ppxscal/embedding_network huggingface dataset:
Strategies for Effective Shilling Attacks against Recommender Systems
Authors: Sanjog Ray, Ambuj Mahanti
Venue: Privacy, Security, and Trust in KDD: Second ACM SIGKDD International Workshop, PinKDD 2008, Las Vegas, NV, USA, August 24, 2008, Revised Selected Papers (2009)

One area of research which has recently gained importance is the security of recommender systems. Malicious users may influence the recommender system by inserting biased data into the system. Such attacks may lead to erosion of user trust in the objectivity and accuracy of the system. In this paper, we propose a new approach for creating attack strategies. Our paper explores the importance of target item and filler items in mounting effective shilling attacks. Unlike previous approaches, we propose strategies built specifically for user based and item based collaborative filtering systems. Our attack strategies are based on intelligent selection of filler items. Filler items are selected on the basis of the target item rating distribution. We show through experiments that our strategies are effective against both user based and item based collaborative filtering systems. Our approach is shown to provide substantial improvement in attack effectiveness over existing attack models.
Training Global Linear Models for Chinese Word Segmentation
Authors: Dong Song, Anoop Sarkar
Venue: Proceedings of the 22nd Canadian Conference on Artificial Intelligence: Advances in Artificial Intelligence (2009)

This paper examines how one can obtain state of the art Chinese word segmentation using global linear models. We provide experimental comparisons that give a detailed road-map for obtaining state of the art accuracy on various datasets. In particular, we compare the use of reranking with full beam search; we compare various methods for learning weights for features that are full sentence features, such as language model features; and, we compare an Averaged Perceptron global linear model with the Exponentiated Gradient max-margin algorithm.
Toward effective initialization for large-scale search spaces
Authors: Shahryar Rahnamayan, G. Gary Wang
Venue: WSEAS TRANSACTIONS on SYSTEMS (2009)

Nowadays, optimization problems with a few thousands of variables become more common. Population-based algorithms, such as Differential Evolution (DE), Particle Swarm Optimization (PSO), Genetic Algorithms (GAs), and Evolutionary Strategies (ES) are commonly used approaches to solve complex large-scale problems from science and engineering. These approaches all work with a population of candidate solutions. On the other hand, for high-dimensional problems, no matter what is the individuals' distribution, the population is highly sparse. Therefore, intelligent employment of individual candidates can play a crucial role to find optimal solution(s) faster. The most majority of population-based algorithms utilize pseudo-random population initialization when there is no a priori knowledge about the solution. In this paper, a center-based population initialization is proposed and investigated on seven benchmark functions. The obtained results are compared with the results of Normal, Pseudo Random, and Latin Hypercube population initialization schemes. Furthermore, the advantages of the proposed center-based sampling method are investigated by a mathematical proof and also Monte Carlo (simulation) method. The detailed experimental verifications are provided for problems with 50, 500, and 1000 dimensions.
Review article: Local adaptive receptive field self-organizing map for image color segmentation
Authors: Aluizio R. F. Araújo, Diogo C. Costa
Venue: Image and Vision Computing (2009)

A new self-organizing map with variable topology is introduced for image segmentation. The proposed network, called a Local Adaptive Receptive Field Self-organizing Map (LARFSOM), is a fast convergent network capable of color segmenting images satisfactorily, which has optimum self-adaptive topology and achieves good PSNR values. LARFSOM is compared to SOM, FS-SOM and GNG, self-organizing maps used for color segmentation. LARFSOM reached a higher color palette variance and a better 3D RGB color space distribution of learned data from the training images than the other models. LARFSOM was tested to segment images with different degrees of complexity and has given promising results.
A Cooperative Distributed Problem Solving Technique for Large Markov Decision Processes
Authors: Abdel-Illah Mouaddib, Simon Le Gloannec
Venue: Proceeding of the 2006 conference on ECAI 2006: 17th European Conference on Artificial Intelligence August 29 -- September 1, 2006, Riva del Garda, Italy (2006)

