An integrated, generic approach to pattern mining: data mining template library.
Saved in:
| Title: | An integrated, generic approach to pattern mining: data mining template library. |
|---|---|
| Authors: | Chaoji, Vineet1 chaojv@cs.rpi.edu, Al Hasan, Mohammad1 alhasan@cs.rpi.edu, Salem, Saeed1 salems@cs.rpi.edu, Zaki, Mohammed1 zaki@cs.rpi.edu |
| Source: | Data Mining & Knowledge Discovery. Dec2008, Vol. 17 Issue 3, p457-495. 39p. 11 Diagrams, 1 Chart, 6 Graphs. |
| Subjects: | Data mining, Generic programming (Computer science), Database searching, Computer networks, Scalability, Systems design, Sequential pattern mining, Software patterns, Online data processing, Decision support systems |
| Abstract: | Frequent pattern mining (FPM) is an important data mining paradigm to extract informative patterns like itemsets, sequences, trees, and graphs. However, no practical framework for integrating the FPM tasks has been attempted. In this paper, we describe the design and implementation of the Data Mining Template Library (DMTL) for FPM. DMTL utilizes a generic data mining approach, where all aspects of mining are controlled via a set of properties. It uses a novel pattern property hierarchy to define and mine different pattern types. This property hierarchy can be thought of as a systematic characterization of the pattern space, i.e., a meta-pattern specification that allows the analyst to specify new pattern types, by extending this hierarchy. Furthermore, in DMTL all aspects of mining are controlled by a set of different mining properties. For example, the kind of mining approach to use, the kind of data types and formats to mine over, the kind of back-end storage manager to use, are all specified as a list of properties. This provides tremendous flexibility to customize the toolkit for various applications. Flexibility of the toolkit is exemplified by the ease with which support for a new pattern can be added. Experiments on synthetic and public dataset are conducted to demonstrate the scalability provided by the persistent back-end in the library. DMTL been publicly released as open-source software (), and has been downloaded by numerous researchers from all over the world. [ABSTRACT FROM AUTHOR] |
| Copyright of Data Mining & Knowledge Discovery is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
|---|---|
| Header | DbId: egs DbLabel: Engineering Source An: 34748891 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
| IllustrationInfo | |
| Items | – Name: Title Label: Title Group: Ti Data: An integrated, generic approach to pattern mining: data mining template library. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Chaoji%2C+Vineet%22">Chaoji, Vineet</searchLink><relatesTo>1</relatesTo><i> chaojv@cs.rpi.edu</i><br /><searchLink fieldCode="AR" term="%22Al+Hasan%2C+Mohammad%22">Al Hasan, Mohammad</searchLink><relatesTo>1</relatesTo><i> alhasan@cs.rpi.edu</i><br /><searchLink fieldCode="AR" term="%22Salem%2C+Saeed%22">Salem, Saeed</searchLink><relatesTo>1</relatesTo><i> salems@cs.rpi.edu</i><br /><searchLink fieldCode="AR" term="%22Zaki%2C+Mohammed%22">Zaki, Mohammed</searchLink><relatesTo>1</relatesTo><i> zaki@cs.rpi.edu</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Data+Mining+%26+Knowledge+Discovery%22">Data Mining & Knowledge Discovery</searchLink>. Dec2008, Vol. 17 Issue 3, p457-495. 39p. 11 Diagrams, 1 Chart, 6 Graphs. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Data+mining%22">Data mining</searchLink><br /><searchLink fieldCode="DE" term="%22Generic+programming+%28Computer+science%29%22">Generic programming (Computer science)</searchLink><br /><searchLink fieldCode="DE" term="%22Database+searching%22">Database searching</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+networks%22">Computer networks</searchLink><br /><searchLink fieldCode="DE" term="%22Scalability%22">Scalability</searchLink><br /><searchLink fieldCode="DE" term="%22Systems+design%22">Systems design</searchLink><br /><searchLink fieldCode="DE" term="%22Sequential+pattern+mining%22">Sequential pattern mining</searchLink><br /><searchLink fieldCode="DE" term="%22Software+patterns%22">Software patterns</searchLink><br /><searchLink fieldCode="DE" term="%22Online+data+processing%22">Online data processing</searchLink><br /><searchLink fieldCode="DE" term="%22Decision+support+systems%22">Decision support systems</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Frequent pattern mining (FPM) is an important data mining paradigm to extract informative patterns like itemsets, sequences, trees, and graphs. However, no practical framework for integrating the FPM tasks has been attempted. In this paper, we describe the design and implementation of the Data Mining Template Library (DMTL) for FPM. DMTL utilizes a generic data mining approach, where all aspects of mining are controlled via a set of properties. It uses a novel pattern property hierarchy to define and mine different pattern types. This property hierarchy can be thought of as a systematic characterization of the pattern space, i.e., a meta-pattern specification that allows the analyst to specify new pattern types, by extending this hierarchy. Furthermore, in DMTL all aspects of mining are controlled by a set of different mining properties. For example, the kind of mining approach to use, the kind of data types and formats to mine over, the kind of back-end storage manager to use, are all specified as a list of properties. This provides tremendous flexibility to customize the toolkit for various applications. Flexibility of the toolkit is exemplified by the ease with which support for a new pattern can be added. Experiments on synthetic and public dataset are conducted to demonstrate the scalability provided by the persistent back-end in the library. DMTL been publicly released as open-source software (), and has been downloaded by numerous researchers from all over the world. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Data Mining & Knowledge Discovery is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=34748891 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s10618-008-0098-x Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 39 StartPage: 457 Subjects: – SubjectFull: Data mining Type: general – SubjectFull: Generic programming (Computer science) Type: general – SubjectFull: Database searching Type: general – SubjectFull: Computer networks Type: general – SubjectFull: Scalability Type: general – SubjectFull: Systems design Type: general – SubjectFull: Sequential pattern mining Type: general – SubjectFull: Software patterns Type: general – SubjectFull: Online data processing Type: general – SubjectFull: Decision support systems Type: general Titles: – TitleFull: An integrated, generic approach to pattern mining: data mining template library. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Chaoji, Vineet – PersonEntity: Name: NameFull: Al Hasan, Mohammad – PersonEntity: Name: NameFull: Salem, Saeed – PersonEntity: Name: NameFull: Zaki, Mohammed IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 12 Text: Dec2008 Type: published Y: 2008 Identifiers: – Type: issn-print Value: 13845810 Numbering: – Type: volume Value: 17 – Type: issue Value: 3 Titles: – TitleFull: Data Mining & Knowledge Discovery Type: main |
| ResultId | 1 |
