Fast Single Pbase Algoritbm for Utility Mining in Big Data
Most of the latest works on utility mining generates a huge number of candidates in dealing with big data,which suffers from the scalability issue.Some work does not generate candidates,but suffers from the efficiency issue due to lack of strong pruning and high computation overhead.A novel algorith...
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| Format: | Article |
| Language: | zho |
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Beijing Xintong Media Co., Ltd
2015-04-01
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| Series: | Dianxin kexue |
| Subjects: | |
| Online Access: | http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2015100/ |
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| author | Junqiang Liu Qingfeng Zhou Wenhui Wang Lei Shi |
| author_facet | Junqiang Liu Qingfeng Zhou Wenhui Wang Lei Shi |
| author_sort | Junqiang Liu |
| collection | DOAJ |
| description | Most of the latest works on utility mining generates a huge number of candidates in dealing with big data,which suffers from the scalability issue.Some work does not generate candidates,but suffers from the efficiency issue due to lack of strong pruning and high computation overhead.A novel algorithm that finds high utility patterns in a single phase without generating candidates was proposed.The novelties lie in a prefix growth strategy with strong pruning,and a sparse matrix based representation of transactions with pseudo projection.The proposed algorithm works in a depth first manner and does not materialize high utility patterns in memory,which further improves the scalability.Extensive experiments on synthetic and rea1-world data show that the proposed algorithm outperforms the latest works in terms of running time,memory overhead,and scalability. |
| format | Article |
| id | doaj-art-7c3fcf465c8044f18a43057fad2e4f96 |
| institution | Kabale University |
| issn | 1000-0801 |
| language | zho |
| publishDate | 2015-04-01 |
| publisher | Beijing Xintong Media Co., Ltd |
| record_format | Article |
| series | Dianxin kexue |
| spelling | doaj-art-7c3fcf465c8044f18a43057fad2e4f962025-01-15T03:17:13ZzhoBeijing Xintong Media Co., LtdDianxin kexue1000-08012015-04-0131778559615235Fast Single Pbase Algoritbm for Utility Mining in Big DataJunqiang LiuQingfeng ZhouWenhui WangLei ShiMost of the latest works on utility mining generates a huge number of candidates in dealing with big data,which suffers from the scalability issue.Some work does not generate candidates,but suffers from the efficiency issue due to lack of strong pruning and high computation overhead.A novel algorithm that finds high utility patterns in a single phase without generating candidates was proposed.The novelties lie in a prefix growth strategy with strong pruning,and a sparse matrix based representation of transactions with pseudo projection.The proposed algorithm works in a depth first manner and does not materialize high utility patterns in memory,which further improves the scalability.Extensive experiments on synthetic and rea1-world data show that the proposed algorithm outperforms the latest works in terms of running time,memory overhead,and scalability.http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2015100/big datautility mininghigh utility patternfrequent pattern |
| spellingShingle | Junqiang Liu Qingfeng Zhou Wenhui Wang Lei Shi Fast Single Pbase Algoritbm for Utility Mining in Big Data Dianxin kexue big data utility mining high utility pattern frequent pattern |
| title | Fast Single Pbase Algoritbm for Utility Mining in Big Data |
| title_full | Fast Single Pbase Algoritbm for Utility Mining in Big Data |
| title_fullStr | Fast Single Pbase Algoritbm for Utility Mining in Big Data |
| title_full_unstemmed | Fast Single Pbase Algoritbm for Utility Mining in Big Data |
| title_short | Fast Single Pbase Algoritbm for Utility Mining in Big Data |
| title_sort | fast single pbase algoritbm for utility mining in big data |
| topic | big data utility mining high utility pattern frequent pattern |
| url | http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2015100/ |
| work_keys_str_mv | AT junqiangliu fastsinglepbasealgoritbmforutilitymininginbigdata AT qingfengzhou fastsinglepbasealgoritbmforutilitymininginbigdata AT wenhuiwang fastsinglepbasealgoritbmforutilitymininginbigdata AT leishi fastsinglepbasealgoritbmforutilitymininginbigdata |