|
|
E-commerce platform designed for continuous optimization and personalization
Dräxler, Peter ; Peška, Ladislav (advisor) ; Bernhauer, David (referee)
The ability of an e-commerce company to collect, synthesize, and utilize data can be vital to its survival. The degree to which a company has the ability to gather data about sources of conversion is proportional to their ability to allocate advertising / im- plementation budget effectively. Measurement and optimization of user flow on a website is equally important as it can deliver a measurable increase in user loyalty, revenue, and profits. Similarly, it can reveal that numerous improvements, while appearing effective on paper, may not perform as well in real-world scenarios. This thesis focuses on the construction of an e-commerce platform centered around data collection and analysis. We use the data to conduct continuous, real-time experi- ments on the platform using the contextual multi-armed bandits algorithm. We develop a recommendation system based on collaborative filtering and set up an experiment to evaluate it's real-world performance. The platform can be easily connected to a business intelligence dashboard to allow data exploration, to support its management in making informed tactical & strategic decisions. The platform is developed with Blazor, which is an emerging technology that en- ables usage on C# code in the browser with compilation to WebAssembly as opposed to JavaScript. We describe...
|
|
|
Recommender systems for the recipes domain
Starýchfojtů, Josef ; Peška, Ladislav (advisor) ; Bernhauer, David (referee)
Recommender systems are now part of our daily life more than ever. We use them through several platforms, like music or video players. As users of such systems, we don't need to actively seek for new content, but let it be comfortably recommended to us instead. One area not covered this way is domain of recipes. In order to cook a recipe, we have to search for some cookbook and find the recipe there, then go shopping for it and only then cook it. Usually there is not a perfect match between the recipe content and the content of our shopping basket, which makes the process even more unpleasant. Main goal of this work is to introduce such platform into this domain. Firstly to research the application of recommender systems in recipe domain, suggestion of several methods and their verification. Then also to introduce these algorithms in real product in form of mobile application, which will accompany the user when shopping and choosing a recipe. 1
|
guest ::
