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Modeling how marketing actions in various channels influence or cause consumer purchase decisions is crucial for marketing decision-making. Marketing campaigns stimulate consumer awareness, interest and help drive interactions such as the browsing of product web pages, ultimately impacting an individual's purchase decision. In addition, some successful(More)
Fitting distributions of travel-time in vehicle traffic is an important application of spatio-temporal data mining. While regression methods to forecast the expected travel-time are standard approaches of travel-time prediction, we need to estimate distributions of the travel-time when using state-of-the-art risk-sensitive route recommendation systems. The(More)
Robustly estimating the state-transition probabilities of high-order Markov processes is an essential task in many applications such as natural language modeling or protein sequence modeling. We propose a novel estimation algorithm called Hierarchical Separated Dirichlet Smoothing (HSDS), where Dirichlet distributions are hierarchically assumed to be the(More)
Modeling of a product or service's attractiveness as a function of its own attributes (e.g., price and quality) is one of the foundations in econometric forecasts, which have been provided with an assumption that each human rationally has a consistent preference order among his choice decisions. Yet the preference orders by real humans become irrationally(More)
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