Skip to main content
SpringerLink
Log in

An ontology-driven context-aware recommender system for indoor shopping based on cellular automata

  • Original Research
  • Published:
Journal of Ambient Intelligence and Humanized Computing Aims and scope Submit manuscript

Abstract

Nowadays, large shopping malls provide tools to help and boost customers to buy products. Some of these tools melt down digital operations with physical ones executed by customers into blended commerce experiences. On the other hand, Ambient Intelligence (AmI) represents a paradigm focused on equipping physical environments to define ergonomic spaces for people interacting with computer-based localized services which are ubiquitously accessible. In this context, we propose a Context-Aware Recommender System to assist indoor shopping by localizing shoppers and provide them with suggestions on where to find suitable offerings related to products that meet their wishlists. Recommendations are generated by means of an Indoor Navigation System. The system lies on two well-known formal models: the Computational Ontologies and the Cellular Automata. Ontologies are based on Description Logic and defined by means of languages, methodologies and tools of the Semantic Web Stack provided by W3C. Cellular Automata is a very well known formal computational model, suitable to abstract services deployed into an AmI-based environment along with the paradigm of Pervasive Computing. The integration of the capabilities provided by such two models offers a set of desirable features like adaptivity, scalability, low-costs, and robustness.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10

Similar content being viewed by others

Notes

  1. http://www.w3.org/standards/semanticweb/.

  2. http://www.w3.org/TR/owl2-overview/.

  3. http://protege.stanford.edu.

  4. https://schema.org.

  5. http://www.foaf-project.org.

  6. https://www.raspberrypi.org.

  7. https://jena.apache.org.

  8. http://virtuoso.openlinksw.com.

  9. http://iioengine.com/.

References

  • Adomavicius G, Tuzhilin A (2011) Context-aware recommender systems. In: Recommender systems handbook, Springer, pp 217–253

  • Atzori L, Iera A, Morabito G (2010) The internet of things: a survey. Comput Netw 54(15):2787–2805

    Article  MATH  Google Scholar 

  • Bandini S (2002) Cellular automata. Future Gener Comp Syst. doi:10.1016/S0167-739X(02)00067-5

  • Bellavista P, Kupper A, Helal S (2008) Location-based services: back to the future. Pervasive Comput IEEE 7(2):85–89

    Article  Google Scholar 

  • Bellavista P, Corradi A, Fanelli M, Foschini L (2012) A survey of context data distribution for mobile ubiquitous systems. ACM Comput Surv CSUR 44(4):24

    Google Scholar 

  • Colombo-Mendoza LO, Alor-Hernández G, Rodríguez-González A, Valencia-García R (2014) Mobicloup!: a paas for cloud services-based mobile applications. Autom Softw Eng 21(3):391–437

    Article  Google Scholar 

  • Compton M, Barnaghi P, Bermudez L, GarcíA-Castro R, Corcho O, Cox S, Graybeal J, Hauswirth M, Henson C, Herzog A et al (2012) The SSN ontology of the w3c semantic sensor network incubator group. Web Semant Sci Serv Agents World Wide Web 17:25–32

    Article  Google Scholar 

  • Conti M, Das SK, Bisdikian C, Kumar M, Ni LM, Passarella A, Roussos G, Tröster G, Tsudik G, Zambonelli F (2012) Looking ahead in pervasive computing: challenges and opportunities in the era of cyber-physical convergence. Pervasive Mob Comput 8(1):2–21

    Article  Google Scholar 

  • Cui B, Jin H, Liu Z, Deng J (2015) Improved collaborative filtering with intensity-based contraction. J Ambient Intell Humaniz Comput 6(5):661–674. doi:10.1007/s12652-015-0284-9

    Article  Google Scholar 

  • D’Aniello G, Gaeta M, Loia V, Orciuoli F (2015) An ami-based software architecture enabling evolutionary computation in blended commerce: the shopping plan application. Mob Inf Syst 2015:1–19, Article ID 936125. doi:10.1155/2015/936125

  • D’Aniello G, Gaeta A, Gaeta M, Lepore M, Orciuoli F, Troisi O (2016) A new DSS based on situation awareness for smart commerce environments. J Ambient Intell Human Comput 7(1):47–61. doi:10.1007/s12652-015-0300-0

