present experimental results using anomaly detection for the virus Yaha.Through the use of data mining tools (RIPPER) and correlation among logs we improve the effectiveness of an intrusion detection system while reducing false positives.
Fractional order dynamics in a GA planner
Authors: E. J. Solteiro Pires, J. A. Tenreiro Machado, P. B. de Moura Oliveira
Venue: Signal Processing (2003)

This work addresses the signal propagation and the fractional-order dynamics during, the evolution of a genetic algorithm (GA), for generating a robot manipulator trajectory. The GA objective is to minimize the trajectory space/time ripple without exceeding the torque requirements. In order to investigate the phenomena involved in the GA population evolution, the mutation is exposed to excitation perturbations and the corresponding fitness variations are evaluated. The chaos-like noise and the input/output signals are studied revealing a fractional-order dynamics, characteristic of a long-term system memory.
Safe as mother's milk: the Hanford project
Authors: Kim Stringfellow
Venue: ACM SIGGRAPH 2003 Web Graphics (2003)

Safe As Mother's Milk: The Hanford Project is a web site and physical installation exploring the atomic history of the Hanford Nuclear Reservation. For more than forty years, Hanford released radioactive materials into the environment on an uninformed public while producing plutonium for America's nuclear arsenal during the Cold War era. The project incorporates recently declassified documents and historical photographs available online through Hanford Declassified Document Retrieval System.
Learning-assisted automated planning: looking back, taking stock, going forward
Authors: Terry Zimmerman, Subbarao Kambhampati
Venue: AI Magazine (2003)

This article reports on an extensive survey and analysis of research work related to machine learning as it applies to automated planning over the past 30 years. Major research contributions are broadly characterized by learning method and then descriptive subcategories. Survey results reveal learning techniques that have extensively been applied and a number that have received scant attention. We extend the survey analysis to suggest promising avenues for future research in learning based on both previous experience and current needs in the planning community.
Classification and feature selection applied to breast cancer diagnosis
Authors: Olvi Managasarian
Venue: ACM SIGBIO Newsletter (1998)

Mathematical programming techniques are applied to the problems of classification, feature selection and clustering. The resulting classification and feature selection algorithms have been applied to the problem of breast cancer diagnosis. The clustering algorithms have been applied to the problem of grouping breast cancer patients with similar prognosis, as determined by survival curves (Kaplan-Meier).
On the Automaticity of Genetic Programming
Authors: Neville Melvin, Robert Soricone, James Waslo
Venue: Proceedings of the 14th International Conference on Electronics, Communications and Computers (2004)

Genetic/evolutionary algorithms, based uponan analogy to the mechanics of Mendeliangenetics and Darwinian evolutionary theory, offeran automatic way to improve programs. Theprocess cycles many times, selecting forreproduction among a population of programvariants (represented by the "chromosomes") toform the next generation, with "mutation" and"crossover" producing additional variation. Thisapproach was tested in such classic problems asfunction evolution, function maximization, and theTraveling Salesman problem. While the basicapproach proved powerful, its implementationrequired a non-automatic series of choices withrespect to the parameters for the algorithm itself,the representation of chromosomes, the meaningsof mutation and crossover, the possibility of othermechanisms such as "inversion", and theevaluation of the fitness of the reproductivecandidates. The most important message is thatdespite the automatic nature of the algorithmitself, knowledge of the problem domain isimportant to its implementation.
Dynamic cluster reconfiguration for power and performance
Authors: Eduardo Pinheiro, Ricardo Bianchini, Enrique V. Carrera, Taliver Heath
Venue: Compilers and operating systems for low power (2003)

