Incremental learning refers to learning from streaming data, which arrive over time, with
limited memory resources and, ideally, without sacrificing model accuracy. This setting fits …

Abstract Parts-of-Speech (POS) Tagging is one of the fundamental and pre-processing steps
for Natural Language Processing (NLP) tasks such as Text Summarization, Name Entity …

This book provides a perspective on the application of machine learning-based methods in
knowledge discovery from natural languages texts. By analysing various data sets …

We introduce the Differentiable Weightless Neural Network (DWN), a model based on
interconnected lookup tables. Training of DWNs is enabled by a novel Extended Finite …

In this paper, we propose a new approach to construct a system of transformation rules for
the Part-of-Speech (POS) tagging task. Our approach is based on an incremental …

Mining social web text has been at the heart of the Natural Language Processing and Data
Mining research community in the last 15 years. Though most of the reported work is on …

WiSARD belongs to the class of weightless neural networks, and it is based on a neural
model which uses lookup tables to store the function computed by each neuron rather than …

Weightless neural networks (WNNs) are an alternative pattern recognition technique where
RAM nodes function as neurons. As both training and inference require mostly table …

This paper covers a particular area of interest in pattern recognition and knowledge-based
systems (PRKbS), being intended for both young researchers and academic professionals …

We consider multilingual dialogue systems and ask how the performance of a dialogue
system can be improved by using information that is available in other languages than the …