FGC: An Efficient Constraint Based Frequent Set Miner
Despite advances in algorithmic design, association rule mining remains problematic from a performance viewpoint when the size of the underlying transaction database is large. The well-known a priori approach, while reducing the computational effort involved still suffers from the problem of scalabi...
Gespeichert in:
| Hauptverfasser: | , |
|---|---|
| Format: | Tagungsbericht |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext bestellen |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 431 |
|---|---|
| container_issue | |
| container_start_page | 424 |
| container_title | |
| container_volume | |
| creator | Pears, R. Kutty, S. |
| description | Despite advances in algorithmic design, association rule mining remains problematic from a performance viewpoint when the size of the underlying transaction database is large. The well-known a priori approach, while reducing the computational effort involved still suffers from the problem of scalability due to its reliance on generating candidate itemsets. In this paper we present a novel approach that combines the power of preprocessing with the application of user-defined constraints to prune the itemset space prior to building a compact FP-tree. Experimentation shows that that our algorithm significantly outperforms the current state of the art algorithm, FP-bonsai. |
| doi_str_mv | 10.1109/AICCSA.2007.370916 |
| format | Conference Proceeding |
| fullrecord | <record><control><sourceid>ieee_6IE</sourceid><recordid>TN_cdi_ieee_primary_4230991</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>4230991</ieee_id><sourcerecordid>4230991</sourcerecordid><originalsourceid>FETCH-LOGICAL-i219t-8ec8f7259a40fce2218812a81f319b5e540fcbe3a31c63cdc031462045ae73b33</originalsourceid><addsrcrecordid>eNo9j8tOwzAURM1Loi39AdjkBxLuw05sdsFqSqUiFoV15aQ3khEESMKCv6cVj9UczZFGGqUuETJEcNflyvtNmRFAkXEBDvMjNXeFRU1aIzDmx2pCmGNqmOFETf8E6NN_QXSupsPwDMCOrJkoUy39TVJ2yaJtYxOlGxP_1g1jH-Ieb8Mgu6Tq5ePzYDYyJvexk_5CnbXhZZD5b87UU7V49Hfp-mG58uU6jYRuTK00ti3IuKChbYQIrUUKFltGVxsxh7oWDoxNzs2u2b_QOYE2QQqumWfq6mc3isj2vY-vof_aamJwDvkbqCRHww</addsrcrecordid><sourcetype>Publisher</sourcetype><iscdi>true</iscdi><recordtype>conference_proceeding</recordtype></control><display><type>conference_proceeding</type><title>FGC: An Efficient Constraint Based Frequent Set Miner</title><source>IEEE Electronic Library (IEL) Conference Proceedings</source><creator>Pears, R. ; Kutty, S.</creator><creatorcontrib>Pears, R. ; Kutty, S.</creatorcontrib><description>Despite advances in algorithmic design, association rule mining remains problematic from a performance viewpoint when the size of the underlying transaction database is large. The well-known a priori approach, while reducing the computational effort involved still suffers from the problem of scalability due to its reliance on generating candidate itemsets. In this paper we present a novel approach that combines the power of preprocessing with the application of user-defined constraints to prune the itemset space prior to building a compact FP-tree. Experimentation shows that that our algorithm significantly outperforms the current state of the art algorithm, FP-bonsai.</description><identifier>ISSN: 2161-5322</identifier><identifier>ISBN: 1424410304</identifier><identifier>ISBN: 9781424410309</identifier><identifier>EISSN: 2161-5330</identifier><identifier>EISBN: 9781424410316</identifier><identifier>EISBN: 1424410312</identifier><identifier>DOI: 10.1109/AICCSA.2007.370916</identifier><language>eng</language><publisher>IEEE</publisher><subject>Algorithm design and analysis ; Association rules ; Bridges ; Costs ; Dairy products ; Data mining ; Itemsets ; Performance gain ; Scalability ; Transaction databases</subject><ispartof>2007 IEEE/ACS International Conference on Computer Systems and Applications, 2007, p.424-431</ispartof><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://ieeexplore.ieee.org/document/4230991$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,780,784,789,790,2058,27925,54920</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/4230991$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Pears, R.</creatorcontrib><creatorcontrib>Kutty, S.</creatorcontrib><title>FGC: An Efficient Constraint Based Frequent Set Miner</title><title>2007 IEEE/ACS International Conference on Computer Systems and Applications</title><addtitle>AICCSA</addtitle><description>Despite advances in algorithmic design, association rule mining remains problematic from a performance viewpoint when the size of the underlying transaction database is large. The well-known a priori approach, while reducing the computational effort involved still suffers from the problem of scalability due to its reliance on generating candidate itemsets. In this paper we present a novel approach that combines the power of preprocessing with the application of user-defined constraints to prune the itemset space prior to building a compact FP-tree. Experimentation shows that that our algorithm significantly outperforms the current state of the art algorithm, FP-bonsai.