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  • 1999  (32)
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  • 1
    Electronic Resource
    Electronic Resource
    Preserving communication context: Virtual workspace and interpersonal space in Japanese CSCW (1999)
    Springer
    AI & society 13 (1999), S. 357-376 
    Details
    ISSN: 1435-5655
    Keywords: Context ; CSCW ; Culture ; Design ; Interface ; Japan ; Work
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract The past decade has seen the development of a perspective holding that technology is socially constructed. This paper examines the social construction of one group of technologies: systems for computer-supported cooperative work (CSCW). It describes the design of CSCW in Japan, with particular attention to the influence of culture on the design process. Two case studies are presented to illustrate the argument that culture is an important factor in technology design, despite commonly held assumptions about the neutrality and objectivity of science and technology. The paper further argues that, by looking at CSCW systems as texts which reflect the context of their production and the society from which they come, we may be better able to understand the transformations that operate when these texts are ‘read’ in the contexts of their implementation.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF01205983
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  • 2
    Electronic Resource
    Electronic Resource
    Why not Artificial Consciousness or Thought? (1999)
    Springer
    Minds and machines 9 (1999), S. 3-28 
    Details
    ISSN: 1572-8641
    Keywords: physical symbols ; formal programs ; neural networks ; designation ; interpretation ; representation ; semantics ; intensional meaning ; extensional meaning ; causal capacities ; emergence ; levels
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Philosophy
    Notes: Abstract The purpose of this article is to show why consciousness and thought are not manifested in digital computers. Analyzing the rationale for claiming that the formal manipulation of physical symbols in Turing machines would emulate human thought, the article attempts to show why this proved false. This is because the reinterpretation of ‘designation’ and ‘meaning’ to accommodate physical symbol manipulation eliminated their crucial functions in human discourse. Words have denotations and intensional meanings because the brain transforms the physical stimuli received from the microworld into a qualitative, macroscopic representation for consciousness. Lacking this capacity as programmed machines, computers have no representations for their symbols to designate and mean. Unlike human beings in which consciousness and thought, with their inherent content, have emerged because of their organic natures, serial processing computers or parallel distributed processing systems, as programmed electrical machines, lack these causal capacities.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1008374714117
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  • 3
    Electronic Resource
    Electronic Resource
    Hohfeld in cyberspace and other applications of normative reasoning in agent technology (1999)
    Springer
    Artificial intelligence and law 7 (1999), S. 81-96 
    Details
    ISSN: 1572-8382
    Keywords: agents ; user interface metaphors ; agent programming languages ; agent communication languages ; agent protocols ; Hohfeld ; formal theories of rights ; normative structures ; deontic logic ; groupware ; CSCW ; electronic commerce
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Law
    Notes: Abstract Two areas of importance for agents and multiagent systems are investigated: design of agent programming languages, and design of agent communication languages. The paper contributes in the above mentioned areas by demonstrating improved or novel applications for deontic logic and normative reasoning. Examples are taken from computer-supported cooperative work, and electronic commerce.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1008367514393
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  • 4
    Electronic Resource
    Electronic Resource
    Introduction: from legal theories to neural networks and fuzzy reasoning (1999)
    Springer
    Artificial intelligence and law 7 (1999), S. 115-128 
    Details
    ISSN: 1572-8382
    Keywords: analogy ; fuzzy logic ; learning ; legal formalism ; neural networks ; vagueness
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Law
    Notes: Abstract Computational approaches to the law have frequently been characterized as being formalistic implementations of the syllogistic model of legal cognition: using insufficient or contradictory data, making analogies, learning through examples and experiences, applying vague and imprecise standards. We argue that, on the contrary, studies on neural networks and fuzzy reasoning show how AI & law research can go beyond syllogism, and, in doing that, can provide substantial contributions to the law.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1008371600675
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  • 5
    Electronic Resource
    Electronic Resource
