Comparative study of apriori-variant algorithms
Big Data era is currently generating tremendous amount of data in various fields such as finance, social media, transportation and medicine. Handling and processing this “big data” demand powerful data mining methods and analysis tools that can turn data into useful knowledge. One of data mining m...
| Главные авторы: | , , , |
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| Формат: | Conference or Workshop Item |
| Язык: | English |
| Опубликовано: |
2016
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| Предметы: | |
| Online-ссылка: | https://repo.uum.edu.my/id/eprint/20082/1/KMICe2016%20203%20208.pdf |
| _version_ | 1825804303382609920 |
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| author | Mutalib, Sofianita Abdul Subar, Ammar Azri Abdul Rahman, Shuzlina Mohamed, Azlinah |
| author_facet | Mutalib, Sofianita Abdul Subar, Ammar Azri Abdul Rahman, Shuzlina Mohamed, Azlinah |
| author_sort | Mutalib, Sofianita |
| collection | UUM |
| description | Big Data era is currently generating tremendous
amount of data in various fields such as finance,
social media, transportation and medicine. Handling and processing this “big data” demand powerful data mining methods and analysis tools that can turn data into useful knowledge. One of data mining methods is frequent itemset mining that has been implemented in real world applications, such as identifying buying
patterns in grocery and online customers’ behavior.Apriori is a classical algorithm in frequent itemset mining, that able to discover large number or itemset with a certain threshold value. However, the algorithm suffers from scanning time problem while generating candidates of frequent itemsets.This study presents a comparative study between several Apriori-variant algorithms and examines their scanning time.We performed experiments using several sets of different transactional data.The result shows that the improved Apriori algorithm manage to
produce itemsets faster than the original Apriori
algorithm. |
| first_indexed | 2024-07-04T06:12:22Z |
| format | Conference or Workshop Item |
| id | uum-20082 |
| institution | Universiti Utara Malaysia |
| language | English |
| last_indexed | 2024-07-04T06:12:22Z |
| publishDate | 2016 |
| record_format | eprints |
| spelling | uum-200822020-11-01T08:11:02Z https://repo.uum.edu.my/id/eprint/20082/ Comparative study of apriori-variant algorithms Mutalib, Sofianita Abdul Subar, Ammar Azri Abdul Rahman, Shuzlina Mohamed, Azlinah QA Mathematics Big Data era is currently generating tremendous amount of data in various fields such as finance, social media, transportation and medicine. Handling and processing this “big data” demand powerful data mining methods and analysis tools that can turn data into useful knowledge. One of data mining methods is frequent itemset mining that has been implemented in real world applications, such as identifying buying patterns in grocery and online customers’ behavior.Apriori is a classical algorithm in frequent itemset mining, that able to discover large number or itemset with a certain threshold value. However, the algorithm suffers from scanning time problem while generating candidates of frequent itemsets.This study presents a comparative study between several Apriori-variant algorithms and examines their scanning time.We performed experiments using several sets of different transactional data.The result shows that the improved Apriori algorithm manage to produce itemsets faster than the original Apriori algorithm. 2016-08-29 Conference or Workshop Item PeerReviewed application/pdf en https://repo.uum.edu.my/id/eprint/20082/1/KMICe2016%20203%20208.pdf Mutalib, Sofianita and Abdul Subar, Ammar Azri and Abdul Rahman, Shuzlina and Mohamed, Azlinah (2016) Comparative study of apriori-variant algorithms. In: Knowledge Management International Conference (KMICe) 2016, 29 – 30 August 2016, Chiang Mai, Thailand. http://www.kmice.cms.net.my/kmice2016/files/KMICe2016_eproceeding.pdf |
| spellingShingle | QA Mathematics Mutalib, Sofianita Abdul Subar, Ammar Azri Abdul Rahman, Shuzlina Mohamed, Azlinah Comparative study of apriori-variant algorithms |
| title | Comparative study of apriori-variant algorithms |
| title_full | Comparative study of apriori-variant algorithms |
| title_fullStr | Comparative study of apriori-variant algorithms |
| title_full_unstemmed | Comparative study of apriori-variant algorithms |
| title_short | Comparative study of apriori-variant algorithms |
| title_sort | comparative study of apriori variant algorithms |
| topic | QA Mathematics |
| url | https://repo.uum.edu.my/id/eprint/20082/1/KMICe2016%20203%20208.pdf |
| work_keys_str_mv | AT mutalibsofianita comparativestudyofapriorivariantalgorithms AT abdulsubarammarazri comparativestudyofapriorivariantalgorithms AT abdulrahmanshuzlina comparativestudyofapriorivariantalgorithms AT mohamedazlinah comparativestudyofapriorivariantalgorithms |