In this paper, we consider the problem of solving a large MDP in a distributed way among several processors. To do that, we propose an approach which decomposes the large MDP into smaller ones each of which is solved on a unique processor. The obtained joint local policies derived from the small MDPs (subMDPs) behave in the same way of the policy of the initial MDP.
A fuzzy clustering algorithm based on evolutionary programming
Authors: Hongbin Dong, Yuxin Dong, Cheng Zhou, Guisheng Yin, Wei Hou
Venue: Expert Systems with Applications: An International Journal (2009)

In this paper, a fuzzy clustering method based on evolutionary programming (EPFCM) is proposed. The algorithm benefits from the global search strategy of evolutionary programming, to improve fuzzy c-means algorithm (FCM). The cluster validity can be measured by some cluster validity indices. To increase the convergence speed of the algorithm, we exploit the modified algorithm to change the number of cluster centers dynamically. Experiments demonstrate EPFCM can find the proper number of clusters, and the result of clustering does not depend critically on the choice of the initial cluster centers. The probability of trapping into the local optima will be very lower than FCM.
Coordination analysis: a method for deriving use cases from process dependencies
Authors: Xiang Michelle Liu, George M. Wyner
Venue: Proceedings of the 4th International Conference on Design Science Research in Information Systems and Technology (2009)

Despite the widespread recognition that information technology (IT) and business process are tightly connected, existing system design methods provide limited guidance on how to take business process into account when designing information systems. The primary goal of this paper is to describe a method which helps systems analysts to explore more systematically the potential of IT to change the design of business processes. We use coordination theory to provide a theoretical connection between use cases and the dependencies among activities within a process. By building use cases from dependencies, we are able to consider a wide range of functionality for managing those dependencies and thus incorporate process redesign into the requirements process. We employ a healthcare case as an example to illustrate the proposed method.
An interactive strategic information management plan to integrate strategic and tactical information management in hospitals
Authors: Ulrike Mueller, Lutz Issler, Gert Funkat, Alfred Winter
Venue: Proceedings of the 2009 ICSE Workshop on Software Engineering in Health Care (2009)

The precondition for systematic information management is a strategic information management plan that has to be monitored constantly. In general, such a plan is a paper document that goes out of date fast, what reduces the acceptance among the users even faster. Moreover, in the majority of cases no systematic monitoring of whether the goals described in the SIM plan are achieved takes place during the validity period of the plan. The aim of the work described here was to publish the SIM plan as an interactive document, and in parallel to offer a possibility to monitor the plan's goals. To evaluate potentials and acceptance of different technological approaches, two alternative concepts were developed and compared.
An intrinsic study on a certain flow of a viscous compressible fluid, with extension to some cases in magneto-plasma dynamics part two: an extension to some special cases in magneto-plasma dynamics
Authors: Richard Selescu
Venue: Proceedings of the 10th WSEAS international conference on Mathematical and computational methods in science and engineering (2008)

This part of the work studies and clarifies some local phenomena in the viscous MHD and represents a continuation of a previous work [1]. The model from part one of the present work can be extended to some cases in magneto-plasma dynamics (taking into account the flow vorticity effects, those of the Joule-Lenz heat losses and the viscous ones), considering a non-isentropic flow of a barotropic viscous electroconducting fluid in an external magnetic field. Some surfaces of 0-work made by the non-conservative elementary forces with a special virtual elementary displacement vector were also introduced. In all treated cases the new found first integrals are similar to D. Bernoulli and D. Bernoulli-Lagrange ones. The differential equations of the virtual isentropic surfaces and those of Selescu's magneto-hydrodynamic - $ vector lines and virtual 0-work surfaces are also given.
Intelligent Layout Design for Complex Mechatronic Products Based on Distributed Knowledge
Authors: Caihong Wang, Jianzhong Cha, Yiping Lu, Wei Liu, Gang Li
Venue: Proceeding of the 2006 conference on Leading the Web in Concurrent Engineering: Next Generation Concurrent Engineering (2006)

