One key task of fine-grained sentiment analysis of product reviews is to extract product
aspects or features that users have expressed opinions on. This paper focuses on …

Lifelong Machine Learning, Second Edition is an introduction to an advanced machine
learning paradigm that continuously learns by accumulating past knowledge that it then …

Over the last two decades, determining the similarity between words as well as between
their meanings, that is, word senses, has been proven to be of vital importance in the field of …

Supervised machine learning techniques have already been widely studied and applied to
various real-world applications. However, most existing supervised algorithms work well …

Since coronavirus has shown up, inaccessibility of legitimate clinical resources is at its peak,
like the shortage of specialists and healthcare workers, lack of proper equipment and …

In this paper, we study cross-domain sentiment classification with neural network
architectures. We borrow the idea from Structural Correspondence Learning and use two …

In this paper, we develop a novel approach to aspect term extraction based on unsupervised
learning of distributed representations of words and dependency paths. The basic idea is to …

Abstract Representation learning with pivot-based methods and with Neural Networks (NNs)
have lead to significant progress in domain adaptation for Natural Language Processing …

Recent research efforts have shown that neural architectures can be effective in
conventional information extraction tasks such as named entity recognition, yielding state-of …

As a primary means of communication, texts are used to implicitly or explicitly reflect
emotions. Emotion or sentiment detection from text has emerged as an important and …