research-article

Concise Description of Telecom Service Use Through Concept Chains

Authors:

Sadok Ben Yahia,

Kristo RaunAuthors Info & Claims

MEDES '19: Proceedings of the 11th International Conference on Management of Digital EcoSystems

Pages 181 - 186

https://doi.org/10.1145/3297662.3365790

Published: 10 January 2020 Publication History

Abstract

Binary data arise naturally in many fields including shopping carts, pass-fail tests, social networks etc. Descriptive data mining aims to discover a concise set of general patterns in these possibly noisy data. An important tool for describing binary data is Formal Concept Analysis (FCA) which describes the data through formal concepts. As the full lattice of formal concepts can become large even when dealing with relatively modest amounts of data there are several methods to reduce the number of concepts used to describe the data: selecting a subset of "interesting" concepts, finding a subset of concepts that cover the data fully etc. In this paper we apply a novel method of concept chain coverage generation to service use data of a telecommunications company. Concept chain coverage aims to cover the data not with single concepts but with chains of related concepts. The aim is not the full coverage but high enough coverage through a concise set of concept chains. We show that a relatively modest set of concept chains (4 to 10) can describe most of the data and that the performance of the algorithm is very acceptable for this case study.

References

[1]

N. Belkhiter, C. Bourhfir, M. Gammoudi, A. Jaoua, N. I. Thanh, and M. Reguig. 1994. Décomposition Rectangulaire Optimale DâĂ&Zacute;une Relation Binaire: Application Aux Bases De Données Documentaires: INFOR: Information Systems and Operational Research: Vol 32, No 1. INFOR 1 (1994), 33--54. https://www.tandfon-line.com/doi/abs/10.1080/03155986.1994.11732236

[2]

Radim Belohlavek and Martin Trnecka. 2015. From-below approximations in Boolean matrix factorization: Geometry and new algorithm. J. Comput. System Sci. 81, 8 (Dec. 2015), 1678--1697. https://doi.org/10.1016/j.jcss.2015.06.002

Digital Library

[3]

Radim Belohlavek and Vilem Vychodil. 2010. Discovery of optimal factors in binary data via a novel method of matrix decomposition. J. Comput. System Sci. 76, 1 (Feb. 2010), 3--20. https://doi.org/10.1016/j.jcss.2009.05.002

Digital Library

[4]

B. A. Davey and H. A. Priestley. 2002. Introduction to lattices and order (2nd ed ed.). Cambridge University Press, Cambridge, UK; New York, NY.

[5]

R. P. Dilworth. 1950. A Decomposition Theorem for Partially Ordered Sets. Annals of Mathematics 51, 1 (1950), 161--166. https://doi.org/10.2307/1969503

[6]

Dheeru Dua and Casey Graff. 2017. UCI Machine Learning Repository. http://archive.ics.uci.edu/ml

[7]

Bernhard Ganter, Gerd Stumme, and Rudolf Wille. 2005. Formal Concept Analysis: Foundations and Applications. Springer. Google-Books-ID: oyb6BwAAQBAJ.

[8]

Cyril Goutte, Peter Toft, Egill Rostrup, Finn ÃE. Nielsen, and Lars Kai Hansen. 1999. On Clustering fMRI Time Series. NeuroImage 9, 3 (March 1999), 298--310. https://doi.org/10.1006/nimg.1998.0391

[9]

Rein Kuusik. 1989. Application of Theory of Monotone Systems for Decision Trees. Number 705. 72 in Transactions of Tallinn Technical University. Tallinna Tehnikaülikool, Tallinn.

[10]

Amira Mouakher and Sadok Ben Yahia. 2016. QualityCover: Efficient binary relation coverage guided by induced knowledge quality. Information Sciences 355--356 (Aug. 2016), 58--73. https://doi.org/10.1016/j.ins.2016.03.009

[11]

A. Mouakher and S. Ben Yahia. 2019. On the efficient stability computation for the selection of interesting formal concepts. Inf. Sci. 472 (2019), 15--34.

[12]

A. Mouakher, O. Ktayfi, and S. Ben Yahia. 2019. Scalable computation of the extensional and intensional stability of formal concepts. Int. J. General Systems 48, 1 (2019), 1--32.

[13]

Oystein Ore. 1943. Chains in partially ordered sets. In Bulletin of the American Mathematical Society 49 (8). https://doi.org/10.1090/S0002-9904-1943-07970-0

[14]

Ants Torim and Rein Kuusik. 2005. Describing Data Table with Best Decision. In Proceedings of the 5th WSEAS international conference on Simulation, modelling and optimization. 158--163.