    Out of their minds: legal theory in neural networks (1999)
    Springer
    Artificial intelligence and law 7 (1999), S. 129-151 
    Details
    ISSN: 1572-8382
    Keywords: connectionism ; legal philosophy ; legal theory ; neural networks
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Law
    Notes: Abstract This paper examines the use of connectionism (neural networks) in modelling legal reasoning. I discuss how the implementations of neural networks have failed to account for legal theoretical perspectives on adjudication. I criticise the use of neural networks in law, not because connectionism is inherently unsuitable in law, but rather because it has been done so poorly to date. The paper reviews a number of legal theories which provide a grounding for the use of neural networks in law. It then examines some implementations undertaken in law and criticises their legal theoretical naïvete. It then presents a lessons from the implementations which researchers must bear in mind if they wish to build neural networks which are justified by legal theories.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1008301122056
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  • 6
    Electronic Resource
    Electronic Resource
    Object Recognition and Selective Handling by a Robot (1999)
    Springer
    Journal of intelligent and robotic systems 25 (1999), S. 121-132 
    Details
    ISSN: 1573-0409
    Keywords: invariant object recognition ; pattern recognition ; neural networks ; flexible manufacturing
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
    Notes: Abstract A small flexible production cell has been built around a selectively compliant articulated robot arm. Moving on a conveyor belt, boxes marked with different labels are presented to the robot in a random order. Using a camera and a vision card, the labels on the boxes are recognized. Each one of the labels can be rotated, translated or scaled. Three different invariant feature extraction methods (signature, invariant moments of Hu and Zernike) are compared. A neural net is used to classify the labels. The task of the SCARA robot is to pick up the moving boxes and to sort them according to their labels.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1008088209663
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  • 7
    Electronic Resource
    Electronic Resource
    Learning Complex Tasks Using a Stepwise Approach (1999)
    Springer
    Journal of intelligent and robotic systems 24 (1999), S. 43-68 
    Details
    ISSN: 1573-0409
    Keywords: learning robots ; system organization ; optimization ; physical equation ; look-ut table ; neural networks ; fuzzy controllers
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
    Notes: Abstract This paper explores a stepwise learning approach based on a system's decomposition into functional subsystems. Two case studies are examined: a visually guided robot that learns to track a maneuvering object, and a robot that learns to use the information from a force sensor in order to put a peg into a hole. These two applications show the features and advantages of the proposed approach: i) the subsystems naturally arise as functional components of the hardware and software; ii) these subsystems are building blocks of the robot behavior and can be combined in several ways for performing various tasks; iii) this decomposition makes it easier to check the performances and detect the cause of a malfunction; iv) only those subsystems for which a satisfactory solution is not available need to be learned; v) the strategy proposed for coordinating the optimization of all subsystems ensures an improvement at the task-level; vi) the overall system's behavior is significantly improved by the stepwise learning approach.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1008058131402
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  • 8
    Electronic Resource
    Electronic Resource
    Stable Neuro-Adaptive Control for Robots with the Upper Bound Estimation on the Neural Approximation Errors (1999)
    Springer
    Journal of intelligent and robotic systems 26 (1999), S. 91-100 
    Details
    ISSN: 1573-0409
    Keywords: robots ; neural networks ; adaptiveness ; stability ; approximation
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
    Notes: Abstract An indirect adaptive control approach is developed in this paper for robots with unknown nonlinear dynamics using neural networks (NNs). A key property of the proposed approach is that the actual joint angle values in the control law are replaced by the desired joint angles, angle velocities and accelerators, and the bound on the NN reconstruction errors is assumed to be unknown. Main theoretical results for designing such a neuro-controller are given, and the control performance of the proposed controller is verified with simulation studies.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1008195720685
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  • 9
    Electronic Resource
    Electronic Resource
    Genetic Tuning of PID Controllers Using a Neural Network Model: A Seesaw Example (1999)
    Springer
    Journal of intelligent and robotic systems 25 (1999), S. 43-59 
    Details
    ISSN: 1573-0409
