Context-predicting models (more commonly known as embeddings or neural language models) are the new kids on the distributional semantics block. Despite the buzz surrounding these models, the literature is still lacking a systematic comparison of the predictive models with classic, count-vector-based distributional semantic approaches. In this paper, we perform such an extensive evaluation, on a...

Organizations often have to face a dynamic market environment. Processes must be frequently adapted in order to stay competitive and allow an efficient workflow. Data Science approaches are currently often used in analysis methods to identify influential indicators on processes and learn predictive models to estimate the duration of an activity. However, current methods do not or only partially...

Extant models of entry and location choices by competing retailers focus on the benefits of differentiation, derived from locating far apart, and therefore cannot explain high degrees of store agglomeration. Unlike extant models that treat firm profits in reduced form, this paper decomposes firm profit as a function of customer choice (to allow for consumer utility from agglomeration) and compe...

This paper presents a pilot study of using contextdependent segmental duration for continuous speech recognition in a domain-speci c application. Di erent modelling strategies are proposed for function words and content words. Stress level, word position in utterance and phone position in word are identi ed to be the 3 most crucial factors a ecting segmental duration in this particular applicat...

Automobile warranties and thus lifetimes are characterized in the two-dimensional space of time and mileage. This paper presents a non-homogenous Poisson Process (NHPP) predictive model for automobile warranty claims consisting of two components: a population size function and a failure or warranty claim rate. The population size function tracks the population in the time domain and accounts fo...

M supermarket firms choose to position themselves by offering either everyday low prices (EDLP) across several items or offering temporary price reductions (promotions) on a limited range of items. While this choice has been addressed from a theoretical perspective in both the marketing and economic literature, relatively little is known about how these decisions are made in practice, especiall...

We give a brief review of hysteresis in viscoelastic polymers. The efforts surveyed range from phenomenological to molecular modelling with applications involving recent efforts on elastomers to biotissue.

Presented in the paper is a C-space based computer automated process planning (CAPP) algorithm for freeform die-cavity machining, which is an extension of the hierarchical CAPP model proposed earlier by the authors. In order to demonstrate its validity, the proposed CAPP algorithm has been implemented and applied to actual die-cavity machining examples. q 2002 Elsevier Science Ltd. All rights r...

Summary: We initiated the Predictive Toxicology Challenge (PTC) to stimulate the development of advanced SAR techniques for predictive toxicology models. The goal of this challenge is to predict the rodent carcinogenicity of new compounds based on the experimental results of the US National Toxicology Program (NTP). Submissions will be evaluated on quantitative and qualitative scales to select ...