Abstract: There is provided a method for predicting a port-stay duration of a vessel at a port. The method includes: determining a plurality of port-stay components of the port-stay duration; determining a regression sequence of the plurality of port-stay components, comprising modeling a first port-stay component and each of a plurality of second port-stay components, determining the regression sequence of the plurality of port-stay components based on a relative measure associated to each of the plurality of second port-stay components; modeling each of the plurality of port-stay components in sequence in accordance with the regression sequence determined to obtain a first plurality of sequentially modeled port-stay components; modeling a first port-stay duration based on the first plurality of sequentially modeled port-stay components to obtain a first port-stay duration model; and predicting the port-stay duration based on the first port-stay duration model.

Abstract: A system and a method for classifying text messages, such as social media messages into sentiment valence categories are provided. The system comprising a module for decomposing text messages, a module for cleaning text messages, a module for producing feature data of text messages, and a module for classifying text messages into sentiment valence categories. The module for decomposing text messages is configured to: receive a text message, parse the text message into separate portions in response to parsing criteria based on sentence delimiters, wherein the separate portions are sentences, phrases and words, and rejoin at least some of the separate portions of the text message into sentences in response to predefined linguistic conditions.