Ontology population using human computation

Download
index.pdf
2010
Evirgen, Gencay Kemal
Show full item record
132
views
142
downloads
In recent years, many researchers have developed new techniques on ontology population. However, these methods cannot overcome the semantic gap between humans and the extracted ontologies. Words-Around is a web application that forms a user-friendly environment which channels the vast Internet population to provide data towards solving ontology population problem that no known efficient computer algorithms can yet solve. This application’s fundamental data structure is a list of words that people naturally link to each other. It displays these lists as a word cloud that is fun to drag around and play with. Users are prompted to enter whatever word comes to their mind upon seeing a word that is suggested from the application’s database; or they can search for one word in particular to see what associations other users have made to it. Once logged in, users can view their activity history, which words they were the first to associate, and mark particular words as misspellings or as junk, to help keep the list’s structure to be relevant and accurate. The results of this implementation indicate the fact that an interesting application that enables users just to play with its visual elements can also be useful to gather information.
Computer enginnering., QA Computer Software 76.75-76.765
http://etd.lib.metu.edu.tr/upload/2/12611559/index.pdf
https://hdl.handle.net/11511/19405
Graduate School of Natural and Applied Sciences, Thesis

Suggestions

A systematic study of probabilistic aggregation strategies in swarm robotic systems
Soysal, Onur; Şahin, Erol; Department of Computer Engineering (2005)
In this study, a systematic analysis of probabilistic aggregation strategies in swarm robotic systems is presented. A generic aggregation behavior is proposed as a combination of four basic behaviors: obstacle avoidance, approach, repel, and wait. The latter three basic behaviors are combined using a three-state finite state machine with two probabilistic transitions among them. Two different metrics were used to compare performance of strategies. Through systematic experiments, how the aggregation performa...
Toward the frontiers of stacked generalization architecture for learning
Mertayak, Cüneyt; Yarman Vural, Fatoş Tunay; Department of Computer Engineering (2007)
In pattern recognition, “bias-variance” trade-off is a challenging issue that the scientists has been working to get better generalization performances over the last decades. Among many learning methods, two-layered homogeneous stacked generalization has been reported to be successful in the literature, in different problem domains such as object recognition and image annotation. The aim of this work is two-folded. First, the problems of stacked generalization are attacked by a proposed novel architecture. ...
A classification system for the problem of protein subcellular localization
Alay, Gökçen; Atalay, Mehmet Volkan; Department of Computer Engineering (2007)
The focus of this study is on predicting the subcellular localization of a protein. Subcellular localization information is important for protein function annotation which is a fundamental problem in computational biology. For this problem, a classification system is built that has two main parts: a predictor that is based on a feature mapping technique to extract biologically meaningful information from protein sequences and a client/server architecture for searching and predicting subcellular localization...
A hybrid recommendation system capturing the effect of time and demographic data
Oktay, Fulya; Alpaslan, Ferda Nur; Department of Computer Engineering (2010)
The information that World Wide Web (WWW) provides have grown up very rapidly in recent years, which resulted in new approaches for people to reach the information they need. Although web pages and search engines are indeed strong enough for us to reach what we want, it is not an efficient solution to present data and wait people to reach it. Some more creative and beneficial methods had to be developed for decreasing the time to reach the information and increase the quality of the information. Recommendat...
Subsequence feature maps for protein function annotation
Saraç, Ömer Sinan; Atalay, Mehmet Volkan; Department of Computer Engineering (2008)
With the advances in sequencing technologies, the number of protein sequences with unknown function increases rapidly. Hence, computational methods for functional annotation of these protein sequences become of the upmost importance. In this thesis, we first defined a feature space mapping of protein primary sequences to fixed dimensional numerical vectors. This mapping, which is called the Subsequence Profile Map (SPMap), takes into account the models of the subsequences of protein sequences. The resulting...
Citation Formats
G. K. Evirgen, “Ontology population using human computation,” M.S. - Master of Science, Middle East Technical University, 2010.
METU IIS - Integrated Information Service open@metu.edu.tr