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A Framework for Incremental Mining of Interesting Temporal Association Rules
2015
International Journal of Computer Applications
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Association rules are an important problem in data mining. ...
In this paper, an incremental association rules mining algorithm is proposed that integrates interestingness criterion during the process of building the model called SUMA. ...
, S.D., Kao, B.: A general Incremental Technique for Mining Discovered Association Rules, Proc. ...
doi:10.5120/ijca2015907433
fatcat:nv7rbchicnddrgz76hfwwq5rre
Text Mining: Extraction of Interesting Association Rule with Frequent Itemsets Mining for Korean Language from Unstructured Data
2015
International Journal of Multimedia and Ubiquitous Engineering
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A proposed Korean language mining method calculates and extracts meaningful patterns (association rules) between words and presents the hidden knowledge. ...
This paper presents the method for extraction information from unstructured text data and the importance of Association Rules Mining, specifically for of Korean language (text) and also, NLP (Natural Language ...
Our Korean language mining model has extracted some interesting association rules. ...
doi:10.14257/ijmue.2015.10.11.02
fatcat:xlt4ocad7bdbxohodqpfhoxqji
Association Rules Mining among Interests and Applications for Users on Social Networks
2019
IEEE Access
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According to our research, we found that there are a large number of association rules between human interests. These rules play a considerable role in our method of interest mining. ...
In this paper, we propose and verify two hypotheses about the interests of social network users. We then use association rules to mine users' interests from LinkedIn users' profiles. ...
a set of interest association rules for interest mining. ...
doi:10.1109/access.2019.2925819
fatcat:wptot77x4vbxpaznzvjxvofvea
Mining Interesting Least Association Rules in Manufacturing Industry: A Case Study in MODENAS
2015
International Journal of Control and Automation
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In this paper, we introduce an enhanced association rules mining method, called Significant Least Pattern Growth (SLP-Growth) and a new measurement named Critical Relative Support (CRS). ...
Least association rules are related to the rarity or uncommonness relationship among itemset in database repository. ...
Jefri Jasin from department of Information System Technology, MODENAS for providing the data in the journey of completing this work. ...
doi:10.14257/ijca.2015.8.12.05
fatcat:m4phatsax5fbzcjeln4r7z4nl4
Optimization of a language for data mining
2003
Proceedings of the 2003 ACM symposium on Applied computing - SAC '03
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Constraint-based mining has attracted in recent y ears the interest of the data mining research community because it increases the relevance of the result set, reduces its volume and the amount o f w orkload ...
This paper is a rst step towards the construction of optimizers for a constraint-based mining language. ...
interesting data patterns. ...
doi:10.1145/952532.952619
dblp:conf/sac/Meo03
fatcat:flsw2xp7uzbalhlhpvoouzvlgi
Optimization of a language for data mining
2003
Proceedings of the 2003 ACM symposium on Applied computing - SAC '03
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Constraint-based mining has attracted in recent y ears the interest of the data mining research community because it increases the relevance of the result set, reduces its volume and the amount o f w orkload ...
This paper is a rst step towards the construction of optimizers for a constraint-based mining language. ...
interesting data patterns. ...
doi:10.1145/952613.952619
fatcat:z7enhoz2cvggvjlfp5lqob3g7i
Alternative interest measures for mining associations in databases
2003
IEEE Transactions on Knowledge and Data Engineering
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Discovering associations between items in a large database is one such data mining activity. In finding associations, support is used as an indicator as to whether an association is interesting. ...
Data mining is defined as the process of discovering significant and potentially useful patterns in large volumes of data. ...
INTRODUCTION T HE past few years has seen a tremendous interest in the area of data mining. ...
doi:10.1109/tkde.2003.1161582
fatcat:xuaeq5htkzhrjjq6fk333pp4bm
RQL: A SQL-Like Query Language for Discovering Meaningful Rules
2014
2014 IEEE International Conference on Data Mining Workshop
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The Rule Query Language (RQL) is an SQL-like pattern mining language that extends and generalizes functional dependencies to new and unexpected rules. ...
It brings to the data analysts' desktop a convenient tool to discover logical implications between attributes of the database. ...
Demo contribution To improve pattern mining usability for data exploration, we introduce a Rule Query Language (RQL) that allows SQL-aware analysts to use pattern mining techniques with an interactive, ...
doi:10.1109/icdmw.2014.50
dblp:conf/icdm/ChardinCPP14
fatcat:44v4mneppferrowvuoidepwzim
A Data Mining view on Class Room Teaching Language
[article]
2011
arXiv
pre-print
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The main idea is to find out the support, confidence and interestingness level for appropriate language and attendance in the classroom. For this purpose association rule is used. ...
