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Targeting Domain

by Identification Of Aescherichia Coli, Xuan-chuan Yu, Anthony H. Tran, Qin Sun, William Margolin , 1997
"... This article cites 24 articles, 14 of which can be accessed free at: ..."
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This article cites 24 articles, 14 of which can be accessed free at:

The Vocabulary Problem in Human-System Communication

by G. W. Furnas, T. K. Landauer, L. M. Gomez, S. T. Dumais - COMMUNICATIONS OF THE ACM , 1987
"... In almost all computer applications, users must enter correct words for the desired objects or actions. For success without extensive training, or in first-tries for new targets, the system must recognize terms that will be chosen spontaneously. We studied spontaneous word choice for objects in five ..."
Abstract - Cited by 562 (8 self) - Add to MetaCart
In almost all computer applications, users must enter correct words for the desired objects or actions. For success without extensive training, or in first-tries for new targets, the system must recognize terms that will be chosen spontaneously. We studied spontaneous word choice for objects

Topics Target domain

by Jie Tang, Sen Wu, Jimeng Sun, Hang Su, Ibm Tj Watson
"... Interdisciplinary collaborations have generated huge impact to society. ..."
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Interdisciplinary collaborations have generated huge impact to society.

Maximizing the Spread of Influence Through a Social Network

by David Kempe - In KDD , 2003
"... Models for the processes by which ideas and influence propagate through a social network have been studied in a number of domains, including the diffusion of medical and technological innovations, the sudden and widespread adoption of various strategies in game-theoretic settings, and the effects of ..."
Abstract - Cited by 990 (7 self) - Add to MetaCart
Models for the processes by which ideas and influence propagate through a social network have been studied in a number of domains, including the diffusion of medical and technological innovations, the sudden and widespread adoption of various strategies in game-theoretic settings, and the effects

Benchmarking Least Squares Support Vector Machine Classifiers

by Tony Van Gestel, Johan A. K. Suykens, Bart Baesens, Stijn Viaene, Jan Vanthienen, Guido Dedene, Bart De Moor, Joos Vandewalle - NEURAL PROCESSING LETTERS , 2001
"... In Support Vector Machines (SVMs), the solution of the classification problem is characterized by a (convex) quadratic programming (QP) problem. In a modified version of SVMs, called Least Squares SVM classifiers (LS-SVMs), a least squares cost function is proposed so as to obtain a linear set of eq ..."
Abstract - Cited by 476 (46 self) - Add to MetaCart
of equations in the dual space. While the SVM classifier has a large margin interpretation, the LS-SVM formulation is related in this paper to a ridge regression approach for classification with binary targets and to Fisher's linear discriminant analysis in the feature space. Multiclass categorization

The faculty of language: what is it, who has it, and how did it evolve?

by Marc D Hauser , Noam Chomsky , W Tecumseh Fitch - Science, , 2002
"... We argue that an understanding of the faculty of language requires substantial interdisciplinary cooperation. We suggest how current developments in linguistics can be profitably wedded to work in evolutionary biology, anthropology, psychology, and neuroscience. We submit that a distinction should ..."
Abstract - Cited by 472 (7 self) - Add to MetaCart
of elements. We hypothesize that FLN only includes recursion and is the only uniquely human component of the faculty of language. We further argue that FLN may have evolved for reasons other than language, hence comparative studies might look for evidence of such computations outside of the domain

Hidden Markov models for detecting remote protein homologies

by Kevin Karplus, Christian Barrett, Richard Hughey - Bioinformatics , 1998
"... A new hidden Markov model method (SAM-T98) for nding remote homologs of protein sequences is described and evaluated. The method begins with a single target sequence and iteratively builds a hidden Markov model (hmm) from the sequence and homologs found using the hmm for database search. SAM-T98 is ..."
Abstract - Cited by 462 (15 self) - Add to MetaCart
A new hidden Markov model method (SAM-T98) for nding remote homologs of protein sequences is described and evaluated. The method begins with a single target sequence and iteratively builds a hidden Markov model (hmm) from the sequence and homologs found using the hmm for database search. SAM-T98

Identification of Target Domains of the Cardiac Ryanodine

by Masunori Matsuzaki, Mamoru Mochizuki, Tetsuro Oda, Shigeki Kobayashi, Noriaki Ikemoto, Takeshi Yamamoto, Masafumi Yano, Xiaojuan Xu, Hitoshi Uchinoumi , 2008
"... located on the World Wide Web at: The online version of this article, along with updated information and services, is ..."
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located on the World Wide Web at: The online version of this article, along with updated information and services, is

Metaphor corpus annotated for source - target domain mappings

by Ekaterina Shutova, Simone Teufel , 2010
"... Besides making our thoughts more vivid and filling our communication with richer imagery, metaphor also plays an important structural role in our cognition. Although there is a consensus in the linguistics and NLP research communities that the phenomenon of metaphor is not restricted to similarity-b ..."
Abstract - Cited by 7 (4 self) - Add to MetaCart
-based extensions of meanings of isolated words, but rather involves reconceptualization of a whole area of experience (target domain) in terms of another (source domain), there still has been no proposal for a comprehensive procedure for annotation of cross-domain mappings. However, a corpus annotated

RANKING ADAPTATION SVM FOR TARGET DOMAIN SEARCH

by M S Gayathri , S Leela , Asst Prof
"... Abstract: With the growth of different search engines, it becomes difficult for an user to search particular information effectively. If a search engine could provide domain specific information such as that confines only to a particular topicality, it is referred to as domain specific engine. Appl ..."
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to domain specific search. An algorithm called Ranking Adaptation SVM is used to effectively adapt a ranking model to a target domain. Such an adaptation has advantages since it needs only the predictions from existing ranking models. Ranking Adaptability measurement is used to quantitatively estimate
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