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Title: ppt for text clustering with seeds affinity propagation
Page Link: ppt for text clustering with seeds affinity propagation -
Posted By: vijay
Created at: Thursday 05th of October 2017 05:12:46 AM
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Title: code for the fuzzy self constructing feature clustering algorithm for text classific
Page Link: code for the fuzzy self constructing feature clustering algorithm for text classific -
Posted By: sumitgupta
Created at: Thursday 05th of October 2017 03:46:00 AM
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Title: Text Clustering with Seeds Affinity Propagation
Page Link: Text Clustering with Seeds Affinity Propagation -
Posted By: Priyanka Pansare
Created at: Thursday 17th of August 2017 05:04:06 AM
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Title: future enhancement of text automatic template extraction from heterogeneous web page
Page Link: future enhancement of text automatic template extraction from heterogeneous web page -
Posted By: bibhu duttadas
Created at: Thursday 05th of October 2017 04:34:48 AM
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Title: cache affinity scheduling
Page Link: cache affinity scheduling -
Posted By: mrsunilkale
Created at: Thursday 17th of August 2017 06:32:59 AM
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Cache affinity scheduling method
In the case of for shared-memory multiprocessors, there are two factors that increase the number of cache misses. One of them being that several processes are forced to time-share the same cache, and as a result, the processes will mutually displace the cache state built up by the previous state. a stream of misses as it rebuilds ita cache state is produced.The processes should reuse their cached state more in order to reduce the number of misses in these workloads. The process of schedule each process b ....etc

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Title: Frequent Term-Based Text Clustering
Page Link: Frequent Term-Based Text Clustering -
Posted By: anokh.scorpio
Created at: Thursday 05th of October 2017 04:58:19 AM
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ABSTRACT

Text clustering methods can be used to structure large sets of text or hypertext documents. The well-known methods of text clustering, however, do not really address the special problems of text clustering: very high dimensionality of the data, very large size of the databases and understandability of the cluster description. In this paper, we introduce a novel approach which uses frequent item (term) sets for text clustering. Such frequent sets can be efficiently discovered using algorithms for associat ....etc

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Title: coding for efficient concept based mining model for enhancing text clustering
Page Link: coding for efficient concept based mining model for enhancing text clustering -
Posted By: ravindra sp
Created at: Thursday 05th of October 2017 03:48:54 AM
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Title: a fuzzy self constructing feature clustering algorithm for text classification full
Page Link: a fuzzy self constructing feature clustering algorithm for text classification full -
Posted By: Athul
Created at: Thursday 05th of October 2017 03:51:33 AM
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Title: frequent term based text clustering code
Page Link: frequent term based text clustering code -
Posted By: NANDA
Created at: Thursday 05th of October 2017 03:46:27 AM
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Abstract

Text clustering methods can be used to structure large sets of text or hypertext documents. The well-known methods of text clustering, however, do not really address the special problems of text clustering: very high dimensionality of the data, very large size of the databases and understandability of the cluster description. In this paper, we introduce a novel approach which uses frequent item (term) sets for text clustering. Such frequent sets can be efficiently discovered using algorithms for association rule mining. To cluster bas ....etc

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Title: a text clustering framework for information retrieval
Page Link: a text clustering framework for information retrieval -
Posted By: veena
Created at: Thursday 05th of October 2017 04:40:59 AM
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Abstract

Text-mining methods have become a key feature for homeland-security technologies, as they can help explore effectively increasing masses of digital documents in the search for relevant information. This research presents a model for document clustering that arranges unstructured documents into content-based homogeneous groups. The overall paradigm is hybrid because it combines pattern-recognition grouping algorithms with semantic-driven processing. First, a semantic-based metric measures distances between documents, by combining conte ....etc

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