Optimizing the Management of Knowledge Assets using Swarm Intelligence

Knowledge assets are the knowledge drivers of an organization’s success and they can be of structured, unstructured, tacit or explicit knowledge. Explicit knowledge are realized as documents and these documents need to be tagged in order to ease the process of retrieval.Such document grouping p...

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Main Authors: Yusof, Yuhanis, Baharom, Fauziah, Mohamed, Athraa Jasim
Format: Conference or Workshop Item
Language:English
Published: 2018
Subjects:
Online Access:https://repo.uum.edu.my/id/eprint/25247/1/KMICE%202018%20330%20335.pdf
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author Yusof, Yuhanis
Baharom, Fauziah
Mohamed, Athraa Jasim
author_facet Yusof, Yuhanis
Baharom, Fauziah
Mohamed, Athraa Jasim
author_sort Yusof, Yuhanis
collection UUM
description Knowledge assets are the knowledge drivers of an organization’s success and they can be of structured, unstructured, tacit or explicit knowledge. Explicit knowledge are realized as documents and these documents need to be tagged in order to ease the process of retrieval.Such document grouping process can help an organisation to meet legal and regulatory requirements for retrieving specific information in a set timeframe. Current document clustering techniques rely on a pre-defined value of k (number of clusters). Hence, the produced clusters will be of different quality. This study presents the employment of swarm intelligence algorithm, i.e Firefly Algorithm, to automatically cluster text document without the use of k value. Experimental results shows that the performance of the algorithm is better compared to the benchmark methods. The number of obtained clusters are the same as the ones defined in the data collection while the purity value for three out of four datasets are higher than the benchmark methods. Hence, this indicates that the proposed swarm intelligence based clustering facilitates the grouping of knowledge assets. By having an automated document clustering, tagging the document with their appropriate label will help organization to better manage their knowledge assets.
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spelling uum-252472018-11-28T00:40:56Z https://repo.uum.edu.my/id/eprint/25247/ Optimizing the Management of Knowledge Assets using Swarm Intelligence Yusof, Yuhanis Baharom, Fauziah Mohamed, Athraa Jasim HD28 Management. Industrial Management Knowledge assets are the knowledge drivers of an organization’s success and they can be of structured, unstructured, tacit or explicit knowledge. Explicit knowledge are realized as documents and these documents need to be tagged in order to ease the process of retrieval.Such document grouping process can help an organisation to meet legal and regulatory requirements for retrieving specific information in a set timeframe. Current document clustering techniques rely on a pre-defined value of k (number of clusters). Hence, the produced clusters will be of different quality. This study presents the employment of swarm intelligence algorithm, i.e Firefly Algorithm, to automatically cluster text document without the use of k value. Experimental results shows that the performance of the algorithm is better compared to the benchmark methods. The number of obtained clusters are the same as the ones defined in the data collection while the purity value for three out of four datasets are higher than the benchmark methods. Hence, this indicates that the proposed swarm intelligence based clustering facilitates the grouping of knowledge assets. By having an automated document clustering, tagging the document with their appropriate label will help organization to better manage their knowledge assets. 2018-07-25 Conference or Workshop Item PeerReviewed application/pdf en https://repo.uum.edu.my/id/eprint/25247/1/KMICE%202018%20330%20335.pdf Yusof, Yuhanis and Baharom, Fauziah and Mohamed, Athraa Jasim (2018) Optimizing the Management of Knowledge Assets using Swarm Intelligence. In: Knowledge Management International Conference (KMICe) 2018, 25 –27 July 2018, Miri Sarawak, Malaysia. http://www.kmice.cms.net.my/ProcKMICe/KMICe2018/toc.html
spellingShingle HD28 Management. Industrial Management
Yusof, Yuhanis
Baharom, Fauziah
Mohamed, Athraa Jasim
Optimizing the Management of Knowledge Assets using Swarm Intelligence
title Optimizing the Management of Knowledge Assets using Swarm Intelligence
title_full Optimizing the Management of Knowledge Assets using Swarm Intelligence
title_fullStr Optimizing the Management of Knowledge Assets using Swarm Intelligence
title_full_unstemmed Optimizing the Management of Knowledge Assets using Swarm Intelligence
title_short Optimizing the Management of Knowledge Assets using Swarm Intelligence
title_sort optimizing the management of knowledge assets using swarm intelligence
topic HD28 Management. Industrial Management
url https://repo.uum.edu.my/id/eprint/25247/1/KMICE%202018%20330%20335.pdf
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