Applications of artificial intelligence in e-commerce and finance.

Summary Artificial Intelligence is present in every aspect of our lives in the era of Big Data. It has led to revolutionary changes in various sectors, including e-commerce and finance. In this thesis, we present four applications of AI that improve existing goods and services, enable automation, and dramatically increase the efficiency of many tasks in both fields. First, we improve the product search service offered by most e-commerce sites by using a novel term weighting system to better evaluate the importance of terms in a search query. Next, we build a predictive model on daily sales using a time series forecasting approach and leverage the predicted results to rank product search results to maximize a company's revenue. Next, we propose the difficulty of online product classification and analyze winning solutions, consisting of state-of-the-art classification algorithms, on our real-world dataset. Finally, we combine the skills previously learned from time series-based sales prediction and classification to predict one of the most challenging but attractive time series: inventory. We perform an in-depth study on each stock in the S&P 500 Index using four state-of-the-art classification algorithms and report very promising results.