nach oben

Knowledge and Information Systems

Erschienen in:

28.06.2018 | Regular Paper

Toward proactive social inclusion powered by machine learning

verfasst von: Emilio Serrano, Mari Carmen Suárez-Figueroa, Jacinto González-Pachón, Asunción Gómez-Pérez

Erschienen in: Knowledge and Information Systems | Ausgabe 3/2019

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config

KI-gestützte Suche

Aus

Abstract

The fight against social exclusion is at the heart of the Europe 2020 strategy: 120 million people are at risk of suffering this condition in the EU. Risk prediction models are widely used in insurance companies and health services. However, the use of these models to allow an early detection of social exclusion by social workers is not a common practice. This paper describes a data analysis of over 16 K cases with over 60 predictors from the Spanish region of Castilla y León. The use of machine learning paradigms such as logistic regression and random forest makes possible a high precision in predicting chronic social exclusion: around 90% in the most conservative predictions. This prediction models offer a quick rule of thumb that can detect citizens who are in danger of been excluded from the society beyond a temporary situation, allowing social workers to further study these cases.

Vorheriger Artikel Accuracy evaluation of methods and techniques in Web-based question answering systems: a survey

Nächster Artikel Mining and clustering service goals for RESTful service discovery

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

Jetzt informieren

In this vein, the adult dataset [11] is a well-known public labeled dataset that allows predicting whether an adult income exceeds $50 K a year based on a 1994 census database. It can be used to train prediction models as a proof of concept before collecting and labeling the own proprietary data.

https://sauss.jcyl.es/sauss-sso/.

Bootstrap Web site: https://getbootstrap.com/.

American Cancer Society: How Common Is Breast Cancer? (2018). https://goo.gl/5XWwsU (Last Medical Review: July of 2017. Last Revised: January of 2018. Accessed April of 2018)

Chapman P, Clinton J, Kerber R, Khabaza T, Reinartz T, Shearer C, Wirth R (2000) CRISP-DM 1.0 step-by-step data mining guide (tech. rep.). The CRISP-DM consortium. Retrieved from http://www.crisp-dm.org/CRISPWP-0800.pdf

Chawla NV, Bowyer KW, Hall LO, Kegelmeyer WP (2002) Smote: synthetic minority over-sampling technique. J Artif Int Res 16(1):321–357. Retrieved from http://dl.acm.org/citation.cfm?id=1622407.1622416

Degenhardt F, Seifert S, Szymczak S (2017) Evaluation of variable selection methods for random forests and omics data sets. Briefings in Bioinformatics, bbx124. Retrieved from https://doi.org/10.1093/bib/bbx124

Eckerson WW (1995) Three tier client/server architecture: achieving scalability, performance, and efficiency in client server applications. In: Open Information Systems 10

European Commission’s DG for Employment, Social Affairs & Inclusion (2018). http://ec.europa.eu/social/main.jsp?catId=751. Accessed April 2018

Fayyad UM, Piatetsky-Shapiro G, Smyth P (1996) Advances in knowledge discovery and data mining. In: Fayyad UM, Piatetsky-Shapiro G, Smyth P, Uthurusamy R (eds). American Association for Artificial Intelligence, Menlo Park, pp 1–34. Retrieved from http://dl.acm.org/citation.cfm?id=257938.257942

Hall MA (1999) Correlation-based feature selection for machine learning (Unpublished doctoral dissertation)

Haron N (2013) On social exclusion and income poverty in Israel: findings from the European social survey. In: Berenger V, Bresson F (eds) Poverty and social exclusion around the Mediterranean sea. Springer, Boston, pp 247–269. Retrieved from https://doi.org/10.1007/978-1-4614-5263-8_9

10.

Khalilia M, Chakraborty S, Popescu M (2011) Predicting disease risks from highly imbalanced data using random forest. BMC Med Inform Dec Mak 11(1):51. Retrieved from https://doi.org/10.1186/1472-6947-11-51

11.

Kohavi R, Becker B (1996) Adult data set. https://archive.ics.uci.edu/ml/datasets/Adult. Accessed April 2018

12.

Lafuente-Lechuga M, Faura-Martínez U (2013) Análisis de los individuos vulnerables a la exclusión social en españa en 2009. Anales de ASEPUMA(21)

13.

Lee J, Wu Y, Kim H (2015) Unbalanced data classification using support vector machines with active learning on scleroderma lung disease patterns. J Appl Stat 42(3):676–689. https://doi.org/10.1080/02664763.2014.978270 MathSciNetCrossRef

14.

Levitas R, Pantazis C, Fahmy E, Gordon D, Lloyd E, Patsios D (2007) The multi-dimensional analysis of social exclusion [Book]. Social Exclusion Task Force, Cabinet Office, London. Retrieved from http://www.cabinetoffice.gov.uk/social_exclusion_task force/publications/multidimensional.aspx

15.

