Skip to Main Content
Frequently Asked Questions
Submit an ETD
Global Search Box
Need Help?
Keyword Search
Participating Institutions
Advanced Search
School Logo
Files
File List
osu1196284256.pdf (264.12 KB)
ETD Abstract Container
Abstract Header
A partition based approach to approximate tree mining : a memory hierarchy perspective
Author Info
Agarwal, Khushbu
Permalink:
http://rave.ohiolink.edu/etdc/view?acc_num=osu1196284256
Abstract Details
Year and Degree
2007, Master of Science, Ohio State University, Computer and Information Science.
Abstract
In the last decade or so, database community is entering a new arena with generation of petabytes of data. In addition to the storage challenges associated with this data, Data Mining has become an imperative discipline to extract the relevant information from this data. Tree Mining,has also received attention in last couple of years with applicability to web mining, bio-informatics etc. Up to now, a majority of the tree mining algorithms have primarily focused on developing efficient algorithms by use of compact tree representations. However, these approaches may not be beneficial for datasets, which have large trees. In this dissertation, we focus on an approximation approach by partitioning individual trees. We design root based, edge based}, size based and node based partitioning schemes. Our evaluations show that balanced partitioning approaches show significant improvements over the existing algorithms. We observe interesting trend between the approximation and the execution time.
Committee
Srinivasan Parthasarathy (Advisor)
Subject Headings
Computer Science
Keywords
Data Mining
;
Tree Partitioning
;
Memory Based Approximation
;
Data Preprocessing
Recommended Citations
Refworks
EndNote
RIS
Mendeley
Citations
Agarwal, K. (2007).
A partition based approach to approximate tree mining : a memory hierarchy perspective
[Master's thesis, Ohio State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=osu1196284256
APA Style (7th edition)
Agarwal, Khushbu.
A partition based approach to approximate tree mining : a memory hierarchy perspective.
2007. Ohio State University, Master's thesis.
OhioLINK Electronic Theses and Dissertations Center
, http://rave.ohiolink.edu/etdc/view?acc_num=osu1196284256.
MLA Style (8th edition)
Agarwal, Khushbu. "A partition based approach to approximate tree mining : a memory hierarchy perspective." Master's thesis, Ohio State University, 2007. http://rave.ohiolink.edu/etdc/view?acc_num=osu1196284256
Chicago Manual of Style (17th edition)
Abstract Footer
Document number:
osu1196284256
Download Count:
743
Copyright Info
© 2007, all rights reserved.
This open access ETD is published by The Ohio State University and OhioLINK.