[...]... concepts and functions of data mining, like classification, clustering, and rule mining, we wish to highlight the current and burning issues related to mining in multimedia applications and Bioinformatics Storage of such huge datasets being more feasible in the compressed domain, we also devote a reasonable portion of the text to data mining in the compressed domain Topics like text mining, image mining, and. .. feature ranking and selection techniques 3 Data preprocessing: This is required to improve the quality of the actual data for mining This also increases the mining efficiency by reducing the time required for mining the preprocessed data Data preprocessing involves data cleaning, data transformation, data integration, data reduction or data compression for compact representation, etc (a) Data cleaning:... collecting and cleaning transactional data and making them available for analysis and decision support Data mining works hand in hand with warehouse data Data warehousing is analogous to a mechanism that provides an enterprize with a memory, while its mining provides the enterprize with intelligence KDD focuses on the overall process of knowledge discovery from large volumes of data, including the storage and. .. chapter we consider data mining from the perspective of machine learning, pattern recognition, image processing, and artificial intelligence We begin by providing the basics of knowledge discovery and data mining in Section 1.2 Sections 1. 3-1 .7 deal with brief introductions to data compression, information retrieval, text mining, Web mining, and image mining Their applicability to multimedia data are also... their hybridizations, along with their roles in data mining We then present some advanced topics and new aspects of data mining related to the processing and retrieval of multimedia data These have direct applications to information retrieval, Web mining, image mining, and PREFACE xvii text mining The huge volumes of data required to be retrieved, processed, and stored make compression techniques a promising... storage and accessing of such data, scaling of algorithms to massive datasets, interpretation and visualization of results, and the modeling and support of the overall human machine interaction Efficient storage of the data, and hence its structure, is very important for its KNOWLEDGE DISCOVERY AND DATA MINING Fig 1.1 The KDD process representation and access Knowledge from modern data compression technologies... store, distribute, and transmit [l ]-[ 3j With significant progress in computing and related technologies and their ever-expanding usage in different walks of life, huge amount of data of diverse characteristics continue to be collected and stored in databases The rate at which such data are stored is growing phenomenally We can draw an analogy between the popular Moore's law and the way data are increasing... Conclusions and Discussion 293 293 294 295 296 297 302 302 305 308 310 311 315 CONTENTS References xiii 315 9 Multimedia Data Mining 9.1 Introduction 9.2 Text Mining 9.2.1 Keyword-based search and mining 9.2.2 Text analysis and retrieval 9.2.3 Mathematical modeling of documents 9.2.4 Similarity-based matching for documents and queries 9.2.5 Latent semantic analysis 9.2.6 Soft computing approaches 9.3 Image Mining. .. removal and handling of missing data, reduction of redundancy, etc Data from real-world sources are often erroneous, incomplete, and inconsistent, perhaps due to operational error or system implementation flaws Such low-quality data needs to be cleaned prior to data mining (b) Data integration: Integration plays an important role in KDD This operation includes integrating multiple, heterogeneous datasets... in data representation, in order to generate a shorter representation for the data to conserve data storage In earlier discussions, we emphasized that data reduction is an important preprocessing task in data mining Need for reduced representation of data is crucial for the success of very large multimedia database applications and the associated 12 INTRODUCTION TO DATA MINING economical usage of data . format. Library of Congress Cataloging-in-Publication Data: Mitra, Sushmita Data mining : multimedia, soft computing, and bioinformatics / Sushmita Mitra and Tinku Acharya. p. cm. Includes .