pSPADE: Mining sequential pattern using personalized support threshold value

As the web log data is considered as complex and temporal, applying Sequential Pattern Mining technique becomes a challenging task.The min sup threshold issue is highlighted - as a pattern is considered as frequent if it meets the specified min sup.If the min sup is high, few patterns are discovered...

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Bibliografische gegevens
Hoofdauteurs: Alias, Suraya, Md Norwawi, Norita
Formaat: Conference or Workshop Item
Taal:English
Gepubliceerd in: 2008
Onderwerpen:
Online toegang:https://repo.uum.edu.my/id/eprint/4421/1/pS.pdf
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author Alias, Suraya
Md Norwawi, Norita
author_facet Alias, Suraya
Md Norwawi, Norita
author_sort Alias, Suraya
collection UUM
description As the web log data is considered as complex and temporal, applying Sequential Pattern Mining technique becomes a challenging task.The min sup threshold issue is highlighted - as a pattern is considered as frequent if it meets the specified min sup.If the min sup is high, few patterns are discovered else the mining process will be longer if too many patterns generated using low min sup. The format of web log data that creates consecutive occurring pages has made it difficult to generate frequent sequences. Also, as each user’ behaviour is unique; using one min sup value for all users may affect the pattern generation. This research introduced a personalized minimum support threshold for each web users using their Median item access (support) value to curb this problem.The pSPADE performance was the highest on the discovery of user’s origin and also interesting pattern discovery attribute.
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spelling uum-44212016-04-26T02:09:09Z https://repo.uum.edu.my/id/eprint/4421/ pSPADE: Mining sequential pattern using personalized support threshold value Alias, Suraya Md Norwawi, Norita QA76 Computer software As the web log data is considered as complex and temporal, applying Sequential Pattern Mining technique becomes a challenging task.The min sup threshold issue is highlighted - as a pattern is considered as frequent if it meets the specified min sup.If the min sup is high, few patterns are discovered else the mining process will be longer if too many patterns generated using low min sup. The format of web log data that creates consecutive occurring pages has made it difficult to generate frequent sequences. Also, as each user’ behaviour is unique; using one min sup value for all users may affect the pattern generation. This research introduced a personalized minimum support threshold for each web users using their Median item access (support) value to curb this problem.The pSPADE performance was the highest on the discovery of user’s origin and also interesting pattern discovery attribute. 2008 Conference or Workshop Item PeerReviewed application/pdf en https://repo.uum.edu.my/id/eprint/4421/1/pS.pdf Alias, Suraya and Md Norwawi, Norita (2008) pSPADE: Mining sequential pattern using personalized support threshold value. In: International Symposium on Information Technology 2008 (ITSim 2008), 26-28 August 2008 , Kuala Lumpur . http://dx.doi.org/10.1109/ITSIM.2008.4631672 doi:10.1109/ITSIM.2008.4631672 doi:10.1109/ITSIM.2008.4631672
spellingShingle QA76 Computer software
Alias, Suraya
Md Norwawi, Norita
pSPADE: Mining sequential pattern using personalized support threshold value
title pSPADE: Mining sequential pattern using personalized support threshold value
title_full pSPADE: Mining sequential pattern using personalized support threshold value
title_fullStr pSPADE: Mining sequential pattern using personalized support threshold value
title_full_unstemmed pSPADE: Mining sequential pattern using personalized support threshold value
title_short pSPADE: Mining sequential pattern using personalized support threshold value
title_sort pspade mining sequential pattern using personalized support threshold value
topic QA76 Computer software
url https://repo.uum.edu.my/id/eprint/4421/1/pS.pdf
work_keys_str_mv AT aliassuraya pspademiningsequentialpatternusingpersonalizedsupportthresholdvalue
AT mdnorwawinorita pspademiningsequentialpatternusingpersonalizedsupportthresholdvalue