In this chapter we address power conservation for clusters of workstations or PCs. Our approach is to develop systems that dynamically turn cluster nodes on - to be able to handle the load imposed on the system efficiently - and off - to save power under lighter load. The key component of our systems is an algorithm that makes cluster reconfiguration decisions by considering the total load imposed on the system and the power and performance implications of changing the current configuration. The algorithm is implemented in two common cluster-based systems: a network server and an operating system for clustered cycle servers. Our experimental results are very favorable, showing that our systems conserve both power and energy in comparison to traditional systems.
Text classification from positive and unlabeled documents
Authors: Hwanjo Yu, ChengXiang Zhai, Jiawei Han
Venue: Proceedings of the twelfth international conference on Information and knowledge management (2003)

Most existing studies of text classification assume that the training data are completely labeled. In reality, however, many information retrieval problems can be more accurately described as learning a binary classifier from a set of incompletely labeled examples, where we typically have a small number of labeled positive examples and a very large number of unlabeled examples. In this paper, we study such a problem of performing Text Classification WithOut labeled Negative data TC-WON). In this paper, we explore an efficient extension of the standard Support Vector Machine (SVM) approach, called SVMC (Support Vector Mapping Convergence) [17]for the TC-WON tasks. Our analyses show that when the positive training data is not too under-sampled, SVMC significantly outperforms other methods because SVMC basically exploits the natural "gap" between positive and negative documents in the feature space, which eventually corresponds to improving the generalization performance. In the text domain there are likely to exist many gaps in the feature space because a document is usually mapped to a sparse and high dimensional feature space. However, as the number of positive training data decreases, the boundary of SVMC starts overfitting at some point and end up generating very poor results.This is because when the positive training data is too few, the boundary over-iterates and trespasses the natural gaps between positive and negative class in the feature space and thus ends up fitting tightly around the few positive training data.
Using an education oriented digital library to organize and present classes in computing and information
Authors: Lillian N. Cassel, John Impagliazzo, Deborah Knox, C. Lee Giles, Edward A. Fox, JAN Lee, Manuel A. Pérez-Quiñones
Venue: Proceedings of the 8th annual conference on Innovation and technology in computer science education (2003)

This demonstration allows conference attendees to gain experience in using the facilities of the NSF National Science Technology Engineering and Mathematics Education Digital Library (NSDL) to prepare and present College or university level classes.
Assessing Uncertainty in Reliability of Component-Based Software Systems
Authors: Katerina Goseva-Popstojanova, Sunil Kamavaram
Venue: Proceedings of the 14th International Symposium on Software Reliability Engineering (2003)

Many architecture-based software reliability models wereproposed in the past. Regardless of the accuracy of thesemodels, if a considerable uncertainty exists in the estimatesof the operational profile and components reliabilities then asignificant uncertainty exists in calculated software reliability.Therefore, the traditional way of estimating software reliabilityby plugging point estimates of unknown parameters into themodel may not be appropriate since it discards any variancedue to uncertainty of the parameters. In this paper we proposea methodology for uncertainty analysis of architecture-basedsoftware reliability models suitable for large complex componentbased applications and applicable throughout the softwarelife cycle. First, we describe different approaches to buildthe architecture based software reliability model and to estimateparameters. Then, we perform uncertainty analysis usingthe method of moments and Monte Carlo simulation which enableus to study how the uncertainty of parameters propagatesin the reliability estimate. Both methods are illustrated on twocase studies and compared using several criteria.
An integrated data base language
Authors: Naveen Prakash, Y. K. Sharma
Venue: ACM SIGPLAN Notices (1979)

In this document, a language, HYPOL is described. HYPOL represents efforts towards arriving atan integrated language, unified from the points of view of computation, data base definition/manipulation and access control. In arriving at this language the capability concept, as it exists in operating systems, has been used to define access control requirements of a user. Further, the relation has been treated as a sequentisl file of records with appropriste operations defined on it. The type data submodel of HYPOL defines, in a unified manner, the part of the data base seen by a user as well as his access rights over it. Facilities exist to dynamically create new data submodels or to destroy existing ones. Care has been taken to ensure that the language HYPOL helps in writing structured programs.
Adaptive AIFS in wireless LAN
Authors: A. Ksentini, A. Gueroui, M. Naimi
Venue: Network control and engineering for Qos, security and mobility II (2003)

