An Improved graph mining tool and its application to object detection in remote sensing

Download

index.pdf

Date

2013

Author

Aktaş, Ümit Ruşen

Metadata

Show full item record

Item Usage Stats

218
views

103
downloads

In many graph-based data mining tools, the use of numeric values as attributes in graphs is very limited. Most algorithms require pre-processing of the attributes, which often involves discretization into bins and embedding group names in the input graph(s). In this thesis, we tackle this problem by utilizing all attributes as is, and directly incorporating them into the pattern mining process. In order to implement our method, we modify an existing graph-based knowledge discovery algorithm, SUBDUE, by adding it the capability of working with continuous and discrete data vectors of any dimension. In addition, we propose an object detection framework using improved SUBDUE in its object matching step. This system detects repetitive objects such as buildings and airplanes in satellite images, once the user specifies a sample target by drawing a bounding box around it. Experiments on artificial and real datasets show that our contributions result from a robust and flexible approach that can generalize over a vast number of problems.

Subject Keywords

Data mining., Querying (Computer science)., Graph algorithms., Computer algorithms., Remote-sensing images

URI

http://etd.lib.metu.edu.tr/upload/12616389/index.pdf
https://hdl.handle.net/11511/23061

Collections

Graduate School of Natural and Applied Sciences, Thesis

Suggestions

OpenMETU
Core

An ilp-based concept discovery system for multi-relational data mining Kavurucu, Yusuf; Karagöz, Pınar; Department of Computer Engineering (2009) Multi Relational Data Mining has become popular due to the limitations of propositional problem definition in structured domains and the tendency of storing data in relational databases. However, as patterns involve multiple relations, the search space of possible hypothesis becomes intractably complex. In order to cope with this problem, several relational knowledge discovery systems have been developed employing various search strategies, heuristics and language pattern limitations. In this thesis, Induct...
A Content-Boosted Collaborative Filtering Approach for Movie Recommendation Based on Local and Global Similarity and Missing Data Prediction Özbal, Gozde; Karaman, Hilal; Alpaslan, Ferda Nur (Oxford University Press (OUP), 2011-09-01) Most traditional recommender systems lack accuracy in the case where data used in the recommendation process is sparse. This study addresses the sparsity problem and aims to get rid of it by means of a content-boosted collaborative filtering approach applied to a web-based movie recommendation system. The main motivation is to investigate whether further success can be obtained by combining 'local and global user similarity' and 'effective missing data prediction' approaches, which were previously introduce...
Improving the scalability of ILP-based multi-relational concept discovery system through parallelization Mutlu, Ayşe Ceyda; Karagöz, Pınar; Kavurucu, Yusuf (2012-03-01) Due to the increase in the amount of relational data that is being collected and the limitations of propositional problem definition in relational domains, multi-relational data mining has arisen to be able to extract patterns from relational data. In order to cope with intractably large search space and still to be able to generate high-quality patterns. ILP-based multi-relational data mining and concept discovery systems employ several search strategies and pattern limitations. Another direction to cope w...
ILP-based concept discovery in multi-relational data mining Kavurucu, Yusuf; Karagöz, Pınar; Toroslu, İsmail Hakkı (Elsevier BV, 2009-11-01) Multi-relational data mining has become popular due to the limitations of propositional problem definition in structured domains and the tendency of storing data in relational databases. Several relational knowledge discovery systems have been developed employing various search strategies, heuristics, language pattern limitations and hypothesis evaluation criteria, in order to cope with intractably large search space and to be able to generate high-quality patterns. In this work, an ILP-based concept discov...
An access structure for similarity-based fuzzy databases Yazıcı, Adnan (Elsevier BV, 1999-04-01) A significant effort has been made in representing imprecise information in database models by using fuzzy set theory. However, the research directed toward access structures to handle fuzzy querying effectively is still at an immature stage. Fuzzy querying involves more complex processing than the ordinary querying does. Additionally, a larger number of tuples are possibly selected by fuzzy conditions in comparison to the crisp ones. It is obvious that the need for fast response time becomes very important...

Citation Formats

Ü. R. Aktaş, “An Improved graph mining tool and its application to object detection in remote sensing,” M.S. - Master of Science, Middle East Technical University, 2013.