    Article  Google Scholar 

  • De Maio C, Fenza G, Furno D, Loia V (2012a) Swarm-based semantic fuzzy reasoning for situation awareness computing. In: Fuzzy Systems (FUZZ-IEEE), 2012 IEEE International Conference IEEE, pp 1–7

  • De Maio C, Fenza G, Furno D, Loia V, Senatore S (2012b) OWL-FC: an upper ontology for semantic modeling of fuzzy control. Soft Comput 16(7):1153–1164

    Article  Google Scholar 

  • Decuir J (2014) Introducing bluetooth smart: Part ii: applications and updates. Consum Electron Mag IEEE 3(2):25–29. doi:10.1109/MCE.2013.2297617

    Article  Google Scholar 

  • Endsley MR (1995) Toward a theory of situation awareness in dynamic systems. Human Factors J Human Factors Ergon Soc 37(1):32–64

    Article  Google Scholar 

  • Fallah N, Apostolopoulos I, Bekris K, Folmer E (2013) Indoor human navigation systems: a survey. Interact Comput 25(1):21–33

    Google Scholar 

  • Fenza G, Furno D, Loia V, Veniero M (2010) Agent-based cognitive approach to airport security situation awareness. In: Complex, Intelligent and Software Intensive Systems (CISIS), 2010 International Conference IEEE, pp 1057–1062

  • Fenza G, Fischetti E, Fumo D, Loia V (2011) A hybrid context aware system for tourist guidance based on collaborative filtering. In: Fuzzy Systems (FUZZ), 2011 IEEE International Conference IEEE, pp 131–138

  • Fenza G, Furno D, Loia V (2012) Hybrid approach for context-aware service discovery in healthcare domain. J Comput Syst Sci 78(4):1232–1247

    Article  MathSciNet  Google Scholar 

  • Fuchs B, Ritz T, Halbach B, Hartl F (2011) Blended shopping: Interactivity and individualization. In: e-Business (ICE-B), 2011 Proceedings of the International Conference, pp 1–6

  • Furey E, Curran K, Kevitt PM (2013) Probabilistic indoor human movement modeling to aid first responders. J Ambient Intell Human Comput 4(5):559–569. doi:10.1007/s12652-012-0112-4

    Article  Google Scholar 

  • Gangemi A (2009) DOLCE+ DnS ultralite. RDF + OWL ontology. http://www.ontologydesignpatterns.org/ont/dul/DUL.owl

  • Gruber TR (1995) Toward principles for the design of ontologies used for knowledge sharing? Int J Human Comput Stud 43(5):907–928

    Article  Google Scholar 

  • Gruska J, La Torre S, Parente M (2004) Optimal time and communication solutions of firing squad synchronization problems on square arrays, toruses and rings. In: Developments in language theory, (DLT), Lecture Notes in Computer Science, vol 3340, Springer, pp 200–211

  • Gruska J, La Torre S, Parente M (2007) The firing squad synchronization problem on squares, toruses and rings. Int J Found Comput Sci 18(3):637–654

    Article  MathSciNet  MATH  Google Scholar 

  • Gu Y, Lo A, Niemegeers I (2009) A survey of indoor positioning systems for wireless personal networks. Commun Surv Tutor IEEE 11(1):13–32

    Article  Google Scholar 

  • Henricksen K, Indulska J (2006) Developing context-aware pervasive computing applications: models and approach. Pervasive Mob Comput 2(1):37–64

    Article  Google Scholar 

  • Hepp M (2008) Goodrelations: an ontology for describing products and services offers on the web. In: Knowledge engineering: practice and patterns, Springer, pp 329–346

  • Horridge M, Drummond N, Goodwin J, Rector AL, Stevens R, Wang H (2006) The manchester owl syntax. In: OWL ed, vol 216

  • Krötzsch M, Simancik F, Horrocks I (2014) Description logics. IEEE Intell Syst 29(1):12–19

    Article  MATH  Google Scholar 

  • La Torre S, Napoli M, Parente D (1998) Synchronization of a line of identical processors at a given time. Fundam Inf 34(1–2):103–128. doi:10.3233/FI-1998-341204