As complex product layout problems are difficult to be solved with simplex optimum algorithms, an approach is introduced to implement intelligent human-computer interactive layout design system based on distributed knowledge for complex mechatronic products. A web-based system structure is represented also, which combines the merit of C/S and B/S. The layout design knowledge of complex products is divided into parts knowledge, space knowledge, layout case, rule knowledge and constraint knowledge. A compound knowledge model is set up by object oriented method, and data structure is described by array. This knowledge representation method makes the maintenance of knowledge base much easy.
Random key predistribution for wireless sensor networks using deployment knowledge
Authors: J. Jaworski, M. Ren, K. Rybarczyk
Venue: Computing (2009)

We consider a key distribution scheme for wireless sensor networks which uses deployment knowledge. Deployment is modeled as a grid of hexagonal clusters, into centers of which the sensor nodes are dropped according to a given probability distribution (e.g. a Gaussian one). We consider sensor connectivity in a random intersection graph model, instead of the more commonly used in literature G(n, p) graph model. While the latter is easier to analyze, the former is much more suitable to modeling sensor network key distribution. We provide analytical, asymptotic results showing how to pick parameters (key pool size |S|, the number of chosen keys d) depending on the number of deployed nodes in order to assure global connectivity of the network, and estimate the diameter of the network for the given parameters.
Social Currencies And Knowledge Currencies
Authors: Claudia Carrillo, Josep Lluis de la Rosa, Araceli Moreno, Eduard Muntaner, Sonia Delfin, Agustí Canals
Venue: Proceeding of the 2006 conference on Artificial Intelligence Research and Development (2006)

This paper describes the state of the art for social currencies and cognitive capitalism, which is used to found a new currency based on knowledge. This new currency better reflects the wealth of nations throughout the world, supports more social economic activity and is better adapted to the challenges of digital business ecosystems. The basic premise of the new currency is a knowledge measurement pattern that is formulated as a new alternative social currency. Therefore, it is a first step contributing to the worldwide evolution towards a knowledge society. It is a currency to facilitate the conservation and storage of knowledge, its organization and categorization, but chiefly its transference and exploitation. The proposal turns recommender agents into the new currency. An example is presented to show how recommender agents receive a new use, transforming them into objects of transaction.
Towards optimally exploiting physical layer information in OFDM wireless networks
Authors: Zheng Zeng, P. R. Kumar
Venue: Proceedings of the 4th Annual International Conference on Wireless Internet (2008)

Wireless communication is inherently vulnerable in nature and packets can be corrupted due to various reasons. The network performance can potentially be improved if one is able to identify the reasons for packet corruption and react to them accordingly. However, none of the current wireless protocols do so. In this paper, we design a novel scheme to diagnose packet corruption in OFDM wireless networks by statistically analyzing certain available physical layer information, based on the observation that different causes of corruption result in different per-symbol-SINR patterns within a packet. Our approach introduces no additional traffic overhead. By running experiments on a GNU radio test bed in an electromagnetic anechoic chamber, we study and demonstrate that one can separate three reasons for packet corruption: weak signal, interference from transmitters using the same band, and interference from transmitters using an adjacent band. We study three statistical classification methods and compare their accuracy.
Self-correlating predictive information tracking for large-scale production systems
Authors: Ying Zhao, Yongmin Tan, Zhenhuan Gong, Xiaohui Gu, Mike Wamboldt
Venue: Proceedings of the 6th international conference on Autonomic computing (2009)

