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An Information-Theoretic Definition of Similarity

by Dekang Lin - In Proceedings of the 15th International Conference on Machine Learning , 1998
"... Similarity is an important and widely used concept. Previous definitions of similarity are tied to a particular application or a form of knowledge representation. We present an informationtheoretic definition of similarity that is applicable as long as there is a probabilistic model. We demonstrate ..."
Abstract - Cited by 1243 (0 self) - Add to MetaCart
Similarity is an important and widely used concept. Previous definitions of similarity are tied to a particular application or a form of knowledge representation. We present an informationtheoretic definition of similarity that is applicable as long as there is a probabilistic model. We demonstrate

Social Network Sites: A Definition A History of Social Network Sites Previous Scholarship

by Nicole B. Ellison
"... ..."
Abstract - Cited by 1017 (12 self) - Add to MetaCart
Abstract not found

Domain names - Implementation and Specification

by P. Mockapetris - RFC-883, USC/Information Sciences Institute , 1983
"... This RFC describes the details of the domain system and protocol, and assumes that the reader is familiar with the concepts discussed in a companion RFC, "Domain Names- Concepts and Facilities " [RFC-1034]. The domain system is a mixture of functions and data types which are an official pr ..."
Abstract - Cited by 725 (9 self) - Add to MetaCart
and the Internet class RR data formats (e.g., host addresses). Since the previous RFC set, several definitions have changed, so some previous definitions are obsolete. Experimental or obsolete features are clearly marked in these RFCs, and such information should be used with caution. The reader is especially

Irrelevant Features and the Subset Selection Problem

by George H. John, Ron Kohavi, Karl Pfleger - MACHINE LEARNING: PROCEEDINGS OF THE ELEVENTH INTERNATIONAL , 1994
"... We address the problem of finding a subset of features that allows a supervised induction algorithm to induce small high-accuracy concepts. We examine notions of relevance and irrelevance, and show that the definitions used in the machine learning literature do not adequately partition the features ..."
Abstract - Cited by 757 (26 self) - Add to MetaCart
into useful categories of relevance. We present definitions for irrelevance and for two degrees of relevance. These definitions improve our understanding of the behavior of previous subset selection algorithms, and help define the subset of features that should be sought. The features selected should depend

Relations among notions of security for public-key encryption schemes

by Mihir Bellare, David Pointcheval, Phillip Rogaway , 1998
"... Abstract. We compare the relative strengths of popular notions of security for public key encryption schemes. We consider the goals of privacy and non-malleability, each under chosen plaintext attack and two kinds of chosen ciphertext attack. For each of the resulting pairs of definitions we prove e ..."
Abstract - Cited by 517 (69 self) - Add to MetaCart
contribution of this paper is a new definition of non-malleability which we believe is simpler than the previous one.

Learning Stochastic Logic Programs

by Stephen Muggleton , 2000
"... Stochastic Logic Programs (SLPs) have been shown to be a generalisation of Hidden Markov Models (HMMs), stochastic context-free grammars, and directed Bayes' nets. A stochastic logic program consists of a set of labelled clauses p:C where p is in the interval [0,1] and C is a first-order r ..."
Abstract - Cited by 1194 (81 self) - Add to MetaCart
probability labels on each definition and near-maximal Bayes posterior probability and then 2) alters the probability labels to further increase the posterior probability. Stage 1) is implemented within CProgol4.5, which differs from previous versions of Progol by allowing user-defined evaluation

Inductive-Data-Type Systems

by Frederic Blanqui, Jean-Pierre Jouannaud, Mitsuhiro Okada , 2002
"... In a previous work ("Abstract Data Type Systems", TCS 173(2), 1997), the leI two authors presented a combined lmbined made of a (strongl normal3zG9 alrmal rewrite system and a typed #-calA#Ik enriched by pattern-matching definitions folnitio a certain format,calat the "General Schem ..."
Abstract - Cited by 821 (23 self) - Add to MetaCart
In a previous work ("Abstract Data Type Systems", TCS 173(2), 1997), the leI two authors presented a combined lmbined made of a (strongl normal3zG9 alrmal rewrite system and a typed #-calA#Ik enriched by pattern-matching definitions folnitio a certain format,calat the "

Applications Of Circumscription To Formalizing Common Sense Knowledge

by John McCarthy - Artificial Intelligence , 1986
"... We present a new and more symmetric version of the circumscription method of nonmonotonic reasoning first described in (McCarthy 1980) and some applications to formalizing common sense knowledge. The applications in this paper are mostly based on minimizing the abnormality of different aspects o ..."
Abstract - Cited by 532 (12 self) - Add to MetaCart
of various entities. Included are nonmonotonic treatments of is-a hierarchies, the unique names hypothesis, and the frame problem. The new circumscription may be called formula circumscription to distinguish it from the previously defined domain circumscription and predicate circumscription. A still more

Cognitive networks

by Ryan W. Thomas, Luiz A. DaSilva, Allen B. MacKenzie - IN PROC. OF IEEE DYSPAN 2005 , 2005
"... This paper presents a definition and framework for a novel type of adaptive data network: the cognitive network. In a cognitive network, the collection of elements that make up the network observes network conditions and then, using prior knowledge gained from previous interactions with the network ..."
Abstract - Cited by 1106 (7 self) - Add to MetaCart
This paper presents a definition and framework for a novel type of adaptive data network: the cognitive network. In a cognitive network, the collection of elements that make up the network observes network conditions and then, using prior knowledge gained from previous interactions

Dynamic programming algorithm optimization for spoken word recognition

by Hiroaki Sakoe, Seibi Chiba - IEEE TRANSACTIONS ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING , 1978
"... This paper reports on an optimum dynamic programming (DP) based time-normalization algorithm for spoken word recognition. First, a general principle of time-normalization is given using timewarping function. Then, two time-normalized distance definitions, ded symmetric and asymmetric forms, are der ..."
Abstract - Cited by 788 (3 self) - Add to MetaCart
This paper reports on an optimum dynamic programming (DP) based time-normalization algorithm for spoken word recognition. First, a general principle of time-normalization is given using timewarping function. Then, two time-normalized distance definitions, ded symmetric and asymmetric forms
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