Philip Chan

Philip Wing Keung Chan

Hillol Kargupta

This book presents introductions to DKD and PKD, extensive reviews of the field, and state-of-the-art techniques. Foreword by Vipin Kumar Knowledge discovery and data mining (KDD) deals with the problem of extracting interesting associations, classifiers, clusters, and other patterns from data. The emergence of network-based distributed computing environments has introduced an important new dimension to this problem--distributed sources of data. Traditional centralized KDD typically requires central aggregation of distributed data, which may not always be feasible because of limited network bandwidth, security concerns, scalability problems, and other practical issues. Distributed knowledge discovery (DKD) works with the merger of communication and computation by analyzing data in a distributed fashion. This technology is particularly useful for large heterogeneous distributed environments such as the Internet, intranets, mobile computing environments, and sensor-networks.When the data sets are large, scaling up the speed of the KDD process is crucial. Parallel knowledge discovery (PKD) techniques addresses this problem by using high-performance multiprocessor machines. This book presents introductions to DKD and PKD, extensive reviews of the field, and state-of-the-art techniques. Contributors Rakesh Agrawal, Khaled AlSabti, Stuart Bailey, Philip Chan, David Cheung, Vincent Cho, Joydeep Ghosh, Robert Grossman, Yi-ke Guo, John Hale, John Hall, Daryl Hershberger, Ching-Tien Ho, Erik Johnson, Chris Jones, Chandrika Kamath, Hillol Kargupta, Charles Lo, Balinder Malhi, Ron Musick, Vincent Ng, Byung-Hoon Park, Srinivasan Parthasarathy, Andreas Prodromidis, Foster Provost, Jian Pun, Ashok Ramu, Sanjay Ranka, Mahesh Sreenivas, Salvatore Stolfo, Ramesh Subramonian, Janjao Sutiwaraphun, Kagan Tummer, Andrei Turinsky, Beat Wüthrich, Mohammed Zaki, Joshua Zhang

Advances in Distributed and Parallel Knowledge Discovery

Enlighten (Good Advice Part 5) By: Philip Chan Eager to understand and appreciate the principles of life, Philip Chan began reading Buddhist literature and philosophy books. In Enlighten (Good Advice Part 5) he distills his research and life experience into a series of short and direct lessons. Life is a journey of learning. You can choose your route and live a life you enjoy. Chan encourages self-reflection and hope by reminding you this is your own life: it cannot be lived by anyone else and it should not be lived for anyone else. To live the best life possible you need to develop a strong personal character that is responsible, grateful, and patient. Learn to relax and let go of the past. By treating others with compassion and respect, you will create nurturing relationships. Enjoy today – time passes quickly and once it’s gone, it’s gone forever. Peace of mind and contentment will keep you happy and healthy. Based on traditional Chinese values and etiquette, Enlighten is a compact and gentle book on living your best life.

Philip Chan

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