This paper presents a novel text representation model called Convolution Term Model
(CTM) for effective text categorization. In the process of text categorization, representation …

Trending topics on forums or social networks are now being analysed to know our
preferences and needs. This line of thought can be applied to the educational context. In this …

In this paper, the problem of skewness in text corpora for effective classification is
addressed. A method of converting an imbalanced text corpus into a more or less balanced …

A sequential learning framework for text categorization based on Meta-cognitive Neural
Network (McNN) is presented in this paper. Initially text documents are pre-processed and …

 Abstract:-As the number of internet users are increasing day by day. This increase in
number was done because of the different available services, with dynamic functionality. So …

Supervisor: Frank Emmert-Streib Tampere University Master's Degree Programme in
Robotics and Artificial Intelligence October 2023 The Shapley value is one of the most …

Term weighting is a process of scoring and ranking a term's relevance to a user's information
need or the importance of a term to a document. This thesis aims to investigate novel term …

Abstract Model Driven Engineering (MDE), where models are the core elements in the entire
life cycle from the specification to maintenance phases, is one of the promising techniques to …

Computational linguistics encompasses a broad range of ideas and research areas, and
only a brief introduction is possible here. We chose to include areas in computational …

Statistical analysis of parliamentary roll call votes is an important topic in political science as
it reveals ideological positions of members of parliament and factions. However, these …