Abstract
The realization of an adaptation and personalization system entails a number of challenges, from developing appropriate user modeling mechanisms based on explicit and implicit user data collection methods, to implementing adaptation procedures and effects for personalizing the content, behavior and functionality during interaction with the system. In this context, this chapter presents the design of an extensible human-centred personalization framework, namely mapU (Multi-purpose Adaptation and Personalization for the User) for personalizing the visual and interaction design of Web-based interactive systems based on intrinsic human factors. It details its main modules and components, placing special emphasis on the formalization of the user modeling and adaptation procedures. Based on the formalization, we further discuss the design and development of a Web-based adaptive interactive system that makes use of the underlying principles of the framework as well as the respective technologies used for realizing it into a working system prototype. Main objective of this chapter is to serve as a guide of how a number of interdisciplinary elements, attributes and functionalities can co-exist under a unified framework, as well as how these can be implemented into a real-life adaptive interactive system, utilizing current state-of-the-art Web technologies.
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AdaptiveWeb (2007) An AdaptiveWeb system for integrating human factors in personalization of web content. Available online at http://adaptiveweb.cs.ucy.ac.cy. Accessed August 2015
Bandura A (1994) Self-efficacy. In: Ramachaudran VS (ed) Encyclopedia of human behaviour, vol 4. Academic, New York, pp 71–81
Belk M, Papatheocharous E, Germanakos P, Samaras G (2013) Modeling users on the world wide web based on cognitive factors, navigation behaviour and clustering techniques. J Syst Softw 86(12):2995–3012
Belk M, Germanakos P, Andreou P, Samaras G (2015) Towards a human-centered e-commerce personalization framework. In: Proceedings of the 2015 IEEE/WIC/ACM international conference on web intelligence (WI 2015). IEEE Computer Society Press (in press)
Blom J (2000) Personalization: a taxonomy. In: Proceedings of extended abstracts on human factors in computing systems (CHI’00), ACM Press, New York, 313–314
Brusilovsky P (1996) Methods and techniques of adaptive hypermedia. User Model User-Adap Inter 6(2–3):87–129
Brusilovsky P (2001) Adaptive hypermedia. User Model User-Adap Inter 11(1–2):87–110
Brusilovsky P, Maybury MT (2002) From adaptive hypermedia to the adaptive web. Commun ACM 45(5):30–33
Brusilovsky P, Millán E (2007) User models for adaptive hypermedia and adaptive educational systems. In: Brusilovsky P, Kobsa A, Nejdl W (eds) The adaptive web: methods and strategies of web personalization, LNCS 4321. Springer, Berlin/Heidelberg, pp 3–53
Cassady JC, Jonhson RE (2002) Cognitive test anxiety and academic performance. Contemp Educ Psychol 27(2):270–295
Cingil I, Dogac A, Azgin A (2000) A broader approach to personalization. Commun ACM 43(8):136–141
De Bra P, Aroyo L, Chepegin V (2004) The next big thing: adaptive web-based systems. J Digit Inf 5(1), Article 247
Demetriou A, Spanoudis G, Shayer M (2013) Developmental intelligence: from empirical to hidden constructs. Intelligence 41:744–749
Dieterich H, Malinowski U, Kühme T, Schneider-Hufschmidt M (1993) State of the art in adaptive user interfaces. In: Schneider-Hufschmidt M, Kühme T, Malinowski U (eds) Adaptive user interfaces: principles and practice. North-Holland, Amsterdam
Ekpaideion (2008) Adapting e-learning environments based on human factors. Available online at http://www3.cs.ucy.ac.cy/ekpaideion. Accessed August 2015
Frias-Martinez E, Magoulas GD, Chen SY, Macredie RD (2005) Modeling human behavior in user-adaptive systems: recent advances using soft computing technique. J Expert Syst Appl 29(2):320–329
Germanakos P, Tsianos N, Lekkas Z, Belk M, Mourlas C, Samaras G (2009) Proposing web design enhancements based on specific cognitive factors: an empirical evaluation. In: Conference on web intelligence. IEEE Computer Society, Washington, DC, pp 602–605
Germanakos P, Belk M, Constantinides A, Samaras G (2015) The PersonaWeb system: personalizing e-commerce environments based on human factors. Demonstration in extended proceedings of the international conference on user modeling, adaptation, and personalization (UMAP 2015), CEUR workshop proceedings 1388, Dublin, 29 Jun 29–3 Jul 2015
