Multi-label classification algorithms based on supervised learning use all the labeled data to
train classifiers. However, in real life, many of the data are unlabeled, and it is costly to label …

The amount of biomedical literature is vast and growing quickly, and accurate text mining
techniques could help researchers to efficiently extract useful information from the literature …

Objectives Question answering (QA) systems have the potential to improve the quality of
clinical care by providing health professionals with the latest and most relevant evidence …

Exponential growth of electronic data requires advanced multi-label classification
approaches for the development of natural language processing (NLP) applications such as …

The field of text mining which deals with the providing of answers to the questions of the
users is also one of the hot topics for researchers. The difficulty seen in the proper …

Biomedical question answering (QA) represents a growing concern among industry and
academia due to the crucial impact of biomedical information. When mapping and ranking …

Effective software defect prediction (SDP) is important for software quality assurance.
Numerous advanced SDP methods have been proposed recently. However, how to …

Question Answering (QA) is a natural language processing task that aims at obtaining
relevant answers to user questions. While some progress has been made in this area …

Question reformulation allows the creation of different forms of the same question in order to
identify the best answer. However, when aspects such as length and complexity increase …

Classification of the topic of a question item is one of the fundamental problems in e-learning
systems. Unlike single-label classification, the multi-label classification method …