    Keywords: PID control ; GAs ; neural networks ; multivariable systems
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
    Notes: Abstract When genetic algorithms (GAs) are applied for PID parameter tuning, since the PID parameters are adjusted almost randomly, it is possible that the plant will be damaged due to abrupt changes in PID parameters. To solve this problem, a neural network will be used to model the plant and the genetic tuning procedure will be performed on the neural network instead of the plant. After determining the PID parameters in this off-line manner, these gains are then applied to the plant for on-line control. Moreover, considering that the neural network model may not be accurate enough, a method is also proposed for on-line fine-tuning of PID parameters. To show the validity of the proposed method, a seesaw system that has one input and two outputs will be used for experimental evaluation
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1008077610571
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  • 10
    Electronic Resource
    Electronic Resource
    An Introduction to Variational Methods for Graphical Models (1999)
    Springer
    Machine learning 37 (1999), S. 183-233 
    Details
    ISSN: 0885-6125
    Keywords: graphical models ; Bayesian networks ; belief networks ; probabilistic inference ; approximate inference ; variational methods ; mean field methods ; hidden Markov models ; Boltzmann machines ; neural networks
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract This paper presents a tutorial introduction to the use of variational methods for inference and learning in graphical models (Bayesian networks and Markov random fields). We present a number of examples of graphical models, including the QMR-DT database, the sigmoid belief network, the Boltzmann machine, and several variants of hidden Markov models, in which it is infeasible to run exact inference algorithms. We then introduce variational methods, which exploit laws of large numbers to transform the original graphical model into a simplified graphical model in which inference is efficient. Inference in the simpified model provides bounds on probabilities of interest in the original model. We describe a general framework for generating variational transformations based on convex duality. Finally we return to the examples and demonstrate how variational algorithms can be formulated in each case.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1007665907178
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  • 11
    Electronic Resource
    Electronic Resource
    On the Sample Complexity for Nonoverlapping Neural Networks (1999)
    Springer
    Machine learning 37 (1999), S. 131-141 
    Details
    ISSN: 0885-6125
    Keywords: neural networks ; read-once formulas ; threshold gates ; sigmoidal gates ; PAC learning ; Vapnik-Chervonenkis dimension
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract A neural network is said to be nonoverlapping if there is at most one edge outgoing from each node. We investigate the number of examples that a learning algorithm needs when using nonoverlapping neural networks as hypotheses. We derive bounds for this sample complexity in terms of the Vapnik-Chervonenkis dimension. In particular, we consider networks consisting of threshold, sigmoidal and linear gates. We show that the class of nonoverlapping threshold networks and the class of nonoverlapping sigmoidal networks on n inputs both have Vapnik-Chervonenkis dimension Ω(nlog n). This bound is asymptotically tight for the class of nonoverlapping threshold networks. We also present an upper bound for this class where the constants involved are considerably smaller than in a previous calculation. Finally, we argue that the Vapnik-Chervonenkis dimension of nonoverlapping threshold or sigmoidal networks cannot become larger by allowing the nodes to compute linear functions. This sheds some light on a recent result that exhibited neural networks with quadratic Vapnik-Chervonenkis dimension.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1007609822199
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  • 12
    Electronic Resource
    Electronic Resource
    Rechnerunterstützung für Interaktionen zwischen Menschen Begriffsklärung, Anwendungsgebiete und Basiswerkzeuge (1999)
    Springer
    Informatik-Spektrum 22 (1999), S. 422-435 
    Details
    ISSN: 1432-122X
    Keywords: CSCW ; Groupware ; Teleteaching ; Workflow-Management ; Elektronischer Handel
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/s002870050149
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  • 13
    Electronic Resource
    Electronic Resource
    Neural Networks and Structured Knowledge: Knowledge Representation and Reasoning (1999)
    Springer
    Applied intelligence 11 (1999), S. 5-13 
    Details
    ISSN: 1573-7497
    Keywords: neural networks ; knowledge representation ; structured knowledge reasoning ; connectionism ; symbol processing ; hybrid systems