</description><subject>Algorithm design and analysis</subject><subject>Association rules</subject><subject>Bridges</subject><subject>Costs</subject><subject>Dairy products</subject><subject>Data mining</subject><subject>Itemsets</subject><subject>Performance gain</subject><subject>Scalability</subject><subject>Transaction databases</subject><issn>2161-5322</issn><issn>2161-5330</issn><isbn>1424410304</isbn><isbn>9781424410309</isbn><isbn>9781424410316</isbn><isbn>1424410312</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2007</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNo9j8tOwzAURM1Loi39AdjkBxLuw05sdsFqSqUiFoV15aQ3khEESMKCv6cVj9UczZFGGqUuETJEcNflyvtNmRFAkXEBDvMjNXeFRU1aIzDmx2pCmGNqmOFETf8E6NN_QXSupsPwDMCOrJkoUy39TVJ2yaJtYxOlGxP_1g1jH-Ieb8Mgu6Tq5ePzYDYyJvexk_5CnbXhZZD5b87UU7V49Hfp-mG58uU6jYRuTK00ti3IuKChbYQIrUUKFltGVxsxh7oWDoxNzs2u2b_QOYE2QQqumWfq6mc3isj2vY-vof_aamJwDvkbqCRHww</recordid><startdate>200705</startdate><enddate>200705</enddate><creator>Pears, R.</creator><creator>Kutty, S.</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>200705</creationdate><title>FGC: An Efficient Constraint Based Frequent Set Miner</title><author>Pears, R. ; Kutty, S.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i219t-8ec8f7259a40fce2218812a81f319b5e540fcbe3a31c63cdc031462045ae73b33</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2007</creationdate><topic>Algorithm design and analysis</topic><topic>Association rules</topic><topic>Bridges</topic><topic>Costs</topic><topic>Dairy products</topic><topic>Data mining</topic><topic>Itemsets</topic><topic>Performance gain</topic><topic>Scalability</topic><topic>Transaction databases</topic><toplevel>online_resources</toplevel><creatorcontrib>Pears, R.</creatorcontrib><creatorcontrib>Kutty, S.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Pears, R.</au><au>Kutty, S.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>FGC: An Efficient Constraint Based Frequent Set Miner</atitle><btitle>2007 IEEE/ACS International Conference on Computer Systems and Applications</btitle><stitle>AICCSA</stitle><date>2007-05</date><risdate>2007</risdate><spage>424</spage><epage>431</epage><pages>424-431</pages><issn>2161-5322</issn><eissn>2161-5330</eissn><isbn>1424410304</isbn><isbn>9781424410309</isbn><eisbn>9781424410316</eisbn><eisbn>1424410312</eisbn><abstract>Despite advances in algorithmic design, association rule mining remains problematic from a performance viewpoint when the size of the underlying transaction database is large. The well-known a priori approach, while reducing the computational effort involved still suffers from the problem of scalability due to its reliance on generating candidate itemsets. In this paper we present a novel approach that combines the power of preprocessing with the application of user-defined constraints to prune the itemset space prior to building a compact FP-tree. Experimentation shows that that our algorithm significantly outperforms the current state of the art algorithm, FP-bonsai.</abstract><pub>IEEE</pub><doi>10.1109/AICCSA.2007.370916</doi><tpages>8</tpages><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext_linktorsrc |
| identifier | ISSN: 2161-5322 |
| ispartof | 2007 IEEE/ACS International Conference on Computer Systems and Applications, 2007, p.424-431 |
| issn | 2161-5322 2161-5330 |
| language | eng |
| recordid | cdi_ieee_primary_4230991 |
| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Algorithm design and analysis Association rules Bridges Costs Dairy products Data mining Itemsets Performance gain Scalability Transaction databases |
| title | FGC: An Efficient Constraint Based Frequent Set Miner |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-25T20%3A06%3A04IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-ieee_6IE&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=proceeding&rft.atitle=FGC:%20An%20Efficient%20Constraint%20Based%20Frequent%20Set%20Miner&rft.btitle=2007%20IEEE/ACS%20International%20Conference%20on%20Computer%20Systems%20and%20Applications&rft.au=Pears,%20R.&rft.date=2007-05&rft.spage=424&rft.epage=431&rft.pages=424-431&rft.issn=2161-5322&rft.eissn=2161-5330&rft.isbn=1424410304&rft.isbn_list=9781424410309&rft_id=info:doi/10.1109/AICCSA.2007.370916&rft_dat=%3Cieee_6IE%3E4230991%3C/ieee_6IE%3E%3Curl%3E%3C/url%3E&rft.eisbn=9781424410316&rft.eisbn_list=1424410312&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rft_ieee_id=4230991&rfr_iscdi=true |