Digital Library

[15]

Ants Torim, Marko Mets, and Kristo Raun. 2019. Covering Concept Lattices with Concept Chains. (2019).

[16]

Leo Võhandu, Rein Kuusik, Ants Torim, Eik Aab, and Grete Lind. 2006. Some algorithms for data table (re)ordering using Monotone Systems. (2006), 7.

[17]

Jaideep Vaidya, Vijayalakshmi Atluri, and Qi Guo. 2007. The role mining problem: finding a minimal descriptive set of roles. In Proceedings of the 12th ACM symposium on Access control models and technologies. ACM, 175--184.

Digital Library

[18]

Rudolf Wille. 2009. Restructuring Lattice Theory: an Approach Based on Hierarchies of Concepts. In Formal Concept Analysis (Lecture Notes in Computer Science), Sébastien Ferré and Sebastian Rudolph (Eds.). Springer Berlin Heidelberg, 314--339.

Cited By

Mouakher ARagobert AGerin SKo A(2021)Conceptual Coverage Driven by Essential Concepts: A Formal Concept Analysis ApproachMathematics10.3390/math92126949:21(2694)Online publication date: 23-Oct-2021
https://doi.org/10.3390/math9212694
Raun KTorim AYahia S(2021)GC and Other Methods for Full and Partial Context CoverageProcedia Computer Science10.1016/j.procs.2021.08.077192(746-755)Online publication date: 2021
https://doi.org/10.1016/j.procs.2021.08.077

Index Terms

Concise Description of Telecom Service Use Through Concept Chains
1. Applied computing
  1. Electronic commerce
    1. Online shopping
2. Computing methodologies
  1. Machine learning
    1. Learning paradigms
      1. Unsupervised learning
        Cluster analysis
        Topic modeling

Recommendations

Rough-set concept analysis

Based on ideas from formal concept analysis, this paper interprets the notions of RS-definable concepts (i.e., rough-set definable concepts) and the Boolean algebra of RS-definable concepts. We explicitly represent a RS-definable concept as a pair of an ...
Semantifying formal concept analysis using description logics
Abstract
Formal Concept Analysis (FCA) is a field of applied mathematics with its roots in order theory, in particular the theory of complete lattices. Over the past 20 years, FCA has been widely studied. Description Logics (DLs) are a family ...
Learning models based on formal concept
RSKT'07: Proceedings of the 2nd international conference on Rough sets and knowledge technology

From the classic view in which a concept consists of the set of extents and the set of intents, a concept learning system extended from a formal context is introduced and two concepts such as an under concept and an over concept are defined. Any pair of ...

Comments

Information & Contributors

Information

Published In

cover image ACM Other conferences

MEDES '19: Proceedings of the 11th International Conference on Management of Digital EcoSystems

November 2019

350 pages

ISBN:9781450362382

DOI:10.1145/3297662

General Chairs:
Richard Chbeir
University of Pau and Pays de l'Adour, France
,
Yannis Manolopoulos
Open University of Cyprus, Cyprus
,
Program Chairs:
Sergio Ilarri
University of Zaragoza, Spain
,
Apostolos Papadopoulos
Aristotle University of Thessaloniki, Greece

Copyright © 2019 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

In-Cooperation

SIGAPP: ACM Special Interest Group on Applied Computing

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 10 January 2020

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article
Research
Refereed limited

Conference

MEDES '19

MEDES '19: 11th International Conference on Management of Digital EcoSystems

November 12 - 14, 2019

Limassol, Cyprus

Acceptance Rates

MEDES '19 Paper Acceptance Rate 41 of 102 submissions, 40%;

Overall Acceptance Rate 267 of 682 submissions, 39%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

2
Total Citations
View Citations
36
Total Downloads

Downloads (Last 12 months)3
Downloads (Last 6 weeks)0

Reflects downloads up to 05 Mar 2025

Other Metrics

View Author Metrics

Citations

Cited By

Mouakher ARagobert AGerin SKo A(2021)Conceptual Coverage Driven by Essential Concepts: A Formal Concept Analysis ApproachMathematics10.3390/math92126949:21(2694)Online publication date: 23-Oct-2021
https://doi.org/10.3390/math9212694
Raun KTorim AYahia S(2021)GC and Other Methods for Full and Partial Context CoverageProcedia Computer Science10.1016/j.procs.2021.08.077192(746-755)Online publication date: 2021
https://doi.org/10.1016/j.procs.2021.08.077

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Figures

Tables

Media

View Table of Conten