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Department of Computer Science Seminar
2015 Series

Approximate High-Dimensional Nearest Neighbor Queries Using R-Forests (and other informatics research @ Baylor)

Dr. King-Ip David Lin
Associate Professor
Baylor University

Date: July 16, 2015 (Thursday)
Time: 11:00 am - 12:00 pm
Venue: LT1 (SCT501), Cha Chi Ming Science Tower, Ho Sin Hang Campus

Highly efficient query processing on high-dimensional data, while important, is still a challenge nowadays -- as the curse of dimensionality makes efficient solution very difficult. On the other hand, there have been suggestions that it is better off if one can return a solution quickly, that is close enough, to be sufficient. In this talk I will introduce the concept R-Forest, comprised of a set of disjoint R-trees built over the domain of the search space. It can be used to answer Approximate Nearest Neighbor queries, returning a result that is an improvement over alternative method such as Locality Sensitive Hashing B-Tree (LSB-tree) with the same amount of IO. With our approach to this difficult problem, we are able to handle different data distribution, even taking advantage of the distribute without any additional parameter tuning, scales with increasing dimensionality and most importantly provides the user with some feedback, in terms of lower bound as to the quality of the results.

I will also present some exciting informatics research that is being conducted at Baylor University, including Big Data, Machine Learning, Bioinformatics and Text Mining.

Dr. King-Ip David Lin was born and raised in Hong Kong. After receiving his Bachelor of Science degree at the University of Hong Kong, he continued his academic pursuit at the University of Maryland, College Park, receiving his Ph.D. in 1996.

Since then he has been working at academia for nearly 20 years, first at the University of Memphis and now at Baylor University. Dr. Lin’s research includes database indexing, data mining, natural language process and health informatics.

********* ALL INTERESTED ARE WELCOME ***********
(For enquiry, please contact Computer Science Department at 3411 2385)
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Department of Computer Science, Hong Kong Baptist University
Hong Kong Baptist University