Goy A, Ardissono L, Petrone G (2007) Personalization in e-commerce applications. In: Brusilovsky P, Kobsa A, Nejdl W (eds) The adaptive web: methods and strategies of web personalization. LNCS 4321. Springer, Berlin/Heidelberg, pp 485–520
Halberstadt AG (2005) Emotional experience and expression: an issue overview. J Nonverbal Behav 17(3):139–143
Hauger D, Köck M (2007) State of the art of adaptivity in e-learning platforms. In: Proceedings of the 15th workshop on adaptivity and user modeling in interactive systems, Halle, pp 355–360
HighCharts (2015) Interactive JavaScript charts for web-pages. Available online at http://www.highcharts.com. Accessed July 2015
JQuery (2015) The write less, do more, JavaScript library. Available online at https://jquery.com. Accessed July 2015
Karat C, Blom JO, Karat J (2004) Designing personalized user experiences in eCommerce, LNCS. Springer, Dordrecht
Kozhevnikov M (2007) Cognitive styles in the context of modern psychology: toward an integrated framework of cognitive style. Psychol Bull 133(3):464–481
Mulvenna M, Anand S, Boechner A (2000) Personalization on the net using web mining: introduction. Commun ACM 43(8):122–125
Lekkas Z, Germanakos P, Tsianos N, Mourlas C, Samaras G (2013) Personality and emotion as determinants of the learning experience: how affective behavior interacts with various components of the learning process. In: Proceedings of the 15th international conference on human-computer interaction – HCI international 2013 (HCI 2013), Las Vegas, 21–26 Jul 2013, LNCS 8005. Springer, Berlin/Heidelberg, pp 418–427
Linden G, Smith B, York J (2003) Amazon.com recommendations: item-to-item collaborative filtering. IEEE Internet Comput 7(1):76–80
PAC (2015) Personalized authentication and CAPTCHA. Available online at http://pac.cs.ucy.ac.cy. Accessed August 2015
Paramythis A, Loidl-Reisinger S (2004) Adaptive learning environments and eLearning standards. Electron J e-Learn 2(1):181–194
Perkowitz M, Etzioni O (2000) Adaptive web sites. Commun ACM 43(8):152–158
PersonaWeb (2015) Personalizing generic web environments. Available online at http://personaweb.cs.ucy.ac.cy, http://adaptiveweb.cs.ucy.ac.cy/. Accessed August 2015
Rezaei AR, Katz L (2004) Evaluation of the reliability and validity of the cognitive styles analysis. Personal Individ Differ 26:1317–1327
Riding R (1991) Cognitive styles analysis. Learning and Training Technology, Birmingham
Riding R, Cheema I (1991) Cognitive styles – an overview and integration. J Educ Psychol 11(3–4):193–215
Salovey P, Mayer JD (1990) Emotional intelligence. Imagin Cogn Pers 9:185–211
Smartag (2012) Intelligent authoring of smart web objects for personalizing e-services. Available online at http://smartag.cs.ucy.ac.cy. Accessed August 2015
Spielberger CD (1983) Manual for the state-trait anxiety inventory (STAI). Consulting Psychologists Press, Palo Alto
Tsianos N, Germanakos P, Belk M, Lekkas Z, Samaras G, Mourlas C (2013) An individual differences approach in designing ontologies for efficient personalization. In: Anagnostopoulos I, Bielikova M, Mylonas P, Tsapatsoulis N (eds) Springer series studies in computational intelligence, edited volume Semantic hyper/multi-media adaptation: schemes and applications. Springer, Berlin/Heidelberg, pp 3–21
Wikipedia (2015) Available online at http://www.wikipedia.org. Accessed May 2015
WordPress (2015a) Free content management system. Available online at http://www.wordpress.org. Accessed July 2015
WordPress (2015b) Wordpress statistics. Available online at https://wordpress.com/activity. Accessed July 2015
Wu X, Kumar V, Quinlan J, Ghosh J, Yang Q, Motoda H, McLachlan G, Ng A, Liu B, Yu P, Zhou Z, Steinbach M, Hand D, Steinberg D (2007) Top 10 algorithms in data mining. Knowl Inf Syst 14(1):1–37
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Germanakos, P., Belk, M. (2016). A Generic Human-Centred Personalization Framework: The Case of mapU. In: Human-Centred Web Adaptation and Personalization. Human–Computer Interaction Series. Springer, Cham. https://doi.org/10.1007/978-3-319-28050-9_5
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DOI: https://doi.org/10.1007/978-3-319-28050-9_5
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