    MathSciNet  MATH  Google Scholar 

  • La Torre S, Napoli M, Parente M (2000) A compositional approach to synchronize two dimensional networks of processors. ITA 34(6):549–564. doi:10.1051/ita:2000130

    MathSciNet  MATH  Google Scholar 

  • Lin Z (2013) Indoor location-based recommender system. PhD thesis, University of Toronto

  • Moore EF (1962) The firing squad synchronization problem. Sequ Mach, pp 213–214

  • Olugbara OO, Ojo SO, Mphahlele M (2010) Exploiting image content in location-based shopping recommender systems for mobile users. Int J Inf Technol Decis Mak 9(05):759–778

    Article  MATH  Google Scholar 

  • Orciuoli F, Parente M, Vitiello A (2015) Solving the shopping plan problem through bio-inspired approaches. Soft Comput, pp 1–13

  • Purohit A, Sun Z, Pan S, Zhang P (2013) Sugartrail: indoor navigation in retail environments without surveys and maps. In: Sensor, mesh and ad hoc communications and networks (SECON), 2013 10th Annual IEEE Communications Society Conference IEEE, pp 300–308

  • Resnick P, Varian HR (1997) Recommender systems. Commun ACM 40(3):56–58

    Article  Google Scholar 

  • Rosenberg AL (2008) Cellular antomata: food-finding and maze-threading. In: Parallel Process. ICPP’08. 37th International Conference IEEE, pp 528–535

  • Rosenberg AL (2012) Cellular antomata. Adv Complex Syst 15(06):28

    Article  MathSciNet  Google Scholar 

  • Sadri F (2011) Ambient intelligence: a survey. ACM Comput Surv CSUR 43(4):36

    Google Scholar 

  • Schafer JB, Konstan J, Riedl J (1999) Recommender systems in e-commerce. In: Proceedings of the 1st ACM conference on electronic commerce, ACM, pp 158–166

  • Shearer R, Motik B, Horrocks I (2008) Hermit: a highly-efficient owl reasoner. In: OWLED, vol 432, p 91

  • TalebiFard P, Leung VCM (2014) Context-aware dissemination of information and services in heterogeneous network environments. J Ambient Intell Humaniz Comput 5(6):775–787. doi:10.1007/s12652-013-0210-y

    Article  Google Scholar 

  • Tapia DI, Abraham A, Corchado JM, Alonso RS (2010) Agents and ambient intelligence: case studies. Journal of Ambient Intell Humaniz Comput 1(2):85–93. doi:10.1007/s12652-009-0006-2

    Article  Google Scholar 

  • Umeo H, Kubo K (2010) A seven-state time-optimum square synchronizer. In: Bandini S, Manzoni S, Umeo H, Vizzari G (eds) Cellular automata. Lecture notes in computer science, vol 6350. Springer, Berlin, pp 219–230

    Google Scholar 

  • Winkler C, Broscheit M, Rukzio E (2011) Navibeam: indoor assistance and navigation for shop-ping malls through projector phones. In: CHI 2011 Workshop on Mobile and Personal Projection

  • Yang WS, Cheng HC, Dia JB (2008) A location-aware recommender system for mobile shopping environments. Expert Syst Appl 34(1):437–445

    Article  Google Scholar 

Download references

Acknowledgments

The authors thanks students and research assistants of GandALF Lab (Università di Salerno) for supporting early experimentation activities of the system.

Author information

Authors and Affiliations

  1. DISA-MIS–Dipartimento di Scienze Aziendali Management & Innovation Systems, Università di Salerno, Via Giovanni Paolo II, 132, 84084, Fisciano, SA, Italy

    Francesco Orciuoli

  2. DIEM–Dipartimento di Ingegneria dell’Informazione, Ingegneria Elettrica e,Matematica Applicata, Università di Salerno, Via Giovanni Paolo II, 132, 84084, Fisciano, SA, Italy

    Mimmo Parente

Authors
  1. Francesco Orciuoli
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Mimmo Parente
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Francesco Orciuoli.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Orciuoli, F., Parente, M. An ontology-driven context-aware recommender system for indoor shopping based on cellular automata. J Ambient Intell Human Comput 8, 937–955 (2017). https://doi.org/10.1007/s12652-016-0411-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12652-016-0411-2

Keywords

Search

Navigation