Luigi’s Box: Personalized recommendations in e-commerce (industry PhD)
Our collaboration with Luigi’s Box in this project addresses the various research challenges of recommender systems in the e-commerce domain, focusing primarily on the web search. We explore novel methods of machine learning and artificial intelligence to improve customer experience across the variety of e-commerce stores.
Personalization proves to be a must for successful and modern e-commerce. Based on the deep data analysis, actual user needs, intent and context can be understood and considered to provide a seamless experience for the customers across various platforms.
Luigi’s Box provides complex product discovery tools that help clients analyze the efficiency of their search, including products such as Search with autocomplete, Recommender, or Product Listing. By utilizing artificial intelligence, these products represent state-of-the-art for the market.
In this project, we will employ the intrasession information and signals provided by users, to generate relevant, diverse, and responsible recommendations, improving the user experience and satisfaction.
The first step to achieve such a goal is to understand the user’s actual context and intent. For this purpose, we will use artificial intelligence methods to extract and in the next step to model the user behavior.
The researched topics we explore in this project are an optimal combination of actual research interest and industry demand, as the results will impact not only the further research but also many users in their everyday life.
The product is never finished. Investing in research and development is essential to becoming and remaining a leader in our industry. We look forward to working with KInIT and blazing new trails in the area of product discovery.
Gejza Nagy, Co-Founder & CEO
Lead and Researcher