Results 1 - 10 of 54,177

A Survey on Sensor Networks

by Lan F. Akyildiz, Welljan Su, Yogesh Sankarasubramaniam, Erdal Cayirci , 2002
"... Recent advancement in wireless communica- tions and electronics has enabled the develop- ment of low-cost sensor networks. The sensor networks can be used for various application areas (e.g., health, military, home). For different application areas, there are different technical issues that research ..."
Abstract - Cited by 2002 (1 self) - Add to MetaCart
that researchers are currently resolving. The current state of the art of sensor networks is captured in this article, where solutions are discussed under their related protocol stack layer sections. This article also points out the open research issues and intends to spark new interests and developments

The Evolution of Social and Economic Networks

by Matthew O. Jackson, Alison Watts - JOURNAL OF ECONOMIC THEORY 106, 265–295 , 2002
"... We examine the dynamic formation and stochastic evolution of networks connecting individuals. The payoff to an individual from an economic or social activity depends on the network of connections among individuals. Over time individuals form and sever links connecting themselves to other individuals ..."
Abstract - Cited by 889 (37 self) - Add to MetaCart
individuals based on the improvement that the resulting network offers them relative to the current network. In addition to intended changes in the network there is a small probability of unintended changes or errors. Predictions can be made regarding the likelihood that the stochastic process will lead

Markov Logic Networks

by Matthew Richardson, Pedro Domingos - MACHINE LEARNING , 2006
"... We propose a simple approach to combining first-order logic and probabilistic graphical models in a single representation. A Markov logic network (MLN) is a first-order knowledge base with a weight attached to each formula (or clause). Together with a set of constants representing objects in the ..."
Abstract - Cited by 816 (39 self) - Add to MetaCart
We propose a simple approach to combining first-order logic and probabilistic graphical models in a single representation. A Markov logic network (MLN) is a first-order knowledge base with a weight attached to each formula (or clause). Together with a set of constants representing objects

Learning probabilistic relational models

by Nir Friedman, Lise Getoor, Daphne Koller, Avi Pfeffer - In IJCAI , 1999
"... A large portion of real-world data is stored in commercial relational database systems. In contrast, most statistical learning methods work only with "flat " data representations. Thus, to apply these methods, we are forced to convert our data into a flat form, thereby losing much ..."
Abstract - Cited by 613 (30 self) - Add to MetaCart
A large portion of real-world data is stored in commercial relational database systems. In contrast, most statistical learning methods work only with "flat " data representations. Thus, to apply these methods, we are forced to convert our data into a flat form, thereby losing much

Centrality in social networks conceptual clarification

by Linton C. Freeman - Social Networks , 1978
"... The intuitive background for measures of structural centrality in social networks is reviewed aPzd existing measures are evaluated in terms of their consistency with intuitions and their interpretability. Three distinct intuitive conceptions of centrality are uncovered and existing measures are refi ..."
Abstract - Cited by 1083 (2 self) - Add to MetaCart
are refined to embody these conceptions. Three measures are developed for each concept, one absolute and one relative measure of the ~entra~~t~ ~ of ~os~tio~ls in a network, and one relenting the degree of centralization of the entire network. The implications of these measures for the experimental study

Error and attack tolerance of complex networks

by Réka Albert, Hawoong Jeong, Albert-László Barabási , 2000
"... Many complex systems display a surprising degree of tolerance against errors. For example, relatively simple organisms grow, persist and reproduce despite drastic pharmaceutical or environmental interventions, an error tolerance attributed to the robustness of the underlying metabolic network [1]. C ..."
Abstract - Cited by 1013 (7 self) - Add to MetaCart
Many complex systems display a surprising degree of tolerance against errors. For example, relatively simple organisms grow, persist and reproduce despite drastic pharmaceutical or environmental interventions, an error tolerance attributed to the robustness of the underlying metabolic network [1

Learning and development in neural networks: The importance of starting small

by Jeffrey L. Elman - Cognition , 1993
"... It is a striking fact that in humans the greatest learnmg occurs precisely at that point in time- childhood- when the most dramatic maturational changes also occur. This report describes possible synergistic interactions between maturational change and the ability to learn a complex domain (language ..."
Abstract - Cited by 531 (17 self) - Add to MetaCart
(language), as investigated in con-nectionist networks. The networks are trained to process complex sentences involving relative clauses, number agreement, and several types of verb argument structure. Training fails in the case of networks which are fully formed and ‘adultlike ’ in their capacity. Training

Secure Routing for Mobile Ad Hoc Networks

by Panagiotis Papadimitratos, Zygmunt Haas - MOBILE COMPUTING AND COMMUNICATIONS REVIEW , 2002
"... For such self-organizing infrastructures as mobile ad hoc networks , envisioned to operate in an open, collaborative, and highly volatile environment, the importance of secu- rity cannot be underrated. The provision of comprehen- sive secure communication mandates that both route dis- covery and dat ..."
Abstract - Cited by 599 (14 self) - Add to MetaCart
For such self-organizing infrastructures as mobile ad hoc networks , envisioned to operate in an open, collaborative, and highly volatile environment, the importance of secu- rity cannot be underrated. The provision of comprehen- sive secure communication mandates that both route dis- covery

Predicting Internet Network Distance with Coordinates-Based Approaches

by T. S. Eugene Ng, Hui Zhang - In INFOCOM , 2001
"... In this paper, we propose to use coordinates-based mechanisms in a peer-to-peer architecture to predict Internet network distance (i.e. round-trip propagation and transmission delay) . We study two mechanisms. The first is a previously proposed scheme, called the triangulated heuristic, which is bas ..."
Abstract - Cited by 631 (6 self) - Add to MetaCart
is based on relative coordinates that are simply the distances from a host to some special network nodes. We propose the second mechanism, called Global Network Positioning (GNP), which is based on absolute coordinates computed from modeling the Internet as a geometric space. Since end hosts maintain

A Bayesian method for the induction of probabilistic networks from data

by Gregory F. Cooper, EDWARD HERSKOVITS - MACHINE LEARNING , 1992
"... This paper presents a Bayesian method for constructing probabilistic networks from databases. In particular, we focus on constructing Bayesian belief networks. Potential applications include computer-assisted hypothesis testing, automated scientific discovery, and automated construction of probabili ..."
Abstract - Cited by 1400 (31 self) - Add to MetaCart
network from a database of cases. Finally, we relate the methods in this paper to previous work, and we discuss open problems.
Results 1 - 10 of 54,177