Implementation and integration of clustering method to web based clustering engine

In this project, two tasks have been implemented. First, a new semi-supervised collaborative clustering process has been diligently researched and implemented. Second, an in-house developed unsupervised clustering algorithm HFCR has been successfully integrated into a web based clustering engine Car...

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Main Author: Vaibhav Vij
Other Authors: Chen Lihui
Format: Final Year Project
Language:English
Published: 2012
Subjects:
Online Access:http://hdl.handle.net/10356/49857
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-498572023-07-07T15:51:47Z Implementation and integration of clustering method to web based clustering engine Vaibhav Vij Chen Lihui School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems In this project, two tasks have been implemented. First, a new semi-supervised collaborative clustering process has been diligently researched and implemented. Second, an in-house developed unsupervised clustering algorithm HFCR has been successfully integrated into a web based clustering engine Carrot2 in Eclipse. The report covers the literature review on both the clustering methods used in this project. It has also documented the design and implementation related to both the algorithms. Preliminary simulations were carried out for the collaborative process on a high dimensional dataset, RE-1. The collaborative process used a small set of labelled samples to discover other relevant patterns in the dataset. The results obtained are tabulated and thoroughly discussed. A quick test on HFCR with a given user query in Carrot2 framework has been carried out to demonstrate and report the success of the implementation. Bachelor of Engineering 2012-05-25T02:46:02Z 2012-05-25T02:46:02Z 2012 2012 Final Year Project (FYP) http://hdl.handle.net/10356/49857 en Nanyang Technological University 62 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems
spellingShingle DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems
Vaibhav Vij
Implementation and integration of clustering method to web based clustering engine
description In this project, two tasks have been implemented. First, a new semi-supervised collaborative clustering process has been diligently researched and implemented. Second, an in-house developed unsupervised clustering algorithm HFCR has been successfully integrated into a web based clustering engine Carrot2 in Eclipse. The report covers the literature review on both the clustering methods used in this project. It has also documented the design and implementation related to both the algorithms. Preliminary simulations were carried out for the collaborative process on a high dimensional dataset, RE-1. The collaborative process used a small set of labelled samples to discover other relevant patterns in the dataset. The results obtained are tabulated and thoroughly discussed. A quick test on HFCR with a given user query in Carrot2 framework has been carried out to demonstrate and report the success of the implementation.
author2 Chen Lihui
author_facet Chen Lihui
Vaibhav Vij
format Final Year Project
author Vaibhav Vij
author_sort Vaibhav Vij
title Implementation and integration of clustering method to web based clustering engine
title_short Implementation and integration of clustering method to web based clustering engine
title_full Implementation and integration of clustering method to web based clustering engine
title_fullStr Implementation and integration of clustering method to web based clustering engine
title_full_unstemmed Implementation and integration of clustering method to web based clustering engine
title_sort implementation and integration of clustering method to web based clustering engine
publishDate 2012
url http://hdl.handle.net/10356/49857
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