The assessment of examination questions is crucial in educational institutes since
examination is one of the most common methods to evaluate students' achievement in …

Text document classification approaches are designed to categorise documents into
predefined classes. These approaches have two main components: document …

Text classification is a central task in Natural Language Processing (NLP) that aims at
categorizing text documents into predefined classes or categories. It requires appropriate …

Source Code Authorship Attribution (SCAA) is to find the real author of source code in a
corpus. Though, it is a privacy threat to open-source programmers, but, it may be …

Learning knowledge is simply one aspect of education but thinking skills are also taught.
Bloom's taxonomy is mostly used for question formulation and evaluation of examination …

Feature selection method is designed to select the representative feature subsets from the
original feature set by different evaluation of feature relevance, which focuses on reducing …

In text analysis tasks like text classification and sentiment analysis, the careful choice of term
weighting schemes can have an important impact on the effectiveness. Classic …

TF-IDF is one of the most popular term-weighting schemes, and is applied by search
engines, recommender systems, and user modeling engines. With regard to user modeling …

Though the strong evolution of knowledge learning models has characterized the last few
years, the explanation of a phenomenon from text documents, called descriptive text mining …

With the rapid growth of information retrieval technology, Chinese text classification, which is
the basis of information content security, has become a widely discussed topic. In view of the …