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A framework for information systems architecture.

by J A Zachman - IBM Syst. J., , 1987
"... With increasing size and complexity of the implementations of information systems, it is necessary to use some logical construct (or architecture) for defining and controlling the interfaces and the integration of all of the components of the system. This paper defines information systems architect ..."
Abstract - Cited by 546 (0 self) - Add to MetaCart
With increasing size and complexity of the implementations of information systems, it is necessary to use some logical construct (or architecture) for defining and controlling the interfaces and the integration of all of the components of the system. This paper defines information systems

Capacity of Fading Channels with Channel Side Information

by Andrea J. Goldsmith , et al. , 1997
"... We obtain the Shannon capacity of a fading channel with channel side information at the transmitter and receiver, and at the receiver alone. The optimal power adaptation in the former case is "water-pouring" in time, analogous to water-pouring in frequency for time-invariant frequency-sele ..."
Abstract - Cited by 586 (20 self) - Add to MetaCart
We obtain the Shannon capacity of a fading channel with channel side information at the transmitter and receiver, and at the receiver alone. The optimal power adaptation in the former case is "water-pouring" in time, analogous to water-pouring in frequency for time-invariant frequency

Maximum entropy markov models for information extraction and segmentation

by Andrew McCallum, Dayne Freitag, Fernando Pereira , 2000
"... Hidden Markov models (HMMs) are a powerful probabilistic tool for modeling sequential data, and have been applied with success to many text-related tasks, such as part-of-speech tagging, text segmentation and information extraction. In these cases, the observations are usually modeled as multinomial ..."
Abstract - Cited by 561 (18 self) - Add to MetaCart
Hidden Markov models (HMMs) are a powerful probabilistic tool for modeling sequential data, and have been applied with success to many text-related tasks, such as part-of-speech tagging, text segmentation and information extraction. In these cases, the observations are usually modeled

A Set Of Principles For Conducting And Evaluating Interpretive Field Studies In Information Systems

by Heinz K. Klein, Michael D. Myers , 1999
"... This article discusses the conduct and evaluation of interpretive research in information systems. While the conventions for evaluating information systems case studies conducted according to the natural science model of social science are now widely accepted, this is not the case for interpretive f ..."
Abstract - Cited by 914 (6 self) - Add to MetaCart
This article discusses the conduct and evaluation of interpretive research in information systems. While the conventions for evaluating information systems case studies conducted according to the natural science model of social science are now widely accepted, this is not the case for interpretive

Games with Incomplete Information Played by 'Bayesian' Players, I-III

by John C Harsanyi - MANAGEMENT SCIENCE , 1967
"... The paper develops a new theory for the analysis of games with incomplete information where the players are uncertain about some important parameters of the game situation, such as the payoff functions, the strategies available to various players, the information other players have about the game, e ..."
Abstract - Cited by 787 (2 self) - Add to MetaCart
The paper develops a new theory for the analysis of games with incomplete information where the players are uncertain about some important parameters of the game situation, such as the payoff functions, the strategies available to various players, the information other players have about the game

The rate-distortion function for source coding with side information at the decoder

by Aaron D. Wyner, Jacob Ziv - IEEE Trans. Inform. Theory , 1976
"... Abstract-Let {(X,, Y,J}r = 1 be a sequence of independent drawings of a pair of dependent random variables X, Y. Let us say that X takes values in the finite set 6. It is desired to encode the sequence {X,} in blocks of length n into a binary stream*of rate R, which can in turn be decoded as a seque ..."
Abstract - Cited by 1060 (1 self) - Add to MetaCart
as well as the decoder has access to the side information {Y,}. In nearly all cases it is shown that when d> 0 then R*(d)> Rx, y(d), so that knowledge of the side information at the encoder permits transmission of the {X,} at a given distortion level using a smaller transmission rate

Semantic Similarity in a Taxonomy: An Information-Based Measure and its Application to Problems of Ambiguity in Natural Language

by Philip Resnik , 1999
"... This article presents a measure of semantic similarityinanis-a taxonomy based on the notion of shared information content. Experimental evaluation against a benchmark set of human similarity judgments demonstrates that the measure performs better than the traditional edge-counting approach. The a ..."
Abstract - Cited by 609 (9 self) - Add to MetaCart
This article presents a measure of semantic similarityinanis-a taxonomy based on the notion of shared information content. Experimental evaluation against a benchmark set of human similarity judgments demonstrates that the measure performs better than the traditional edge-counting approach

Transformation-Based Error-Driven Learning and Natural Language Processing: A Case Study in Part-of-Speech Tagging

by Eric Brill - Computational Linguistics , 1995
"... this paper, we will describe a simple rule-based approach to automated learning of linguistic knowledge. This approach has been shown for a number of tasks to capture information in a clearer and more direct fashion without a compromise in performance. We present a detailed case study of this learni ..."
Abstract - Cited by 924 (8 self) - Add to MetaCart
this paper, we will describe a simple rule-based approach to automated learning of linguistic knowledge. This approach has been shown for a number of tasks to capture information in a clearer and more direct fashion without a compromise in performance. We present a detailed case study

Constrained K-means Clustering with Background Knowledge

by Kiri Wagstaff, Claire Cardie, Seth Rogers, Stefan Schroedl - In ICML , 2001
"... Clustering is traditionally viewed as an unsupervised method for data analysis. However, in some cases information about the problem domain is available in addition to the data instances themselves. In this paper, we demonstrate how the popular k-means clustering algorithm can be pro tably modi- ed ..."
Abstract - Cited by 488 (9 self) - Add to MetaCart
Clustering is traditionally viewed as an unsupervised method for data analysis. However, in some cases information about the problem domain is available in addition to the data instances themselves. In this paper, we demonstrate how the popular k-means clustering algorithm can be pro tably modi- ed

Verbal reports as data

by K. Anders Ericsson, Herbert A. Simon - Psychological Review , 1980
"... The central proposal of this article is that verbal reports are data. Accounting for verbal reports, as for other kinds of data, requires explication of the mech-anisms by which the reports are generated, and the ways in which they are sensitive to experimental factors (instructions, tasks, etc.). W ..."
Abstract - Cited by 513 (3 self) - Add to MetaCart
to understand in detail the mecha-nisms and internal structure of cognitive pro-cesses that produce these relations. In the limiting case, we would like to have process models so explicit that they could actually produce the predicted behavior from the in-formation in the stimulus.
Results 1 - 10 of 91,365