Strong valid inequalities for Boolean logical pattern generation
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Yan, Kedong | - |
dc.contributor.author | Ryoo, Hong Seo | - |
dc.date.accessioned | 2021-09-03T02:19:01Z | - |
dc.date.available | 2021-09-03T02:19:01Z | - |
dc.date.created | 2021-06-16 | - |
dc.date.issued | 2017-09 | - |
dc.identifier.issn | 0925-5001 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/82392 | - |
dc.description.abstract | 0-1 multilinear programming (MP) captures the essence of pattern generation in logical analysis of data (LAD). This paper utilizes graph theoretic analysis of data to discover useful neighborhood properties among data for data reduction and multi-term linearization of the common constraint of an MP pattern generation model in a small number of stronger valid inequalities. This means that, with a systematic way to more efficiently generating Boolean logical patterns, LAD can be used for more effective analysis of data in practice. Mathematical properties and the utility of the new valid inequalities are illustrated on small examples and demonstrated through extensive experiments on 12 real-life data mining datasets. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | SPRINGER | - |
dc.subject | LOCAL SEARCH | - |
dc.subject | OPTIMIZATION | - |
dc.subject | MODELS | - |
dc.subject | RISK | - |
dc.title | Strong valid inequalities for Boolean logical pattern generation | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Ryoo, Hong Seo | - |
dc.identifier.doi | 10.1007/s10898-017-0512-2 | - |
dc.identifier.scopusid | 2-s2.0-85015625861 | - |
dc.identifier.wosid | 000408066400009 | - |
dc.identifier.bibliographicCitation | JOURNAL OF GLOBAL OPTIMIZATION, v.69, no.1, pp.183 - 230 | - |
dc.relation.isPartOf | JOURNAL OF GLOBAL OPTIMIZATION | - |
dc.citation.title | JOURNAL OF GLOBAL OPTIMIZATION | - |
dc.citation.volume | 69 | - |
dc.citation.number | 1 | - |
dc.citation.startPage | 183 | - |
dc.citation.endPage | 230 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Operations Research & Management Science | - |
dc.relation.journalResearchArea | Mathematics | - |
dc.relation.journalWebOfScienceCategory | Operations Research & Management Science | - |
dc.relation.journalWebOfScienceCategory | Mathematics, Applied | - |
dc.subject.keywordPlus | LOCAL SEARCH | - |
dc.subject.keywordPlus | OPTIMIZATION | - |
dc.subject.keywordPlus | MODELS | - |
dc.subject.keywordPlus | RISK | - |
dc.subject.keywordAuthor | Boolean logic | - |
dc.subject.keywordAuthor | Logical analysis of data | - |
dc.subject.keywordAuthor | Pattern | - |
dc.subject.keywordAuthor | 0-1 multilinear programming | - |
dc.subject.keywordAuthor | 0-1 linearization | - |
dc.subject.keywordAuthor | Hypercube | - |
dc.subject.keywordAuthor | Clique | - |
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