Automatic management of large-scale production systems requires a continuous monitoring service to keep track of the states of the managed system. However, it is challenging to achieve both scalability and high information precision while continuously monitoring a large amount of distributed and time-varying metrics in large-scale production systems. In this paper, we present a new self-correlating, predictive information tracking system called InfoTrack, which employs lightweight temporal and spatial correlation discovery methods to minimize continuous monitoring cost. InfoTrack combines both metric value prediction within individual nodes and adaptive clustering among distributed nodes to suppress remote information update in distributed system monitoring. We have implemented a prototype of the InfoTrack system and deployed the system on the PlanetLab. We evaluated the performance of the InfoTrack system using both real system traces and micro-benchmark prototype experiments. The experimental results show that InfoTrack can reduce the continuous monitoring cost by 50-90% while maintaining high information precision (i.e., within 0.01-0.05 error bound).
Single-machine scheduling with sum-of-logarithm-processing-times-based learning considerations
Authors: T. C. E. Cheng, Peng-Jen Lai, Chin-Chia Wu, Wen-Chiung Lee
Venue: Information Sciences: an International Journal (2009)

Scheduling with learning effects has attracted growing attention of the scheduling research community. A recent survey classifies the learning models in scheduling into two types, namely position-based learning and sum-of-processing-times-based learning. However, the actual processing time of a given job drops to zero precipitously as the number of jobs increases in the first model and when the normal job processing times are large in the second model. Motivated by this observation, we propose a new learning model where the actual job processing time is a function of the sum of the logarithm of the processing times of the jobs already processed. The use of the logarithm function is to model the phenomenon that learning as a human activity is subject to the law of diminishing return. Under the proposed learning model, we show that the scheduling problems to minimize the makespan and total completion time can be solved in polynomial time. We further show that the problems to minimize the maximum lateness, maximum tardiness, weighted sum of completion times and total tardiness have polynomial-time solutions under some agreeable conditions on the problem parameters.
How to Qualitatively + Quantitatively Assess Concepts Maps: the case of COMPASS
Authors: Evangelia Gouli, Agoritsa Gogoulou, Kyparisia Papanikolaoy, Maria Grigoriadou
Venue: Proceeding of the 2005 conference on Artificial Intelligence in Education: Supporting Learning through Intelligent and Socially Informed Technology (2005)

This paper presents a scheme for the quantitative and qualitative assessment of concept maps in the context of a web-based adaptive concept map assessment tool, referred to as COMPASS. The propositions are characterized qualitatively based on specific criteria and on the error(s) that may be identified. The quantitative assessment depends on the weights assigned to the concepts/propositions and the error categories.
Risk control in strategic management projects
Authors: Claudia-Georgeta Carstea, Ioan-Gheorghe Ratiu, Neculai Patrascu, Marian Pearsica, Nicoleta David, Dana Damian, Lucian Patrascu
Venue: Proceedings of the 10th WSEAS international conference on Mathematical methods, computational techniques and intelligent systems (2008)

One of the most important targets of the leadership is preventing and identification of the errors and frauds. The cost of the possible control measures must be compared with the probability of appearance of such fraud or error and the consequences. The evaluation system offers the leaders the required data necessary for the administration of that business. But it's still the job of those being in charge to create and launch such a system. Risk quantification is the process of measuring the probability of a risk and its impact on project objectives. Unlike risk assessment, risk quantification aims to produce verifiable numerical values. Risk quantification typically uses techniques such as Monte Carlo simulation and decision analysis to determine the cost and schedule contingencies that will be required, based on the levels of uncertainty (= risk) in the various components of a project; to determine probabilities of completing within a certain cost or by a certain date; to identify realistic project targets (cost, schedule, functionality, quality).
Brief paper: Convergence properties of constrained linear system under MPC control law using affine disturbance feedback
Authors: Chen Wang, Chong-Jin Ong, Melvyn Sim
Venue: Automatica (Journal of IFAC) (2009)

