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On interestingness measures of formal concepts [article]

Sergei O. Kuznetsov, Tatiana Makhalova
2017 arXiv   pre-print
In this paper interestingness measures of concepts are considered and compared with respect to various aspects, such as efficiency of computation and applicability to noisy data and performing ranking  ...  Formal concepts and closed itemsets proved to be of big importance for knowledge discovery, both as a tool for concise representation of association rules and a tool for clustering and constructing domain  ...  .: Concept interestingness measures: a compar- ative study. In: Proceedings of the Twelfth International Conference on Concept Lattices and Their Applications. pp. 59–72 (2015) 33.  ... 
arXiv:1611.02646v2 fatcat:hseqpw6tibg2bplsarfpjheiuu

On interestingness measures of formal concepts

S.O. Kuznetsov, T. Makhalova
2018 Information Sciences  
In this paper, we consider several methods for pruning concept lattices and discuss results of their comparative study. c paper author(s), 2015.  ...  Concept lattices arising from noisy or high dimensional data have huge amount of formal concepts, which complicates the analysis of concepts and dependencies in data.  ...  interestingness measures: a comparative study  ... 
doi:10.1016/j.ins.2018.02.032 fatcat:qrk4jw2oznfbldtgi2aayz7fxa

Correlation-based interestingness measure for video semantic concept detection

Lin Lin, Mei-Ling Shyu, Shu-Ching Chen
2009 2009 IEEE International Conference on Information Reuse & Integration  
In this paper, a new correlation-based interestingness measure that is used at both stages is proposed.  ...  The association rules are generated by a novel interestingness measure obtained from applying multiple correspondence analysis (MCA) to explore the correlation between two feature-value pairs and concept  ...  In this paper, a novel video semantic concept detection framework facilitated with a correlation-based interestingness measure for association rule generation and selection is proposed.  ... 
doi:10.1109/iri.2009.5211537 dblp:conf/iri/LinSC09 fatcat:5gt5iju66vb3zp7anmhon4uycu

Detecting Local Community Structures in Social Networks Using Concept Interestingness [article]

Mohamed-Hamza Ibrahim, Rokia Missaoui, Abir Messaoudi
2019 arXiv   pre-print
In this paper, we introduce a novel strategy called (COIN), which exploits COncept INterestingness measures to detect communities based on the concept lattice construction of the network.  ...  One key challenge in Social Network Analysis is to design an efficient and accurate community detection procedure as a means to discover intrinsic structures and extract relevant information.  ...  Concept interestingness Interestingness (quality) measures of a formal concept c = (A, B) are commonly used to assess its relevancy.  ... 
arXiv:1902.03109v1 fatcat:3aqv5d6llferxgcxd3vixnj6de

Automatic Melody Harmonization with Triad Chords: A Comparative Study [article]

Yin-Cheng Yeh, Wen-Yi Hsiao, Satoru Fukayama, Tetsuro Kitahara, Benjamin Genchel, Hao-Min Liu, Hao-Wen Dong, Yian Chen, Terence Leong, Yi-Hsuan Yang
2021 arXiv   pre-print
In this paper, we present a comparative study evaluating and comparing the performance of a set of canonical approaches to this task, including a template matching based model, a hidden Markov based model  ...  We report the result of an objective evaluation using six different metrics and a subjective study with 202 participants.  ...  We then present a comparative study comparing the performance of these models.  ... 
arXiv:2001.02360v3 fatcat:7pnp7smx6jbc5gmnrmdgnvor5u

Query Languages Supporting Descriptive Rule Mining: A Comparative Study [chapter]

Marco Botta, Jean-François Boulicaut, Cyrille Masson, Rosa Meo
2004 Lecture Notes in Computer Science  
description in a standard language of statistical and data mining models.  ...  With an IDB, the user/analyst performs a set of very different operations on data using a query language, powerful enough to support all the required manipulations, such as data preprocessing, pattern  ...  classes), generalized relations (obtained by generalizing a set of data corresponding to low level concepts with data corresponding to higher level concepts according to a specified concept hierarchy).  ... 
doi:10.1007/978-3-540-44497-8_2 fatcat:37yowihfhnauzo3vjzvs7uhxrq

Mining Education Data to Predict Student's Retention: A comparative Study [article]

Surjeet Kumar Yadav, Brijesh Bharadwaj, Saurabh Pal
2012 arXiv   pre-print
This paper presents a data mining project to generate predictive models for student retention management.  ...  One way to achieve highest level of quality in higher education system is by discovering knowledge for prediction regarding enrolment of students in a course.  ...  Khan [11] conducted a performance study on 400 students with a main objective to establish the prognostic value of different measures of cognition, personality and demographic variables for success at  ... 
arXiv:1203.2987v1 fatcat:pqccdikxbjcfnc4l6j2ad3o7lu

Information-theoretic Interestingness Measures for Cross-Ontology Data Mining [article]

