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.
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Online Offline Retail E-Commerce. https://www.dealkyahai.com/online-retail-offline-ecommerce
Lackermair, G., Kailer, D., Kanmaz, K.: Importance of online product reviews from a consumer’s perspective. Adv. Econ. Bus. 1(1), 1–5 (2013)
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)
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)
Sohail, S.S., Siddiqui, J., Ali, R.: OWA based book recommendation technique. In: International Conference on Soft Computing and Software Engineering (2015)
Zeng, Z.: An ıntelligent e-commerce recommender system based on web mining. Int. J. Bus. Manag. 4–7, 10–14 (2009)
Li, F.T.: Community computation. In: MIT DSpace library
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)
Of Bayesian average and star ratings. http://fulmicoton.com/posts/bayesian_rating/
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)
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)
Senecal, S., Nantel, J.: The influence of online product recommendations on consumers’ online choices. J. Retail. 80, 159–169 (2004)
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)
Gruber, T.R.: A translation approach to portable ontology specifications. Knowl. Acquisition 5(2), 199–220 (1993)
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Kuriakose, B., Mathai, V., Baby, A., Jose, J. (2019). Enhanced Portable Customer Experience Using Community Computation in Offline Retail. In: Hemanth, J., Fernando, X., Lafata, P., Baig, Z. (eds) International Conference on Intelligent Data Communication Technologies and Internet of Things (ICICI) 2018. ICICI 2018. Lecture Notes on Data Engineering and Communications Technologies, vol 26. Springer, Cham. https://doi.org/10.1007/978-3-030-03146-6_2
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DOI: https://doi.org/10.1007/978-3-030-03146-6_2
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