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract This collection of articles is the first of two parts of a special issue on “Neural Networks and Structured Knowledge.” The contributions to the first part shed some light on the issues of knowledge representation and reasoning with neural networks. Their scope ranges from formal models for mapping discrete structures like graphs or logical formulae onto different types of neural networks, to the construction of practical systems for various types of reasoning. In the second part to follow, the emphasis will be on the extraction of knowledge from neural networks, and on applications of neural networks and structured knowledge to practical tasks.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1008327412259
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  • 14
    Electronic Resource
    Electronic Resource
    Comparing Structures Using a Hopfield-Style Neural Network (1999)
    Springer
    Applied intelligence 11 (1999), S. 15-30 
    Details
    ISSN: 1573-7497
    Keywords: neural networks ; structured objects ; machine learning ; classification ; similarity ; nearest neighbor
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract Labeled graphs are an appropriate and popular representation of structured objects in many domains. If the labels describe the properties of real world objects and their relations, finding the best match between two graphs turns out to be the weakly defined, NP-complete task of establishing a mapping between them that maps similar parts onto each other preserving as much as possible of their overall structural correspondence. In this paper, former approaches of structural matching and constraint relaxation by spreading activation in neural networks and the method of solving optimization tasks using Hopfield-style nets are combined. The approximate matching task is reformulated as the minimization of a quadratic energy function. The design of the approach enables the user to change the parameters and the dynamics of the net so that knowledge about matching preferences is included easily and transparently. In the last section, some examples demonstrate the successful application of this approach in classification and learning in the domain of organic chemistry.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1008320413168
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  • 15
    Electronic Resource
    Electronic Resource
    Visualizing Common Artefacts to Support Awareness in Computer-Mediated Cooperation (1999)
    Springer
    Computer supported cooperative work 8 (1999), S. 207-238 
    Details
    ISSN: 1573-7551
    Keywords: awareness ; common artefact ; CSCW ; distortion ; notification ; state presentation
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract The idea of a “common artefact” is a useful metaphor for the design of CSCW systems. Our ACCT model of a common artefact describes structural elements that provide awareness about the work of others. The ACCT model identifies actors, contents, conversations, and tools as the central components of a common artefact, arranged on a shared background. The elements of a common artefact provide both a background visualization of the activity, but also permit dynamic notification of particular events. We explore this process of notification, which is composed of a selection and a presentation stage. We identify the critical factors of the process, in particular we highlight techniques related to temporal and spatial distortion. The framework helps to prepare design decisions of multi-user systems more consciously.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1008608425504
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  • 16
    Electronic Resource
    Electronic Resource
    Exploiting Hierarchy in Text Categorization (1999)
    Springer
    Information retrieval 1 (1999), S. 193-216 
    Details
    ISSN: 1573-7659
    Keywords: information retrieval ; text mining ; topic spotting ; text categorization ; knowledge management ; problem decomposition ; machine learning ; neural networks ; probabilistic models ; hierarchical models ; performance evaluation
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract With the recent dramatic increase in electronic access to documents, text categorization—the task of assigning topics to a given document—has moved to the center of the information sciences and knowledge management. This article uses the structure that is present in the semantic space of topics in order to improve performance in text categorization: according to their meaning, topics can be grouped together into “meta-topics”, e.g., gold, silver, and copper are all metals. The proposed architecture matches the hierarchical structure of the topic space, as opposed to a flat model that ignores the structure. It accommodates both single and multiple topic assignments for each document. Its probabilistic interpretation allows its predictions to be combined in a principled way with information from other sources. The first level of the architecture predicts the probabilities of the meta-topic groups. This allows the individual models for each topic on the second level to focus on finer discriminations within the group. Evaluating the performance of a two-level implementation on the Reuters-22173 testbed of newswire articles shows the most significant improvement for rare classes.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1009983522080