Prashanti Manda, Fiona McCarthy, Bindu Nanduri, Hui Wang, Susan M. Bridges
2016 arXiv   pre-print
We apply our data mining algorithm and interestingness measures to datasets from the Gene Expression Database at the Mouse Genome Informatics as a preliminary proof of concept to mine relationships between  ...  In this study, we present a data mining method that uses ontology-guided generalization to discover relationships across ontologies along with a new interestingness metric based on information theory.  ...  Integrated Rule Information Content Integrated Rule Information Content (IRIC) is a novel interestingness measure that combines information content (N _IC) of concepts in a rule with the shared information  ... 
arXiv:1504.08027v2 fatcat:ppys6mbnbbbalnbysd2u4wwsqq

A Robustness Measure of Association Rules [chapter]

Yannick Le Bras, Patrick Meyer, Philippe Lenca, Stéphane Lallich
2010 Lecture Notes in Computer Science  
It is a central concept in the evaluation of the rules and has only been studied unsatisfactorily up to now.  ...  We propose a formal definition of the robustness of association rules for interestingness measures.  ...  We then compare this concept to that of statistical significance in Section 4 and conclude in Section 5.  ... 
doi:10.1007/978-3-642-15883-4_15 fatcat:sgc5opmxrnc6jd7icmlu5lxogm

Interestingness Measures for Multi-Level Association Rules [chapter]

Gavin Shaw, Yue Xu, Shlomo Geva
2013 Studies in Computational Intelligence  
There has also been a focusing on the quality of rules from single level datasets with many interestingness measures proposed.  ...  However, with multi-level datasets now being common there is a lack of interestingness measures developed for multi-level and cross-level rules.  ...  Diversity is a measure that compares items within a rule and peculiarity compares items in two rules to see how different they are.  ... 
doi:10.1007/978-3-319-01866-9_2 fatcat:mbobcu5bcnb2plcwrcdepopxqi


Kavita Mittal
2017 International Journal of Advanced Research in Computer Science  
The goal of this paper is to survey and understand different ARM and AC techniques and comparing their performance.  ...  In the literature a variety of AC algorithms have be proposed such as CBA, CMAR, MCAR, CPAR etc each adopting some or the other approach for rule learning in the initial stages.  ...  The study also presents the distribution of the rule clusters with pattern XiY over different interestingness measures.  ... 
doi:10.26483/ijarcs.v8i9.4984 fatcat:dcywgghzvbao7l4azddk47gi4e

Interestingness Measures for Fuzzy Association Rules [chapter]

Attila Gyenesei, Jukka Teuhola
2001 Lecture Notes in Computer Science  
In this paper we study interestingness measures for generalized quantitative association rules, where the attribute domains can be fuzzy.  ...  Our suggestion is that the information-theoretic measures are a good choice when estimating the interestingness of rules, both for fuzzy and non-fuzzy domains.  ...  We compared the fuzzy version of confidence to six other measures, three of which were statistical, and the rest three were information-theoretic, based on the entropy concept.  ... 
doi:10.1007/3-540-44794-6_13 fatcat:ixwnublh5nfajni4anc4zabdri

Probabilistic Measures for Interestingness of Deviations - A Survey

Adnan Masood, Sofiane Ouaguenouni
2013 International Journal of Artificial Intelligence & Applications  
However, study of literature suggests that interestingness is difficult to define quantitatively and can be best summarized as, a record or pattern is interesting if it suggests a change in an established  ...  Matheus, in their paper, "The Interestingness of Deviations," argued that deviations should be grouped together in a finding and that the interestingness of a finding is the estimated benefit from a possible  ...  INTRODUCTION The concepts of interestingness and outliers are arduous to define and quantify.  ... 
doi:10.5121/ijaia.2013.4201 fatcat:3bwuzx3egbc7xk62g3zosizrcu

An Interpretable Music Similarity Measure Based on Path Interestingness [article]

Giovanni Gabbolini, Derek Bridge
2021 arXiv   pre-print
We introduce a novel and interpretable path-based music similarity measure.  ...  We compare the accuracy of our similarity measure with other competitive path-based similarity baselines in two experimental settings and with four datasets.  ...  In a comparative study, Piao et al. show that LDSD largely outperforms Shakti in accuracy [14] . The similarity measure that we propose in this paper is also path-based.  ... 
arXiv:2108.01632v2 fatcat:k2kdfiugrzc6ngejkgvi5f47dy

Interestingness measures for data mining

Liqiang Geng, Howard J. Hamilton
2006 ACM Computing Surveys  
This survey reviews the interestingness measures for rules and summaries, classifies them from several perspectives, compares their properties, identifies their roles in the data mining process, gives  ...  Interestingness measures play an important role in data mining, regardless of the kind of patterns being mined.  ...  Two recent studies have compared the ranking of rules by human experts to the ranking of rules by various interestingness measures, and suggested choosing the measure that produces the ranking which most  ... 
doi:10.1145/1132960.1132963 fatcat:pkb33tqvlnh53kr2rbdgumr52i
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