Consumer neuroscience is a growing field in both marketing and consumer behavior
research. The number of articles published on the topic has increased exponentially in the …

ABSTRACT Natural Language Processing (NLP) is now widely integrated into web and
mobile applications, enabling natural interactions between humans and computers …

Extractive summarization aims to automatically produce a short summary of a document by
concatenating several sentences taken exactly from the original material. Due to its …

With the increasing popularity of online social networks, more and more people are posting
information, updating their statuses, and searching for topics there. Massive cross-media big …

Automatic text summarization is an exertion of contriving the abridged form of a text
document covering salient knowledge. Numerous statistical, linguistic, rule-based, and …

Aspect extraction is one of the fundamental steps in analyzing the characteristics of
opinions, feelings and emotions expressed in textual data provided for a certain topic …

Most of existing text automatic summarization algorithms are targeted for multi-documents of
relatively short length, thus difficult to be applied immediately to novel documents of …

Construction accident investigation reports contain critical information, but extracting useful
insights from the voluminous Chinese text is challenging. Traditional methods rely on expert …

Traditional topic models are based on the bag-of-words assumption, which states that the
topic assignment of each word is independent of the others. However, this assumption …

In this study, we focus on understanding and mining user's preferences and intentions via
user-based aggregation in the context of a social network. Understanding preference and …