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  • 17
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    A Re-Engineering, Methodology for Cooperative Management of Enterprise Networks (1999)
    Springer
    Journal of network and systems management 7 (1999), S. 105-126 
    Details
    ISSN: 1573-7705
    Keywords: ENTERPRISE NETWORKS ; CSCW ; NETWORK AND SYSTEMS MANAGEMENT ; REENGINEERING ; MANAGEMENT PROCESSES
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract With the increasing implementation by networkedmission-critical applications, an enterprise network isbecoming the lifeline of an organization. Massiveinvestments are being made in the modernization of enterprise networks of diverse serviceorganizations, such as telecommunications andhealth-care providers. Organizations need to adapt tochanging business environment, such as the deregulationof telecommunication services. This necessitates a seamlessintegration of business management processes withenterprise network management processes. Hence there isa need for the formulation of new methodologies for there-engineering of management solutions (with focus onintegrated business processes), though most present daysolutions concentrate on the management of networkequipment only. This paper presents a new methodologyfor the reengineering of the management processesfor enterprise networks, based on Computer SupportedCooperative Work (CSCW) techniques.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1018769917171
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  • 18
    Electronic Resource
    Electronic Resource
    Medical Data Mining on the Internet: Research on a Cancer Information System (1999)
    Springer
    Artificial intelligence review 13 (1999), S. 437-466 
    Details
    ISSN: 1573-7462
    Keywords: CancerLit ; concept spaces ; data mining ; Hopfield net ; information retrieval ; Kohonen net ; medical knowledge ; neural networks
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract This paper discusses several data mining algorithms and techniques thatwe have developed at the University of Arizona Artificial Intelligence Lab.We have implemented these algorithms and techniques into severalprototypes, one of which focuses on medical information developed incooperation with the National Cancer Institute (NCI) and the University ofIllinois at Urbana-Champaign. We propose an architecture for medicalknowledge information systems that will permit data mining across severalmedical information sources and discuss a suite of data mining tools that weare developing to assist NCI in improving public access to and use of theirexisting vast cancer information collections.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1006548623067
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  • 19
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    A Hybrid Architecture for Situated Learning of Reactive Sequential Decision Making (1999)
    Springer
    Applied intelligence 11 (1999), S. 109-127 
    Details
    ISSN: 1573-7497
    Keywords: hybrid models ; sequential decision making ; neural networks ; reinforcement learning ; cognitive modeling
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract In developing autonomous agents, one usually emphasizes only (situated) procedural knowledge, ignoring more explicit declarative knowledge. On the other hand, in developing symbolic reasoning models, one usually emphasizes only declarative knowledge, ignoring procedural knowledge. In contrast, we have developed a learning model CLARION, which is a hybrid connectionist model consisting of both localist and distributed representations, based on the two-level approach proposed in [40]. CLARION learns and utilizes both procedural and declarative knowledge, tapping into the synergy of the two types of processes, and enables an agent to learn in situated contexts and generalize resulting knowledge to different scenarios. It unifies connectionist, reinforcement, and symbolic learning in a synergistic way, to perform on-line, bottom-up learning. This summary paper presents one version of the architecture and some results of the experiments.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1008332731824
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  • 20
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    A Neural Network Diagnosis Approach for Analog Circuits (1999)
    Springer
    Applied intelligence 11 (1999), S. 169-186 
    Details
    ISSN: 1573-7497
    Keywords: neural networks ; multiple fault diagnosis ; analog circuits
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract This paper presents a neural network system for the diagnosis of analog circuits and shows how the performance of such a system can be affected by the choice of different techniques used by its submodules. In particular we discuss the influence of feature extraction techniques such as Fourier Transforms, Wavelets and Principal Component Analysis. The system uses several different power supplies and as many neural networks “in parallel”. Two different algorithms that can be used to combine the candidate sets produced by each network are also presented. The system is capable of diagnosing multiple faults even if trained on single ones.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1008376430315
