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Your search keyword '"Freeman, Richard T."' showing total 35 results
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35 results on '"Freeman, Richard T."'

1. Web Feed Clustering and Tagging Aggregator Using Topological Tree-Based Self-Organizing Maps

Author

Freeman, Richard T., Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Corchado, Emilio, editor, and Yin, Hujun, editor

Published
2009
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2. Topological Tree Clustering of Social Network Search Results

Author

Freeman, Richard T., Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Yin, Hujun, editor, Tino, Peter, editor, Corchado, Emilio, editor, Byrne, Will, editor, and Yao, Xin, editor

Published
2007
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3. Topological Tree Clustering of Web Search Results

Author

Freeman, Richard T., Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Corchado, Emilio, editor, Yin, Hujun, editor, Botti, Vicente, editor, and Fyfe, Colin, editor

Published
2006
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4. Topological Tree for Web Organisation, Discovery and Exploration

Author

Freeman, Richard T., Yin, Hujun, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Yang, Zheng Rong, editor, Yin, Hujun, editor, and Everson, Richard M., editor

Published
2004
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6. Web content management by self-organization

Author

Freeman, Richard T. and Yin, Hujun

Subjects
Knowledge management -- Methods, Self-organizing systems -- Usage, Neural networks -- Usage, Information storage and retrieval -- Research, Hierarchical organization (Computers) -- Methods, Knowledge management, Neural network, Business, Computers, Electronics, Electronics and electrical industries
Abstract

We present a new method for content management and knowledge discovery using a topology-preserving neural network. The method, termed topological organization of content (TOC), can generate a taxonomy of topics from a set of unannotated, unstructured documents. The TOC consists of a hierarchy of self-organizing growing chains (GCs), each of which can develop independently in terms of size and topics. The dynamic development process is validated continuously using a proposed entropy-based Bayesian information criterion (BIC). Each chain meeting the criterion spans child chains, with reduced vocabularies and increased specializations. This results in a topological tree hierarchy, which can be browsed like a table of contents directory or web portal. A brief review is given on existing methods for document clustering and organization, and clustering validation measures. The proposed approach has been tested and compared with several existing methods on real world web page datasets. The results have clearly demonstrated the advantages and efficiency in content organization of the proposed method in terms of computational cost and representation. The TOC can be easily adapted for large-scale applications. The topology provides a unique, additional feature for retrieving related topics and confining the search space. Index Terms--Bayesian information criterion (BIC), content management, document categorization, hierarchical clustering, information retrieval (IR), self-organizing maps (SOMs), taxonomy generation, topic hierarchy, topological tree structure.

Published
2005

12. Inflation Targeting in the 1990s: The Experiences of New Zealand, Canada, and the United Kingdom

Author

Ammer, John and Freeman, Richard T.

Subjects
Inflation (Finance) -- Research, Inflation accounting -- Research, Business, Economics
Abstract

As observed in a survey of three countries, New Zealand, Canada and the United Kingdom, inflation targets had been achieved. In a simulation exercise, however, only in New Zealand was the cost of inflation reduction substantial.

Published
1995

24. Topological Tree Clustering of Web Search Results.

Author

Corchado, Emilio, Yin, Hujun, Botti, Vicente, Fyfe, Colin, and Freeman, Richard T.

Abstract

In the knowledge economy taxonomy generation, information retrieval and portals in intelligent enterprises need to be dynamically adaptive to changes in their enterprise content. To remain competitive and efficient, this has to be done without exclusively relying on knowledge workers to update taxonomies or manually label documents. This paper briefly reviews existing visualisation methods used in presenting search results retrieved from a web search engine. A method, termed topological tree, that could be use to automatically organise large sets of documents retrieved from any type of search, is presented. The retrieved results, organised using an online version of the topological tree method, are compared to the visual representation of a web search engine that uses a document clustering algorithm. A discussion is made on the criterions of representing hierarchical relationships, having visual scalability, presenting underlying topics extracted from the document set, and providing a clear view of the connections between topics. The topological tree has been found to be a superior representation in all cases and well suited for organising web content. Keywords: Information retrieval, document clustering, search engine, self organizing maps, topological tree, information access, faceted classification, guided navigation, taxonomy generation, neural networks, post retrieval clustering, taxonomy generation, enterprise portals, enterprise content management, enterprise search, information management. [ABSTRACT FROM AUTHOR]

Published
2006
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35. Choosing the right pond (Book Review).

Author

Freeman, Richard T.

Subjects
HUMAN behavior, NONFICTION
Abstract

Reviews the book "Choosing the Right Pond: Human Behavior and the Quest for Status," by Robert L. Frank.

Published
1987

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