The new medium access protocol proposed by the IEEE 802.11e group, namely EDCF (Enhanced Distributed Coordination Function) provides a best way to guarantee a Qos for real time and multimedia applications. However the parameters used in EDCF are static and don't takes into account the instantaneous wireless link fluctuation, and applications requirements. In this work, we propose a new MAC access protocol AAIFS (Adaptive Arbitration InterFrame Space), which dynamically adjusts the intrinsic MAC parameters to fit both the transported stream relevant priority and wireless link overload. AAIFS protocol provides (1) a wireless link conditions aware scheme based on the measured packet loss rate (2) a differentiate QoS provisioning scheme at the mobile node side, which aggregate the different traffic into 3 service classes (3) a fair medium exploitation between the some service class belonging to different nodes.
Fine-grain web site structure discovery
Authors: Valter Crescenzi, Paolo Merialdo, Paolo Missier
Venue: Proceedings of the 5th ACM international workshop on Web information and data management (2003)

Several techniques have been recently proposed to automatically derive web wrappers, i.e., programs that extract data from HTML pages, and transform them into a more structured format, typically in XML syntax. These techniques automatically induce a wrapper from a set of sample pages that share a common HTML template. An open issue, however, is how to collect suitable classes of sample pages to feed the wrapper inducer. Presently, the pages are chosen manually.In this paper, we tackle the problem of automatically discovering the main classes of pages offered by a site by exploring only a small, representative, portion of it. The web site model we propose describes the structure of the site as a graph whose nodes are classes of pages that share a common structure, and whose edges represent links among instances of the page classes. Using this model, we have developed an algorithm that accepts the url of an entry point to the target web site, visits a limited portion of the site, and produces an accurate model of the site structure. We also report on preliminary experiments performed on actual web sites, that have produced encouraging results.
Relationship-based clustering and cluster ensembles for high-dimensional data mining
Authors: Alexander Strehl
Venue:  (2002)

This dissertation takes a relationship-based approach to cluster analysis of high (1000 and more) dimensional data that side-steps the &lsquo;curse of dimensionality&rsquo; issue by working in a suitable similarity space instead of the original feature space. We propose two frameworks that leverage graph algorithms to achieve relationship-based clustering and visualization, respectively. In the visualization framework, the output from the clustering algorithm is used to reorder the data points so that the resulting permuted similarity matrix can be readily visualized in 2 dimensions, with clusters showing up as bands. Results on retail transaction, document (bag-of-words), and web-log data show that our approach can yield superior results while also taking additional balance constraints into account. The choice of similarity is a critical step in relationship-based clustering and this motivates our systematic comparative study of the impact of similarity measures on the quality of document clusters . The key findings of our experimental study are: (i) Cosine, correlation, and extended Jaccard similarities perform comparably; (ii) Euclidean distances do not work well; (iii) graph partitioning tends to be superior to k-means and SOMs especially when balanced clusters are desired; and (iv) performance curves generally do not cross. We also propose a cluster quality evaluation measure based on normalized mutual information and find an analytical relation between similarity measures. It is widely recognized that combining multiple classification or regression models typically provides superior results compared to using a single, well-tuned model. However, there are no well known approaches to combining multiple clusterings. The idea of combining cluster labelings without accessing the original features leads to a general knowledge reuse framework that we call cluster ensembles. We propose a formal definition of the cluster ensemble as an optimization problem. Taking a relationship-based approach we propose three effective and efficient combining algorithms for solving it heuristically based on a hypergraph model. Results on synthetic as well as real data-sets show that cluster ensembles can (i) improve quality and robustness, and (ii) enable distributed clustering, and (iii) speed up processing significantly with little loss in quality.