Where a teacher explains the material and students understand and learn the lesson. ...
Data mining involves many different tasks. So it is a complex process but it has a high degree of accuracy [9] . An association rule data mining model identifies specific types of data association. ...
arXiv:1104.4164v1
fatcat:hh2g5nj2fncxfhg4bfq7xlestq
A Practical Comparative Study Of Data Mining Query Languages
[chapter]
2010
Inductive Databases and Constraint-Based Data Mining
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We verify whether and how these languages can be used to perform four prototypical data mining tasks in the domain of itemset and association rule mining, and summarize their stronger and weaker points ...
Besides offering a comparative evaluation of different data mining query languages, this chapter also provides a motivation for the next chapter, where a deeper integration of data mining into databases ...
DMQL The language DMQL (Data Mining Query Language) [6, 7] is an SQL-like data mining query language designed for mining several kinds of rules in relational databases, such as classification and association ...
doi:10.1007/978-1-4419-7738-0_3
fatcat:wgtjh44tozevtdibrngfxkx2fi
Data Mining the Yeast Genome in a Lazy Functional Language
[chapter]
2002
Lecture Notes in Computer Science
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We present an application (PolyFARM) for distributed data mining in relational bioinformatics data, written in the lazy functional language Haskell. ...
PolyFARM is currently in use mining data from the Saccharomyces cerevisiae genome and is freely available for non-commercial use at ...
Association rule mining Association rule mining is a common data mining technique that can be used to produce interesting patterns or rules. ...
doi:10.1007/3-540-36388-2_4
fatcat:ial6m7vitzbclg7navuobrbsqy
A Data Mining Query Language for Knowledge Discovery in a Geographical Information System
[chapter]
2004
Lecture Notes in Computer Science
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Currently, SDMOQL supports two data mining tasks: inducing classification rules and discovering association rules. ...
Spatial data mining is a process used to discover interesting but not explicitly available, highly usable patterns embedded in both spatial and nonspatial data, which are possibly stored in a spatial database ...
Designing a comprehensive data mining language is a challenging problem because data mining covers a wide spectrum of tasks, from data classification to mining association rules. ...
doi:10.1007/978-3-540-44497-8_5
fatcat:jpnunp245bd6hnohehww2jnruq
A Survey of the State of the Art in Data Mining and Integration Query Languages
2011
2011 14th International Conference on Network-Based Information Systems
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The languages surveyed in this paper include: DMQL, MineSQL, MSQL, M2MQL, dmFSQL, OLEDB for DM, MINE RULE, and Oracle Data Mining. ...
The major aim of this survey is to identify the strengths and weaknesses of a representative set of Data-Mining and Integration (DMI) query languages. ...
This language supports association rule-mining. ...
doi:10.1109/nbis.2011.58
dblp:conf/nbis/PllanaJBW11
fatcat:gbry6kcfabglpieo2tmexbxiey
Mining Patterns with Domain Knowledge: A Case Study on Multi-language Data
2012
2012 IEEE/ACIS 11th International Conference on Computer and Information Science
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Multi-language data impairs the application of mining techniques in a generalized form, since language remains an impenetrable barrier. ...
This paper proposes a new method for mining patterns over multi-language data, through the use of the D 2 FP-Growth algorithm and a language constraint, both defined in the context of the referred framework ...
A. Pattern Mining and D 3 M Pattern mining is a subtask of mining association rules, first formulated in 1993 in the context of basket analysis [9] and further developed from then. ...
doi:10.1109/icis.2012.70
dblp:conf/ACISicis/AntunesB12
fatcat:yhnmalwdp5hmbb4neikxtvhd5i
Natural language processing in mining unstructured data from software repositories: a review
2019
Sadhana (Bangalore)
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More than 80 percent of the data present in them is unstructured. Mining data from these repositories helps project managers, developers and businesses, in getting interesting insights. ...
Most of the software artefacts present in these repositories are in the natural language form, which makes natural language processing (NLP) an important part of mining to get the useful results. ...
Review data is in natural language and thus, with NLP, mining becomes easier. ...
doi:10.1007/s12046-019-1223-9
fatcat:agssr4ggozendduyxjk3wc6lru
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