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  • 21
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    A New Symmetric Probabilistic Encryption Scheme Based on Chaotic Attractors of Neural Networks (1999)
    Springer
    Applied intelligence 10 (1999), S. 71-84 
    Details
    ISSN: 1573-7497
    Keywords: encryption ; chaotic attractors ; neural networks ; symmetric-key
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract A new probabilistic symmetric-key encryption scheme based on chaotic-classified properties of Hopfield neural networks is described. In an overstoraged Hopfield Neural Network (OHNN) the phenomenon of chaotic-attractors is well documented and messages in the attraction domain of an attractor are unpredictably related to each other. By performing permutation operations on the neural synaptic matrix, several interesting chaotic-classified properties of OHNN were found and these were exploited in developing a new cryptography technique. By keeping the permutation operation of the neural synaptic matrix as the secret key, we introduce a new probabilistic encryption scheme for a symmetric-key cryptosystem. Security and encryption efficiency of the new scheme are discussed.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1008337631906
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  • 22
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    Fusion Via a Linear Combination of Scores (1999)
    Springer
    Information retrieval 1 (1999), S. 151-173 
    Details
    ISSN: 1573-7659
    Keywords: linear combination ; fusion ; neural networks ; routing ; performance evaluation
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract We present a thorough analysis of the capabilities of the linear combination (LC) model for fusion of information retrieval systems. The LC model combines the results lists of multiple IR systems by scoring each document using a weighted sum of the scores from each of the component systems. We first present both empirical and analytical justification for the hypotheses that such a model should only be used when the systems involved have high performance, a large overlap of relevant documents, and a small overlap of nonrelevant documents. The empirical approach allows us to very accurately predict the performance of a combined system. We also derive a formula for a theoretically optimal weighting scheme for combining 2 systems. We introduce d—the difference between the average score on relevant documents and the average score on nonrelevant documents—as a performance measure which not only allows mathematical reasoning about system performance, but also allows the selection of weights which generalize well to new documents. We describe a number of experiments involving large numbers of different IR systems which support these findings.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1009980820262
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  • 23
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    Sharrock and Button ... and Much Ado about Nothing (1999)
    Springer
    Computer supported cooperative work 8 (1999), S. 285-293 
    Details
    ISSN: 1573-7551
    Keywords: CSCW ; critical theory ; deconstruction ; ideal speech situation ; social action theory
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract The paper discusses Sharrock's and Button's criticism of our attempt to use Habermas' communicative action theory to analyze group work platforms. We demonstrate that they misconstrue our goals of the paper, misinterpret our analysis of Habermas' action types, and misunderstand the concept of critical science. At the end we question the usefulness of these types of debates in furthering CSCW research.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1008720609782
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  • 24
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    The Invisible World of Intermediaries: A Cautionary Tale (1999)
    Springer
    Computer supported cooperative work 8 (1999), S. 147-167 
    Details
    ISSN: 1573-7551
    Keywords: CSCW ; electronic commerce ; intermediary ; digital library ; electronic community ; costomer support ; librarians ; notes ; trust
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract Many observers consider traditional intermediaries such as brokers, lenders and salespersons anachronisms in a world where consumers can communicate directly with providers of products and services over computer networks. Under the same rubric, information mediators such as journalists, editors, librarians and customer support representatives are being targeted for elimination. Drawing on our ethnographically-informed studies of customer support analysts and librarians, we demonstrate that the expertise and experience of intermediaries is often invisible – to the consumer, to the organization in which these intermediaries work, and even to the intermediaries' managers. The valuable services provided by intermediaries are not made unnecessary by end-user access. We argue for a richer understanding of intermediation, and a reallocation of functions and roles in which “new intermediaries” – people, software or a combination of the two – aggregate, personalize and assure the quality of information.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1008696415354
