Developments in Data Extraction, Management, and Analysis

Developments in Data Extraction, Management, and Analysis

Nhung Do, J. Wenny Rahayu, Torab Torabi

Copyright: © 2013 |Pages: 417

ISBN13: 9781466621480|ISBN10: 1466621486|EISBN13: 9781466621497

DOI: 10.4018/978-1-4666-2148-0

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Do, Nhung, et al., editors. Developments in Data Extraction, Management, and Analysis. IGI Global, 2013. https://doi.org/10.4018/978-1-4666-2148-0

APA

Do, N., Rahayu, J. W., & Torabi, T. (Eds.). (2013). Developments in Data Extraction, Management, and Analysis. IGI Global. https://doi.org/10.4018/978-1-4666-2148-0

Chicago

Do, Nhung, J. Wenny Rahayu, and Torab Torabi, eds. Developments in Data Extraction, Management, and Analysis. Hershey, PA: IGI Global, 2013. https://doi.org/10.4018/978-1-4666-2148-0

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With the improvements of artificial intelligence, processor speeds and database sizes, the rapidly expanding field of data mining continues to provide advancing methods for managing databases and gaining knowledge.

Developments in Data Extraction, Management, and Analysis is an essential collection of research on the area of data mining and analytics. Presenting the most recent perspectives on data mining subjects and current issues, this book is useful for practitioners and academics alike.

Table of Contents

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Front Materials

Title Page

Copyright Page

Editorial Advisory Board

Preface

Chapters

Chapter 1

Visual Mobility Analysis using T-Warehouse (pages 1-22)

A. Raffaetà, L. Leonardi, G. Marketos, G. Andrienko, N. Andrienko, E. Frentzos, N. Giatrakos, S. Orlando, N. Pelekis, A. Roncato, C. Silvestri

Technological advances in sensing technologies and wireless telecommunication devices enable research fields related to the management of trajectory data. The challenge after storing the data is the implementation of appropriate...

Chapter 2

A Query Language for Mobility Data Mining (pages 23-44)

Roberto Trasarti, Fosca Giannotti, Mirco Nanni, Dino Pedreschi, Chiara Renso

The technologies of mobile communications and ubiquitous computing pervade society. Wireless networks sense the movement of people and vehicles, generating large volumes of mobility data, such as mobile phone call records and GPS...

Chapter 3

Distributed Privacy Preserving Clustering via Homomorphic Secret Sharing and its Application to (Vertically) Partitioned Spatio-Temporal Data (pages 45-65)

Can Brochmann Yildizli, Thomas Pedersen, Yucel Saygin, Erkay Savas, Albert Levi

Recent concerns about privacy issues have motivated data mining researchers to develop methods for performing data mining while preserving the privacy of individuals. One approach to develop privacy preserving data mining algorithms...

Chapter 4

Query Recommendations for OLAP Discovery-Driven Analysis (pages 66-90)

Arnaud Giacometti, Patrick Marcel, Elsa Negre, Arnaud Soulet

Recommending database queries is an emerging and promising field of research and is of particular interest in the domain of OLAP systems, where the user is left with the tedious process of navigating large datacubes. In this paper...

Chapter 5

Data Warehouse Testing (pages 91-108)

Matteo Golfarelli, Stefano Rizzi

Testing is an essential part of the design life-cycle of a software product. Although most phases of data warehouse design have received considerable attention in the literature, not much research has been conducted concerning data...

Chapter 6

An Empirical Evaluation of Similarity Coefficients for Binary Valued Data (pages 109-131)

David M. Lewis, Vandana P. Janeja

In this paper, the authors present an empirical evaluation of similarity coefficients for binary valued data. Similarity coefficients provide a means to measure the similarity or distance between two binary valued objects in a...

Chapter 7

Dynamic View Management System for Query Prediction to View Materialization (pages 132-161)

Negin Daneshpour, Ahmad Abdollahzadeh Barfourosh

On-Line Analytical Processing (OLAP) systems based on data warehouses are the main systems for managerial decision making and must have a quick response time. Several algorithms have been presented to select the proper set of data...

Chapter 8

Finding Associations in Composite Data Sets: The CFARM Algorithm (pages 162-186)

M. Sulaiman Khan, Maybin Muyeba, Frans Coenen, David Reid, Hissam Tawfik

In this paper, a composite fuzzy association rule mining mechanism (CFARM), directed at identifying patterns in datasets comprised of composite attributes, is described. Composite attributes are defined as attributes that can take...

Chapter 9

Automatic Item Weight Generation for Pattern Mining and its Application (pages 187-207)

Yun Sing Koh, Russel Pears, Gillian Dobbie

Association rule mining discovers relationships among items in a transactional database. Most approaches assume that all items within a dataset have a uniform distribution with respect to support. However, this is not always the...

Chapter 10

Weak Ratio Rules: A Generalized Boolean Association Rules (pages 208-244)

Baoqing Jiang, Xiaohua Hu, Qing Wei, Jingjing Song, Chong Han, Meng Liang

This paper examines the problem of weak ratio rules between nonnegative real-valued data in a transactional database. The weak ratio rule is a weaker form than Flip Korn’s ratio rule. After analyzing the mathematical model of weak...

Chapter 11

Decision Rule Extraction for Regularized Multiple Criteria Linear Programming Model (pages 245-258)

DongHong Sun, Li Liu, Peng Zhang, Xingquan Zhu, Yong Shi

Due to the flexibility of multi-criteria optimization, Regularized Multiple Criteria Linear Programming (RMCLP) has received attention in decision support systems. Numerous theoretical and empirical studies have demonstrated that...

Chapter 12

Incremental Algorithm for Discovering Frequent Subsequences in Multiple Data Streams (pages 259-279)

Reem Al-Mulla, Zaher Al Aghbari

In recent years, new applications emerged that produce data streams, such as stock data and sensor networks. Therefore, finding frequent subsequences, or clusters of subsequences, in data streams is an essential task in data mining....

Chapter 13

HYBRIDJOIN for Near-Real-Time Data Warehousing (pages 280-302)

M. Asif Naeem, Gillian Dobbie, Gerald Weber

An important component of near-real-time data warehouses is the near-real-time integration layer. One important element in near-real-time data integration is the join of a continuous input data stream with a disk-based relation. For...

Chapter 14

Data Field for Hierarchical Clustering (pages 303-324)

Shuliang Wang, Wenyan Gan, Deyi Li, Deren Li

In this paper, data field is proposed to group data objects via simulating their mutual interactions and opposite movements for hierarchical clustering. Enlightened by the field in physical space, data field to simulate nuclear field...

Chapter 15

Preserving Privacy in Time Series Data Mining (pages 325-346)

Ye Zhu, Yongjian Fu, Huirong Fu

Time series data mining poses new challenges to privacy. Through extensive experiments, the authors find that existing privacy-preserving techniques such as aggregation and adding random noise are insufficient due to privacy attacks...

Back Materials

Compilation of References

About the Contributors

Index

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