This paper shows new convergence properties of constrained linear discrete time system with bounded disturbances under Model Predictive Control (MPC) law. The MPC control law is obtained using an affine disturbance feedback parametrization with an additional linear state feedback term. This parametrization has the same representative ability as some recent disturbance feedback parametrization, but its choice together with an appropriate cost function results in a different closed-loop convergence property. More exactly, the state of the closed-loop system converges to a minimal invariant set with probability one. Deterministic convergence to the same minimal invariant set is also possible if a less intuitive cost function is used. Numerical experiments are provided that validate the results.
Automatic dimension inference and checking for object-oriented programs
Authors: Sudheendra Hangal, Monica S. Lam
Venue: Proceedings of the 2009 IEEE 31st International Conference on Software Engineering (2009)

This paper introduces UniFi, a tool that attempts to automatically detect dimension errors in Java programs. UniFi infers dimensional relationships across primitive type and string variables in a program, using an inter-procedural, context-sensitive analysis. It then monitors these dimensional relationships as the program evolves, flagging inconsistencies that may be errors. UniFi requires no programmer annotations, and supports arbitrary program-specific dimensions, thus providing fine-grained dimensional consistency checking. UniFi exploits features of object-oriented languages, but can be used for other languages as well. We have run UniFi on real-life Java code and found that it is useful in exposing dimension errors. We present a case study of using UniFi on nightly builds of a 19,000 line code base as it evolved over 10 months.
When Cultures Meet: Modelling Cross-Cultural Knowledge Spaces
Authors: Anneli Heimbürger
Venue: Proceeding of the 2008 conference on Information Modelling and Knowledge Bases XIX (2008)

Cross-cultural research projects are becoming a norm in our global world. More and more projects are being executed using teams from eastern and western cultures. Cultural competence might help project managers to achieve project goals and avoid potential risks in cross-cultural project environments and would also support them to promote creativity and motivation through flexible leadership. In our paper we introduce an idea for constructing an information system, a cross-cultural knowledge space, which could support cross-cultural communication, collaborative learning experiences and time-based project management functions. The case cultures in our project are Finnish and Japanese. The system can be used both in virtual and in physical spaces for example to clarify cultural business etiquette. The core of our system design will be based on cross-cultural ontology, and the system implementation on XML technologies. Our approach is a practical, step-by-step example of constructive research. In our paper we shortly describe Hofstede's dimensions for assessing cultures as one example of a larger framework for our study. We also discuss the concept of time in cultural context.
The consumer loan default predicting model - An application of DEA-DA and neural network
Authors: Ming-Chun Tsai, Shu-Ping Lin, Ching-Chan Cheng, Yen-Ping Lin
Venue: Expert Systems with Applications: An International Journal (2009)

In this paper we construct the consumer loan default predicting model through conducting the empirical analysis on the customers of unsecured consumer loan from a certain financial institution in Taiwan, and adopt the borrower's demographic variables and money attitude as the real-timeaneous discriminant information. Furthermore, we construct respectively through four predicting methods, such as DA, LR, NN and DEA-DA, to compare the suitability of these four mentioned methods. The results show that DEA-DA and NN are possessed better predicting capability and they are the optimal predicting model that this study longing for. In addition, this study showed that the default loan predicting model will be possessed higher level of predicting capability after added money attitude.
A theory of contracts for strong service compliance
Authors: Mario Bravetti, Gianluigi Zavattaro
Venue: Mathematical Structures in Computer Science (2009)

We investigate, in a process algebraic setting, a new notion of correctness for service compositions, which we call strong service compliance: composed services are strong compliant if their composition is both deadlock and livelock free (this is the traditional notion of compliance), and whenever a message can be sent to invoke a service, it is guranteed to be ready to serve the invocation. We also define a new notion of refinement, called strong subcontract pre-order, suitable for strong compliance: given a composition of strong compliant services, we can replace any service with any other service in subcontract relation while preserving the overall strong compliance. Finally, we present a characterisation of the strong subcontract pre-order by resorting to the theory of a (should) testing pre-order.