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31,463
An Overview of Workflow Management: From Process Modeling to Workflow Automation Infrastructure
- DISTRIBUTED AND PARALLEL DATABASES
, 1995
"... Today’s business enterprises must deal with global competition, reduce the cost of doing business, and rapidly develop new services and products. To address these requirements enterprises must constantly reconsider and optimize the way they do business and change their information systems and appl ..."
Abstract
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Cited by 670 (26 self)
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and applications to support evolving business processes. Workflow technology facilitates these by providing methodologies and software to support (i) business process modeling to capture business processes as workflow specifications, (ii) business process reengineering to optimize specified processes, and (iii
SCRIBE: A large-scale and decentralized application-level multicast infrastructure
- IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS (JSAC
, 2002
"... This paper presents Scribe, a scalable application-level multicast infrastructure. Scribe supports large numbers of groups, with a potentially large number of members per group. Scribe is built on top of Pastry, a generic peer-to-peer object location and routing substrate overlayed on the Internet, ..."
Abstract
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Cited by 658 (29 self)
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This paper presents Scribe, a scalable application-level multicast infrastructure. Scribe supports large numbers of groups, with a potentially large number of members per group. Scribe is built on top of Pastry, a generic peer-to-peer object location and routing substrate overlayed on the Internet
A tutorial on support vector machines for pattern recognition
- Data Mining and Knowledge Discovery
, 1998
"... The tutorial starts with an overview of the concepts of VC dimension and structural risk minimization. We then describe linear Support Vector Machines (SVMs) for separable and non-separable data, working through a non-trivial example in detail. We describe a mechanical analogy, and discuss when SV ..."
Abstract
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Cited by 3393 (12 self)
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The tutorial starts with an overview of the concepts of VC dimension and structural risk minimization. We then describe linear Support Vector Machines (SVMs) for separable and non-separable data, working through a non-trivial example in detail. We describe a mechanical analogy, and discuss when
Sequential minimal optimization: A fast algorithm for training support vector machines
- Advances in Kernel Methods-Support Vector Learning
, 1999
"... This paper proposes a new algorithm for training support vector machines: Sequential Minimal Optimization, or SMO. Training a support vector machine requires the solution of a very large quadratic programming (QP) optimization problem. SMO breaks this large QP problem into a series of smallest possi ..."
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Cited by 461 (3 self)
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This paper proposes a new algorithm for training support vector machines: Sequential Minimal Optimization, or SMO. Training a support vector machine requires the solution of a very large quadratic programming (QP) optimization problem. SMO breaks this large QP problem into a series of smallest
Transductive Inference for Text Classification using Support Vector Machines
, 1999
"... This paper introduces Transductive Support Vector Machines (TSVMs) for text classification. While regular Support Vector Machines (SVMs) try to induce a general decision function for a learning task, Transductive Support Vector Machines take into account a particular test set and try to minimiz ..."
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Cited by 892 (4 self)
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to minimize misclassifications of just those particular examples. The paper presents an analysis of why TSVMs are well suited for text classification. These theoretical findings are supported by experiments on three test collections. The experiments show substantial improvements over inductive methods
Choosing multiple parameters for support vector machines
- MACHINE LEARNING
, 2002
"... The problem of automatically tuning multiple parameters for pattern recognition Support Vector Machines (SVMs) is considered. This is done by minimizing some estimates of the generalization error of SVMs using a gradient descent algorithm over the set of parameters. Usual methods for choosing para ..."
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Cited by 470 (17 self)
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The problem of automatically tuning multiple parameters for pattern recognition Support Vector Machines (SVMs) is considered. This is done by minimizing some estimates of the generalization error of SVMs using a gradient descent algorithm over the set of parameters. Usual methods for choosing
Tapestry: A Resilient Global-scale Overlay for Service Deployment
- IEEE Journal on Selected Areas in Communications
, 2004
"... We present Tapestry, a peer-to-peer overlay routing infrastructure offering efficient, scalable, locationindependent routing of messages directly to nearby copies of an object or service using only localized resources. Tapestry supports a generic Decentralized Object Location and Routing (DOLR) API ..."
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Cited by 598 (14 self)
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We present Tapestry, a peer-to-peer overlay routing infrastructure offering efficient, scalable, locationindependent routing of messages directly to nearby copies of an object or service using only localized resources. Tapestry supports a generic Decentralized Object Location and Routing (DOLR) API
The Player/Stage Project: Tools for Multi-Robot and Distributed Sensor Systems
- In Proceedings of the 11th International Conference on Advanced Robotics
, 2003
"... This paper describes the Player/Stage software tools applied to multi-robot, distributed-robot and sensor network systems. Player is a robot device server that provides network transparent robot control. Player seeks to constrain controller design as little as possible; it is device independent, non ..."
Abstract
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Cited by 622 (14 self)
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, non-locking and language- and style-neutral. Stage is a lightweight, highly configurable robot simulator that supports large populations. Player/Stage is a community Free Software project. Current usage of Player and Stage is reviewed, and some interesting research opportunities opened up
PVM: A Framework for Parallel Distributed Computing
- Concurrency: Practice and Experience
, 1990
"... The PVM system is a programming environment for the development and execution of large concurrent or parallel applications that consist of many interacting, but relatively independent, components. It is intended to operate on a collection of heterogeneous computing elements interconnected by one or ..."
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Cited by 788 (27 self)
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of various types of algorithms (and their interactions), while the underlying infrastructure permits the execution of applications on a virtual computing environment that supports multiple parallel computation models. PVM contains facilities for concurrent, sequential, or conditional execution of application
A survey of context-aware mobile computing research
, 2000
"... Context-aware computing is a mobile computing paradigm in which applications can discover and take advantage of contextual information (such as user location, time of day, nearby people and devices, and user activity). Since it was proposed about a decade ago, many researchers have studied this topi ..."
Abstract
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Cited by 692 (2 self)
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this topic and built several context-aware applications to demonstrate the usefulness of this new technology. Context-aware applications (or the system infrastructure to support them), however, have never been widely available to everyday users. In this survey of research on context-aware systems
Results 1 - 10
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31,463