Liaw A, Wiener M (2002) Classification and regression by randomforest. R News 2(3):18–22. Retrieved from http://CRAN.R-project.org/doc/Rnews/

16.

Lunardon N, Menardi G, Torelli N (2014) Rose: a package for binary imbalanced learning. R J 6(1):79–89

17.

Manulife Philippines. Calculate your risk, your partner’s risk or both (2018). http://www.insureright.ca/what-is-your-risk. Accessed April 2018

18.

Mayo Clinic. Heart Disease Risk Calculator (2018). http://www.mayoclinic.org/diseases-conditions/heart-disease/in-depth/heart-disease-risk/itt-20084942. Accessed April 2018

19.

Piatetsky G (2014) CRISP-DM, still the top methodology for analytics, data mining, or data science projects. https://goo.gl/zrikMB. Accessed April 2018

20.

Ramos J, Varela A (2016) Beyond the margins: analyzing social exclusion with a homeless client dataset. Soc Work Soc 14(2):104–120

21.

Rank MR, Hirschl TA (2016) Calculate your economic risk. New York times

22.

Ribeiro MT, Singh S, Guestrin C (2016) “why should I trust you?” Explaining the predictions of any classifier. CoRR, arXiv:1602.04938. Retrieved from

23.

Rogalewicz M, Sika R (2016) Methodologies of knowledge discovery from data and data mining methods in mechanical engineering. Manag Prod Eng Rev 7(4):97–108

24.

Serrano E, del Pozo-Jiménez P, Suàrez-Figueroa MC, Gonzàlez-Pachón J, Bajo J, Gómez-Pérez, A (2017) Predicting the risk of suffering chronic social exclusion with machine learning. In: Omatu S, Rodríguez S, Villarrubia G, Faria P, Sitek P, Prieto J (eds) Distributed computing and artificial intelligence, 14th international conference, DCAI 2017, Porto, Portugal, 21–23 June, 2017, vol 620, pp 132–139. Springer. Retrieved from https://doi.org/10.1007/978-3-319-62410-5_16

25.

Serrano E, Rovatsos M, Botía JA (2013) Data mining agent conversations: a qualitative approach to multiagent systems analysis. Inf Sci 230:132–146. https://doi.org/10.1016/j.ins.2012.12.019 MathSciNetCrossRef

26.

Serrano E, Such JM, Botía JA, García-Fornes A (2014) Strategies for avoiding preference profiling in agent-based e-commerce environments. Appl Intell 40(1):127–142. https://doi.org/10.1007/s10489-013-0448-2 CrossRef

27.

Shafique U, Qaiser H (2014) A comparative study of data mining process models (KDD, CRISP-DM and SEMMA). Int J Innov Sci Res 12(1):217–222. Retrieved from http://www.ijisr.issr-journals.org/abstract.php?article=IJISR-14-281-04

28.

Suh E, Tiffany Vizard P, Asghar Burchardt T (2013) Quality of life in Europe: social inequalities. 3rd European Quality of Life Survey

29.

Turner R (2016) A model explanation system. In: Palmieri FAN, Uncini A, Diamantaras KI, Larsen J (eds) 26th IEEE International Workshop on Machine Learning for Signal Processing (MLSP). IEEE, Vietri sul Mare, Salerno, Italy, pp 1–6

30.

Wan X, Liu J, Cheung WK, Tong T (2014) Learning to improve medical decision making from imbalanced data without a priori cost. BMC Med Inform Decis Mak 14:111. Retrieved from http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4261533/(111[PII]). DOIurlhttps://doi.org/10.1186/s12911-014-0111-9

31.

Witten IH, Frank E, Hall MA (2011) Data mining: practical machine learning tools and techniques. Morgan Kaufmann, Burlington

Titel: Toward proactive social inclusion powered by machine learning
verfasst von: Emilio Serrano
Mari Carmen Suárez-Figueroa
Jacinto González-Pachón
Asunción Gómez-Pérez
Publikationsdatum: 28.06.2018
Verlag: Springer London
Erschienen in: Knowledge and Information Systems / Ausgabe 3/2019
Print ISSN: 0219-1377
Elektronische ISSN: 0219-3116
DOI: https://doi.org/10.1007/s10115-018-1230-x

Springer Professional

Abstract

Bitte loggen Sie sich ein, um Zugang zu Ihrer Lizenz zu erhalten.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Wirtschaft"

Springer Professional "Technik"

Weitere Artikel der Ausgabe 3/2019

Ad hoc retrieval via entity linking and semantic similarity

Predicting hypernym–hyponym relations for Chinese taxonomy learning

Practical characterization of large networks using neighborhood information

A novel page clipping search engine based on page discussion topics

Accuracy evaluation of methods and techniques in Web-based question answering systems: a survey

Mining and clustering service goals for RESTful service discovery

Premium Partner