Zobrazeno 1 - 10
of 56
pro vyhledávání: '"Fedja Hadzic"'
Publikováno v:
Information Sciences. 310:97-117
Frequent subtree mining is a major research topic in knowledge discovery from tree-structured data, whose importance is witnessed by the pervasiveness of such data in several domains. In this paper, we present a novel approach to discover all the fre
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::94ba9e04c0ed400bc4b4ad3cd56153f4
https://doi.org/10.1016/j.ins.2015.03.015
https://doi.org/10.1016/j.ins.2015.03.015
Evaluation of an associative classifier based on position-constrained frequent/closed subtree mining
Publikováno v:
Journal of Intelligent Information Systems. 45:397-421
Tree-structured data are popular in many domains making structural classification an important task. In this paper, an associative classification method is introduced based on a structure preserving flat representation of trees. A major difference to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3f32d37d9e963d6cf76b9badae7f842c
https://doi.org/10.1007/s10844-014-0312-9
https://doi.org/10.1007/s10844-014-0312-9
Publikováno v:
Statistics and Computing. 24:821-843
Real world applications of association rule mining have well-known problems of discovering a large number of rules, many of which are not interesting or useful for the application at hand. The algorithms for closed and maximal itemsets mining signifi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4852235f9300affe2266618a4b53f932
https://doi.org/10.1007/s11222-013-9404-6
https://doi.org/10.1007/s11222-013-9404-6
Publikováno v:
Fundamenta Informaticae. 119:187-231
The increasing need for representing information through more complex structures where semantics and relationships among data objects can be more easily expressed has resulted in many semi-structured data sources. Structure comparison among semi-stru
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7c05a8ffae98e526a96da0f31da18462
https://doi.org/10.3233/fi-2012-733
https://doi.org/10.3233/fi-2012-733
Publikováno v:
Knowledge-Based Systems. 24:386-392
Assessing rules with interestingness measures is the pillar of successful application of association rules discovery. However, association rules discovered are normally large in number, some of which are not considered as interesting or significant f
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9d81f7d6837cf2e75ebc0357a348e126
https://doi.org/10.1016/j.knosys.2010.11.005
https://doi.org/10.1016/j.knosys.2010.11.005
Publikováno v:
Web Intelligence and Agent Systems: An International Journal. 8:413-430
Large amount of online information is or can be represented using semi-structured documents, such as XML. The information contained in an XML document can be effectively represented using a rooted ordered labeled tree. This has made the frequent patt
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b4856fa7abf71fba8faa86e1f7ddef83
https://doi.org/10.3233/wia-2010-0200
https://doi.org/10.3233/wia-2010-0200
Publikováno v:
Scopus-Elsevier
Due to the inherent flexibilities in both structure and semantics, XML association rules mining faces few challenges, such as: a more complicated hierarchical data structure and ordered data context. Mining frequent patterns from XML documents can be
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b0bacb0c81b107a53251e19aada28d31
https://doi.org/10.1145/1376815.1376818
https://doi.org/10.1145/1376815.1376818
Publikováno v:
Advances in Knowledge Discovery and Data Mining ISBN: 9783540332060
PAKDD
Scopus-Elsevier
Proceedings of the 10th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining (PAKDD 2006), 450-461
STARTPAGE=450;ENDPAGE=461;TITLE=Proceedings of the 10th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining (PAKDD 2006)
PAKDD
Scopus-Elsevier
Proceedings of the 10th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining (PAKDD 2006), 450-461
STARTPAGE=450;ENDPAGE=461;TITLE=Proceedings of the 10th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining (PAKDD 2006)
Tree mining has recently attracted a lot of interest in areas such as Bioinformatics, XML mining, Web mining, etc. We are mainly concerned with mining frequent induced and embedded subtrees. While more interesting patterns can be obtained when mining
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::01d8db8421fe96125217dfcee5865209
http://eprints.eemcs.utwente.nl/secure2/9419/01/fulltext.pdf
http://eprints.eemcs.utwente.nl/secure2/9419/01/fulltext.pdf
Publikováno v:
Feature Selection for Data and Pattern Recognition ISBN: 9783662456194
Feature Selection for Data and Pattern Recognition
Feature Selection for Data and Pattern Recognition
Practical applications of association rule mining often suffer from overwhelming number of rules that are generated, many of which are not interesting or useful for the application in question. Removing irrelevant features and/or rules comprised of i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f7c515895c19b4b36050fde2d4269114
https://doi.org/10.1007/978-3-662-45620-0_10
https://doi.org/10.1007/978-3-662-45620-0_10
Credit risk assessment has been one of the most appealing topics in banking and finance studies, attracting both scholars’ and practitioners’ attention for some time. Following the success of the Grameen Bank, works on credit risk, in particular
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ceff279884b3c259e786f955394f4de4
https://doi.org/10.4018/978-1-4666-3886-0.ch025
https://doi.org/10.4018/978-1-4666-3886-0.ch025