Advertisement

Enhanced Portable Customer Experience Using Community Computation in Offline Retail

  • Bineeth KuriakoseEmail author
  • Varghese Mathai
  • Arun Baby
  • Jeexson Jose
Conference paper
Part of the Lecture Notes on Data Engineering and Communications Technologies book series (LNDECT, volume 26)

Abstract

Seeking out customer reviews has become such standard part of the buying process for people these days that every retailer needs to be thinking about them. But often customer reviews are found extensively in online shopping sites such as Amazon, Flipkart etc. and social media sites such as Facebook, twitter etc. But when a product is purchased from a retailer offline, these reviews are usually unattended and mining for the exact review will be time-consuming. Also, in large super-markets, the customer interaction is not as much as in online shopping so as to provide with details such as related products, what products were also purchased by the product who purchased the particular product etc. All these drawbacks are erased with our proposal to enhance customer interactivity through a smartphone application. Our proposed system uses a unique concept of ‘community-computation’, a variation of distributed systems for processing. The results of the proposed system show that by implementing such a real time system, the shopping experience of a normal customer can be enhanced and also the same will pave way for next-generation shopping.

Keywords

Review Ratings Offline shopping Community computation Customer experience 

References

  1. 1.
  2. 2.
    Lackermair, G., Kailer, D., Kanmaz, K.: Importance of online product reviews from a consumer’s perspective. Adv. Econ. Bus. 1(1), 1–5 (2013)Google Scholar
  3. 3.
    Bin, D., Peiji, S., et al.: E-commerce reviews management system based on online customer reviews mining. In: International Conference on Innovative Computing and Communication (2010)Google Scholar
  4. 4.
    Aciar, S., Zhang, D., Simoff, S., Debenham, J.: Recommender system based on consumer product reviews. In: Proceedings of the IEEE/WIC/ACM International Conference on Web Intelligence (2006)Google Scholar
  5. 5.
    Sohail, S.S., Siddiqui, J., Ali, R.: OWA based book recommendation technique. In: International Conference on Soft Computing and Software Engineering (2015)Google Scholar
  6. 6.
    Zeng, Z.: An ıntelligent e-commerce recommender system based on web mining. Int. J. Bus. Manag. 4–7, 10–14 (2009)Google Scholar
  7. 7.
    Li, F.T.: Community computation. In: MIT DSpace libraryGoogle Scholar
  8. 8.
    Lowe, D.G.: Object recognition from local scale-invariant features. In: Proceedings of the International Conference on Computer Vision, vol. 2, pp. 1150–1157 (1999)Google Scholar
  9. 9.
  10. 10.
    Of Bayesian average and star ratings. http://fulmicoton.com/posts/bayesian_rating/
  11. 11.
    Guo, S., Wang, M., Leskovec, J.: The role of social networks in online shopping: information passing, price of trust, and consumer choice. In: Proceedings of the 12th ACM Conference on Electronic Commerce, pp. 157–166 (2011)Google Scholar
  12. 12.
    Popescu, A.-M., Etzioni, O.: Extracting product features and opinion from reviews. In: Proceedings of the Conference on Human Language Technology and Empirical Methods in Natural Language Processing, pp. 339–346 (2005)Google Scholar
  13. 13.
    Senecal, S., Nantel, J.: The influence of online product recommendations on consumers’ online choices. J. Retail. 80, 159–169 (2004)CrossRefGoogle Scholar
  14. 14.
    Wietsma, R., Ricci, F.: Product reviews in mobile decision aid systems. In: Workshop on Pervasive Mobile Interaction Devices, in conjunction with Pervasive 2005, Munich, Germany, 11 May 2005 (2005)Google Scholar
  15. 15.
    Gruber, T.R.: A translation approach to portable ontology specifications. Knowl. Acquisition 5(2), 199–220 (1993)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Bineeth Kuriakose
    • 1
    Email author
  • Varghese Mathai
    • 1
  • Arun Baby
    • 1
  • Jeexson Jose
    • 1
  1. 1.Department of Computer Science and EngineeringMuthoot Institute of Technology and ScienceErnakulamIndia

Personalised recommendations