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    Neural Networks in Non-Euclidean Spaces (1999)
    Springer
    Neural processing letters 10 (1999), S. 201-210 
    Details
    ISSN: 1573-773X
    Keywords: neural networks ; learning ; minimal distance methods ; similarity-based methods ; machine learning ; interpretation of neural functions ; classification
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract Multilayer Perceptrons (MLPs) use scalar products to compute weighted activation of neurons providing decision borders using combinations of soft hyperplanes. The weighted fun-in activation function may be replaced by a distance function between the inputs and the weights, offering a natural generalization of the standard MLP model. Non-Euclidean distance functions may also be introduced by normalization of the input vectors into an extended feature space. Both approaches influence the shapes of decision borders dramatically. An illustrative example showing these changes is provided.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1018728407584
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    A New Relaxation Procedure in the Hopfield Network for Solving Optimization Problems (1999)
    Springer
    Neural processing letters 10 (1999), S. 211-222 
    Details
    ISSN: 1573-773X
    Keywords: constraint satisfaction ; Hopfield network ; neural networks ; optimization ; relaxation procedure
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract When solving an optimization problem with a Hopfield network, a solution is obtained after the network is relaxed to an equilibrium state. The relaxation process is an important step in achieving a solution. In this paper, a new procedure for the relaxation process is proposed. In the new procedure, the amplified signal received by a neuron from other neurons is treated as the target value for its activation (output) value. The activation of a neuron is updated directly based on the difference between its current activation and the received target value, without using the updating of the input value as an intermediate step. A relaxation rate is applied to control the updating scale for a smooth relaxation process. The new procedure is evaluated and compared with the original procedure in the Hopfield network through simulations based on 200 randomly generated instances of the 10-city traveling salesman problem. The new procedure reduces the error rate by 34.6% and increases the percentage of valid tours by 194.6% as compared with the original procedure.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1018780424422
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    Performance Analysis of Neural Network Detectors by Importance Sampling Techniques (1999)
    Springer
    Neural processing letters 9 (1999), S. 257-269 
    Details
    ISSN: 1573-773X
    Keywords: detectors ; detection and false alarm probabilities ; importance sampling techniques ; Monte Carlo simulations ; neural networks
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract Often, Neural Networks are involved in binary detectors of communication, radar or sonar systems. The design phase of a neural network detector usually requires the application of Monte Carlo trials in order to estimate some performance parameters. The classical Monte Carlo method is suitable to estimate high event probabilities (higher than 0.01), but not suitable to estimate very low event probabilities (say, 10−5 or less). For estimations of very low false alarm probabilities (or error probabilities), a modified Monte Carlo technique, the so-called Importance Sampling (IS) technique, is considered in this paper; some topics are developed, such as optimal and suboptimal IS probability density functions (biasing density functions), control parameters and new algorithms for the minimization of the estimator error. The main novelty of this paper is the application of an efficient IS technique on neural networks, drastically reducing the number of patterns required for testing events of low probability. As a practical application, the IS technique is applied to a neural detector on a radar (or sonar) system.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1018612207016
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    A Neural-Network-Based Approach to Detecting Hyperellipsoidal Shells (1999)
    Springer
    Neural processing letters 9 (1999), S. 279-292 
    Details
    ISSN: 1573-773X
    Keywords: cluster analysis ; neural networks ; shell detection
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract This paper presents a novel class of neural networks which can be trained in an unsupervised manner to detect a mixture of hyperellipsoidal shells and/or segments of hyperellipsoidal shells. This approach is computationally and implementationally simpler than other clustering algorithms that have been suggested for this purpose. Experimental results on several data sets are presented.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1018676508833
