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: | , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2018
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| Subjects: | |
| Online Access: | http://repo.uum.edu.my/25247/1/KMICE%202018%20330%20335.pdf http://repo.uum.edu.my/25247/ http://www.kmice.cms.net.my/ProcKMICe/KMICe2018/toc.html |
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| Summary: | 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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