FpGrowth algorithm-based pruning strategy
An FpGrowth algorithm is an association rule mining algorithm which does not generate candidate sets, and has a wide practical application value. Through deeply analyzing and researching a structure and a mining process of an FP-tree of a classic FpGrowth algorithm, and analyzing a single-path minin...
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| creator | WANG WEI LIU HAI LI YUAN WU ZHAOXIA CHU ZENAN |
| description | An FpGrowth algorithm is an association rule mining algorithm which does not generate candidate sets, and has a wide practical application value. Through deeply analyzing and researching a structure and a mining process of an FP-tree of a classic FpGrowth algorithm, and analyzing a single-path mining method and a multi-path mining method of the FP-tree, the invention discloses a pruning strategy which is capable of decreasing the iteration frequencies of a part of branches. Experiment results prove that the pruning strategy is capable of effectively improving the algorithm and improving the data processing ability and efficiency of the FpGrowth algorithm.
FpGrowth算法是不产生候选集的关联规则挖掘算法，具有广泛的实际应用价值。为此对经典FpGrowth算法的FP-tree的结构和挖掘过程进行了深入分析和研究，分析了FP-tree单路径和多路径的挖掘方法，提出了个剪枝策略，在频繁模式挖掘时可以减少部分分支的迭代次数。实验结果验证提出的剪枝策略有效地改进了算法，并提高了FpGrowth算法对数据的处理能力和效率。 |
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FpGrowth算法是不产生候选集的关联规则挖掘算法，具有广泛的实际应用价值。为此对经典FpGrowth算法的FP-tree的结构和挖掘过程进行了深入分析和研究，分析了FP-tree单路径和多路径的挖掘方法，提出了个剪枝策略，在频繁模式挖掘时可以减少部分分支的迭代次数。实验结果验证提出的剪枝策略有效地改进了算法，并提高了FpGrowth算法对数据的处理能力和效率。</description><language>chi ; eng</language><subject>CALCULATING ; COMPUTING ; COUNTING ; ELECTRIC DIGITAL DATA PROCESSING ; PHYSICS</subject><creationdate>2018</creationdate><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20181123&DB=EPODOC&CC=CN&NR=108875015A$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,309,782,887,25571,76555</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20181123&DB=EPODOC&CC=CN&NR=108875015A$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>WANG WEI</creatorcontrib><creatorcontrib>LIU HAI</creatorcontrib><creatorcontrib>LI YUAN</creatorcontrib><creatorcontrib>WU ZHAOXIA</creatorcontrib><creatorcontrib>CHU ZENAN</creatorcontrib><title>FpGrowth algorithm-based pruning strategy</title><description>An FpGrowth algorithm is an association rule mining algorithm which does not generate candidate sets, and has a wide practical application value. Through deeply analyzing and researching a structure and a mining process of an FP-tree of a classic FpGrowth algorithm, and analyzing a single-path mining method and a multi-path mining method of the FP-tree, the invention discloses a pruning strategy which is capable of decreasing the iteration frequencies of a part of branches. Experiment results prove that the pruning strategy is capable of effectively improving the algorithm and improving the data processing ability and efficiency of the FpGrowth algorithm.
FpGrowth算法是不产生候选集的关联规则挖掘算法，具有广泛的实际应用价值。为此对经典FpGrowth算法的FP-tree的结构和挖掘过程进行了深入分析和研究，分析了FP-tree单路径和多路径的挖掘方法，提出了个剪枝策略，在频繁模式挖掘时可以减少部分分支的迭代次数。实验结果验证提出的剪枝策略有效地改进了算法，并提高了FpGrowth算法对数据的处理能力和效率。</description><subject>CALCULATING</subject><subject>COMPUTING</subject><subject>COUNTING</subject><subject>ELECTRIC DIGITAL DATA PROCESSING</subject><subject>PHYSICS</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2018</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNrjZNB0K3Avyi8vyVBIzEnPL8osycjVTUosTk1RKCgqzcvMS1coLilKLElNr-RhYE1LzClO5YXS3AyKbq4hzh66qQX58anFBYnJqXmpJfHOfoYGFhbmpgaGpo7GxKgBACbNKRA</recordid><startdate>20181123</startdate><enddate>20181123</enddate><creator>WANG WEI</creator><creator>LIU HAI</creator><creator>LI YUAN</creator><creator>WU ZHAOXIA</creator><creator>CHU ZENAN</creator><scope>EVB</scope></search><sort><creationdate>20181123</creationdate><title>FpGrowth algorithm-based pruning strategy</title><author>WANG WEI ; LIU HAI ; LI YUAN ; WU ZHAOXIA ; CHU ZENAN</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_CN108875015A3</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>chi ; eng</language><creationdate>2018</creationdate><topic>CALCULATING</topic><topic>COMPUTING</topic><topic>COUNTING</topic><topic>ELECTRIC DIGITAL DATA PROCESSING</topic><topic>PHYSICS</topic><toplevel>online_resources</toplevel><creatorcontrib>WANG WEI</creatorcontrib><creatorcontrib>LIU HAI</creatorcontrib><creatorcontrib>LI YUAN</creatorcontrib><creatorcontrib>WU ZHAOXIA</creatorcontrib><creatorcontrib>CHU ZENAN</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>WANG WEI</au><au>LIU HAI</au><au>LI YUAN</au><au>WU ZHAOXIA</au><au>CHU ZENAN</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>FpGrowth algorithm-based pruning strategy</title><date>2018-11-23</date><risdate>2018</risdate><abstract>An FpGrowth algorithm is an association rule mining algorithm which does not generate candidate sets, and has a wide practical application value. Through deeply analyzing and researching a structure and a mining process of an FP-tree of a classic FpGrowth algorithm, and analyzing a single-path mining method and a multi-path mining method of the FP-tree, the invention discloses a pruning strategy which is capable of decreasing the iteration frequencies of a part of branches. Experiment results prove that the pruning strategy is capable of effectively improving the algorithm and improving the data processing ability and efficiency of the FpGrowth algorithm.
FpGrowth算法是不产生候选集的关联规则挖掘算法，具有广泛的实际应用价值。为此对经典FpGrowth算法的FP-tree的结构和挖掘过程进行了深入分析和研究，分析了FP-tree单路径和多路径的挖掘方法，提出了个剪枝策略，在频繁模式挖掘时可以减少部分分支的迭代次数。实验结果验证提出的剪枝策略有效地改进了算法，并提高了FpGrowth算法对数据的处理能力和效率。</abstract><oa>free_for_read</oa></addata></record> |
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| subjects | CALCULATING COMPUTING COUNTING ELECTRIC DIGITAL DATA PROCESSING PHYSICS |
| title | FpGrowth algorithm-based pruning strategy |
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