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Mining Association Rules from Responded Questionnaire of Sanitary Education Guidance
"... Abstract- Since it can provide high-contrast and is good to produce uniform brightness, FTIR multi-touch technology is chosen to design the proposed platform. The device is designed to display propagandas, images, videos, and games to propagate knowledge of sanitary education and disease prevention ..."
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Abstract- Since it can provide high-contrast and is good to produce uniform brightness, FTIR multi-touch technology is chosen to design the proposed platform. The device is designed to display propagandas, images, videos, and games to propagate knowledge of sanitary education and disease prevention to users. Furthermore, a physical and mental health questionnaire scale is implemented for users to on-line fill out the questionnaire after logging into the system by their own RFID tags. The responded questionnaires are then used to find the association rules among them based on various combinations of grade intervals, minimum supports, and minimum confidences. Experimental results show that the proposed system can discover interesting association rules from users’ responded questionnaire. Keywords: data mining, FP-tree, touch display system, sanitary education guidance. 1
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, VOL., NO., 1 Cascading
, 2011
"... This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. ..."
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This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication.
Improving Spatiotemporal Change Detection: A High Level Fusion Approach for Discovering Uncertain Knowledge from Satellite Image Databases
"... Abstract—This paper investigates the problem of tracking spatiotemporal changes of a satellite image through the use of Knowledge Discovery in Database (KDD). The purpose of this study is to help a given user effectively discover interesting knowledge and then build prediction and decision models. U ..."
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Abstract—This paper investigates the problem of tracking spatiotemporal changes of a satellite image through the use of Knowledge Discovery in Database (KDD). The purpose of this study is to help a given user effectively discover interesting knowledge and then build prediction and decision models. Unfortunately, the KDD process for spatiotemporal data is always marked by several types of imperfections. In our paper, we take these imperfections into consideration in order to provide more accurate decisions. To achieve this objective, different KDD methods are used to discover knowledge in satellite image databases. Each method presents a different point of view of spatiotemporal evolution of a query model (which represents an extracted object from a satellite image). In order to combine these methods, we use the evidence fusion theory which considerably improves the spatiotemporal knowledge discovery process and increases our belief in the spatiotemporal model change. Experimental results of satellite images representing the region of Auckland in New Zealand depict the improvement in the overall change detection as compared to using classical methods. Keywords—Knowledge discovery in satellite databases, knowledge fusion, data imperfection, data mining, spatiotemporal change detection. I.
Mining Mutation Chains in Biological Sequences
"... Abstract — The increasing infectious disease outbreaks has led to a need for new research to better understand the disease’s origins, epidemiological features and pathogenicity caused by fast-mutating, fast-spreading viruses. Traditional sequence analysis methods do not take into account the spatio- ..."
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Abstract — The increasing infectious disease outbreaks has led to a need for new research to better understand the disease’s origins, epidemiological features and pathogenicity caused by fast-mutating, fast-spreading viruses. Traditional sequence analysis methods do not take into account the spatio-temporal dynamics of rapidly evolving and spreading viral species. They are also focused on identifying single-point mutations. In this paper, we propose a novel approach that incorporates space-time relationships for studying changes in protein sequences from fast mutating viruses. We aim to detect both single-point mutations as well as k-mutations in the viral sequences. We define the problem of mutation chain pattern mining and design algorithms to discover valid mutation chains. Compact data structures to facilitate the mining process as well as pruning strategies to increase the scalability of the algorithms are devised. Experiments on both synthetic datasets and real world influenza A virus dataset show that our algorithms are scalable and effective in discovering mutations that occur geographically over time. I.
Oral examination:.................................................. Learning Social Links and Communities from
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OF THE UNIVERSITY OF MINNESOTA BY
, 2012
"... I had the honor of working with a number of amazing individuals during my time at the University of Minnesota. This thesis is the outcome of that wonderful association. First, I express my gratitude to my advisor, Professor. Shekhar, for being such a wonderful mentor. I am particularly grateful for ..."
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I had the honor of working with a number of amazing individuals during my time at the University of Minnesota. This thesis is the outcome of that wonderful association. First, I express my gratitude to my advisor, Professor. Shekhar, for being such a wonderful mentor. I am particularly grateful for his patient and steadfast support during anxious moments in Graduate School. I am indebted to him for helping me understand the principles behind the practice of science through several memorable experiences. I truly appreciate the con-fidence he instilled in me, the courage he has given me to face challenges in research and all the advise that he has been kind to give me through these years. He has inspired me with his balanced approach to any challenge, amazing wisdom and unique perspectives. I am blessed to have had him as my advisor and I consider having been his student a great honor. My sincere thanks to my dissertation committee members, Professor Kumar, Professor Srivastava, Professor Karypis, Professor Harvey and Professor Banerjee for their support, feedback and guidance. I am indebted to our collaborators from the U.S. Army Corps Engineers and the Na-tional Institute of Justice who gave me valuable insights into the societal applications of this research. I am particularly grateful for several valuable comments that shaped differ-ent parts of this thesis through publications in highly selective conferences and journals. I i
