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New Algorithms for Fast Discovery of Association Rules
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You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. --> <table class="greyBorderTable" > <tr> <td width="10" class="noBorderTabletd"></td> <td class="bottomBorder" align="left"> <span class="whiteFileImg"></span><!-- the is Preview flag indicates that the file is being previewed by a user this should be passed in by the importing file --> <a href="/fileDownloadForInstitutionalItem.action;jsessionid=0C2EBDA4EA2E558C0DED40C7FA55E5C9?itemId=360&itemFileId=449" > 97.tr651.New_algorithms_for_fast_discovery_of_association_rul.ps</a> 395.27 KB (No. of downloads : 255) <br/> </td> <td class="bottomBorder" align="left"> </td> </tr> </table><!-- Copyright 2008 University of Rochester Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. --> <table class="greyBorderBlueBgTable"> <tr> <td width="60%" valign="top" class="greyBorderTableTd"> <table class="noPaddingTable" width="100%" align="left"> <tr> <td> <label for="abstract" class="previewLabel"> Abstract </label> </td> </tr> <tr> <td> Association rule discovery has emerged as an important problem in knowledge discovery and data mining. The association mining task consists of identifying the frequent itemsets, and then forming conditional implication rules among them. In this paper we present efficient algorithms for the discovery of frequent itemsets, which forms the compute intensive phase of the task. The algorithms utilize the structural properties of frequent itemsets to facilitate fast discovery. The related database items are grouped together into clusters representing the potential maximal frequent itemsets in the database. Each cluster induces a sub-lattice of the itemset lattice. Efficient lattice traversal techniques are presented, which quickly identify all the true maximal frequent itemsets, and all their subsets if desired. We also present the effect of using different database layout schemes combined with the proposed clustering and traversal techniques. The proposed algorithms scan a (pre-processed) database only once, addressing the open question in association mining, whether all the rules can be efficiently extracted in a single database pass. We experimentally compare the new algorithms against the previous approaches, obtaining improvements of more than an order of magnitude for our test databases.</td> </tr> </table> </td> <td valign="top" class="greyBorderTableTd"> <table width="100%"> <tr> <td class="previewLabel">Contributor(s):</td> </tr> <tr> <td> <a href="/viewContributorPage.action;jsessionid=0C2EBDA4EA2E558C0DED40C7FA55E5C9?personNameId=183"> Mohammed Javeed Zaki </a> - Author<br/><br/> </td> </tr> <tr> <td> <a href="/viewContributorPage.action;jsessionid=0C2EBDA4EA2E558C0DED40C7FA55E5C9?personNameId=195"> Srinivasan Parthasarathy </a> - Author<br/><br/> </td> </tr> <tr> <td> <a href="/viewContributorPage.action;jsessionid=0C2EBDA4EA2E558C0DED40C7FA55E5C9?personNameId=185"> Mitsunori Ogihara (1963 - )</a> - Author<br/><br/> </td> </tr> <tr> <td> <a href="/viewContributorPage.action;jsessionid=0C2EBDA4EA2E558C0DED40C7FA55E5C9?personNameId=198"> Wei Li </a> - Author<br/><br/> </td> </tr> <tr> <td class="previewLabel"> Primary Item Type: </td> </tr> <tr> <td> Technical Report</td> </tr> <tr> <td class="previewLabel"> Series/Report Number:</td> </tr> <tr> <td> UR CSD / TR651</td> </tr> <tr> <td class="previewLabel"> Language:</td> </tr> <tr> <td> English</td> </tr> <tr> <td class="previewLabel"> Subject Keywords: </td> </tr> <tr> <td> frequent itemsets;association rules;knowledge discovery and data mining;parallel algorithms;maximal hypergraph cliques;lattice traversals</td> </tr> <tr> <td class="previewLabel"> First presented to the public:</td> </tr> <tr> <td>7/22/2004</td> </tr> <tr> <td class="previewLabel">Original Publication Date:</td> </tr> <tr> <td>7/1997</td> </tr> <tr> <td class="previewLabel">Previously Published By:</td> </tr> <tr> <td>University of Rochester. Computer Science Department.</td> </tr> <tr> <td class="previewLabel">License Grantor / Date Granted: </td> </tr> <tr> <td> Suzanne S. Bell / 2004-07-22 21:39:32.0 ( <a href="viewItemRepositoryLicense.action;jsessionid=0C2EBDA4EA2E558C0DED40C7FA55E5C9?versionedLicenseId=1&version=1">View License</a> ) </td> </tr> <tr> <td class="previewLabel">Date Deposited</td> </tr> <tr> <td> 2004-07-22 21:39:32.0</td> </tr> <tr> <td class="previewLabel">Date Last Updated</td> </tr> <tr> <td> 2012-09-26 16:35:14.586719</td> </tr> <tr> <td class="previewLabel">Submitter:</td> </tr> <tr> <td> Suzanne S. Bell</td> </tr> </table> </td> </tr> <tr> <td colspan="2" class="greyBorderTableTd"> <p>Copyright © This item is protected by copyright, with all rights reserved.</p> </td> </tr> </table><!-- End - Display the Item preview --> <!-- end if for show publication --> <!-- ************************* All versions Start ************************* --> <h3>All Versions</h3> <div class="dataTable"> <table width="100%" ><thead ><tr ><td > Thumbnail </td><td > Name </td><td > Version </td><td > Created Date </td></tr></thead><tbody ><tr onmouseover="this.className='highlight'" onmouseout="this.className='even'" class="even" ><td ></td><td >New Algorithms for Fast Discovery of Association Rules</td><td ><a href="institutionalPublicationPublicView.action;jsessionid=0C2EBDA4EA2E558C0DED40C7FA55E5C9?institutionalItemId=360&versionNumber=1">1</a> </td><td >2004-07-22 21:39:32.0</td></tr></tbody></table></div> <!-- ************************* All versions End ************************* --> </div> <!-- end the body tag --> <!-- this is the footer of the page --> <!-- Copyright 2008 University of Rochester Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. 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