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    A Multilayer Perceptrons Model for the Stability of a Bipedal Robot (1999)
    Springer
    Neural processing letters 9 (1999), S. 221-227 
    Details
    ISSN: 1573-773X
    Keywords: dynamical equilibrium ; walking robots ; neural networks ; Levenberg-Marquardt's rules
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract A neural network model is proposed as a means of controlling the dynamical equilibrium of a walking bipedal robot. As a criterion to determine the stability of such a robot in relation with the organization of the sensorimotor system, we have been making use of the ZMP (Zero Momentum Point). Simulations are used to check the convergence of the algorithm. In the generalization phase, it is shown that the neural network has the ability to stabilise the robot for motions which have not previously been learned. An extended model is proposed, which seeks to closely inspect the physiology of the cerebellar cortex.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1018631315677
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    System Thoughts in Manufacturing (1999)
    Springer
    Journal of systems integration 9 (1999), S. 167-185 
    Details
    ISSN: 1573-8787
    Keywords: flexibility ; complexity ; systems approach ; taxonomy
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract In this paper we present a taxonomy of manufacturing problems, labeled in a general sense as Design, Production, or Distribution problems. One or more basic systems concepts, such as complexity and adaptation, attach themselves to each such problems. By combining the hierarchical Design—Production—Distribution idea with system concepts, we establish the fact that there is, indeed, a significant systems component to most problems of modern manufacturing.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1008422627181
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    An active worlds interface to Basic Support for Cooperative Working (BSCW) to enhance chance encounters (1999)
    Springer
    Virtual reality 4 (1999), S. 4-14 
    Details
    ISSN: 1434-9957
    Keywords: CSCW ; Shared spaces ; Chance encounters ; BSCW ; Active Worlds
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract New ways of working, as exemplified by distance learning, telecommuting and the virtual organisation, are growing in popularity. This paper concerns itself with the role that 3D virtual environments can play in assisting such collaborative working. Specifically,chance encounters have been shown to be important in collaboration, that is, encounters that are not pre-arranged by its participants. There are a number of tools to facilitate encounters online, but these create new problems. It is argued that 3D shared spaces can assist in the management of chance encounters, allowing them to create a situation similar to that found in the traditional workplace, in which tasks and content are situated inlocales. If shared 3D spaces are to have utility for computing in general, rather than specific applications, it is suggested that this may be in such spatial management of encounters. An example, in which Active Worlds is employed as an interface to Basic Support for Cooperative Working (BSCW) content is described. This content creates the motivation for users to be within the space, and thus available for chance encounters with other users; their nature and extent of being spatially coordinated.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF01434990
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    Learning of Sensor-Based Arm Motions while Executing High-Level Descriptions of Tasks (1999)
    Springer
    Autonomous robots 7 (1999), S. 57-75 
    Details
    ISSN: 1573-7527
    Keywords: sensor-based manipulators ; multi-goal reaching tasks ; reinforcement learning ; neural networks ; differential inverse kinematics
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
    Notes: Abstract Our work focuses on making an autonomous robot manipulator learn suitable collision-free motions from local sensory data while executing high-level descriptions of tasks. The robot arm must reach a sequence of targets where it undertakes some manipulation. The robot manipulator has a sonar sensing skin covering its links to perceive the obstacles in its surroundings. We use reinforcement learning for that purpose, and the neural controller acquires appropriate reaction strategies in acceptable time provided it has some a priori knowledge. This knowledge is specified in two main ways: an appropriate codification of the signals of the neural controller—inputs, outputs and reinforcement—and decomposition of the learning task. The codification facilitates the generalization capabilities of the network as it takes advantage of inherent symmetries and is quite goal-independent. On the other hand, the task of reaching a certain goal position is decomposed into two sequential subtasks: negotiate obstacles and move to goal. Experimental results show that the controller achieves a good performance incrementally in a reasonable time and exhibits high tolerance to failing sensors.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1008969830273
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