Data Mining: Multimedia, Soft Computing, and Bioinformatics
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Page 11
... hence , commu- nication costs when transmitted through a communication network [ 24 , 25 ] . Reducing the storage requirement is equivalent to increasing the capacity of the storage medium . If the compressed data are properly indexed ...
... hence , commu- nication costs when transmitted through a communication network [ 24 , 25 ] . Reducing the storage requirement is equivalent to increasing the capacity of the storage medium . If the compressed data are properly indexed ...
Page 12
... Hence storage and subsequent access of thousands of high - resolution images , which are possibly interspersed with other datatypes as attributes , is a challenge . Data compression offers advantages in the storage management of such ...
... Hence storage and subsequent access of thousands of high - resolution images , which are possibly interspersed with other datatypes as attributes , is a challenge . Data compression offers advantages in the storage management of such ...
Page 13
... Hence it encompasses both text and image mining . Information re- trieval automatically entails some amount of summarization or compression , along with retrieval based on content . Given a user query , the information system has to ...
... Hence it encompasses both text and image mining . Information re- trieval automatically entails some amount of summarization or compression , along with retrieval based on content . Given a user query , the information system has to ...
Page 14
... hence the extraction of knowledge from it , is a long - standing challenge in artificial in- telligence . There were efforts to develop models and retrieval techniques for semistructured data from the database community . The ...
... hence the extraction of knowledge from it , is a long - standing challenge in artificial in- telligence . There were efforts to develop models and retrieval techniques for semistructured data from the database community . The ...
Page 15
... Hence access of text information in the compressed domain will become a challenge in the near future . There is practically no remarkable effort in this direction in the research community . In order to make progress in such efforts ...
... Hence access of text information in the compressed domain will become a challenge in the near future . There is practically no remarkable effort in this direction in the research community . In order to make progress in such efforts ...
Contents
1 | |
2 Soft Computing | 35 |
3 Multimedia Data Compression | 89 |
4 String Matching | 143 |
5 Classification in Data Mining | 181 |
6 Clustering in Data Mining | 227 |
7 Association Rules | 267 |
8 Rule Mining with Soft Computing | 293 |
9 Multimedia Data Mining | 319 |
An Application | 365 |
Index | 392 |
About the Authors | 399 |
Other editions - View all
Data Mining: Multimedia, Soft Computing, and Bioinformatics Sushmita Mitra,Tinku Acharya No preview available - 2005 |
Common terms and phrases
analysis applications association rules attributes binary Bioinformatics bits categorical character chromosome classification coding coefficients color components content-based image retrieval corresponding data compression data mining dataset decision tree decoder defined dictionary distance document domain encoded entropy entropy encoding evaluation example extracted feature frequent itemsets fuzzy sets genetic algorithms Hence Huffman code IEEE IEEE Transactions image retrieval initial input interaction involving JPEG knowledge discovery learning linguistic matrix measure method Mitra multimedia data neural networks neuro-fuzzy neurons node objects optimal output parameters partition pattern matching pixel prediction problem protein quantization query representation represented rough set S. K. Pal sample Section sequence shown in Fig soft computing spatial statistical string matching structure subbands subnetworks subsets substring symbol Table techniques text mining Transactions on Neural transformed vector visual wavelet Web mining weights