Constructing & Evaluating Context-Aware Recommender System in a case study with webshop carts and AB-testing

Examensarbete för masterexamen

Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.12380/212556
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Type: Examensarbete för masterexamen
Master Thesis
Title: Constructing & Evaluating Context-Aware Recommender System in a case study with webshop carts and AB-testing
Authors: Lundgren, Alexander
Lindberg, Linus
Abstract: A potential customer spends around five minutes on a webshop and visits roughly ten pages. To maximise sales it is crucial that the most relevant products is presented within those limits. The solution is to use a recommender system that predicts and recommends items on a personal level to the customer using collaborative filtering. Therefore, the project aim was to construct a working prototype for 3Bits and Lindex with an AB-testing phase to validate performance. Such evaluation of the collaborative filtering paradigm is not very common and as it only focus on on-going carts with binary implicit feedback, it does not take other information sources into account. To thoroughly evaluate the performance in this particular configuration five testphases was used: experimental prototype cross-validation tests, prototype testing using historical data sets, prototype testing using contextual pre-filtering, prototype crossvalidation of synthetic generated data and finally AB-testing. A lot of literature and data was studied in order to be able to construct the evaluation tests. Furthermore, to enable AB-testing 3Bits had to integrate the prototype into Lindex web page in a way that maintained the professional level. The evaluation shows a high accuracy compared to recommendations based on the most frequent occurring items. Furthermore, results from AB-tests of the projectalgorithm against the old recommendation services at Lindex showed contradicting results. Additionally, the evaluation also showed that incorporating contextual pre-filtering to the prototype did not increase performance.
Keywords: Data- och informationsvetenskap;Informations- och kommunikationsteknik;Computer and Information Science;Information & Communication Technology
Issue Date: 2014
Publisher: Chalmers tekniska högskola / Institutionen för data- och informationsteknik, Datavetenskap (Chalmers)
Chalmers University of Technology / Department of Computer Science and Engineering, Computing Science (Chalmers)
URI: https://hdl.handle.net/20.500.12380/212556
Collection:Examensarbeten för masterexamen // Master Theses



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