The effectiveness of Neuro-Linguistic Programming (NLP) on students’ motivation and attitude

Neuro-Linguistic Programming (NLP) was developed at the University of California at Santa Cruz in the 1970's by its founders and principal authors, Richard Bandler and John Grinder, a professor of linguistics (Tosey & Mathison, 2003). Richard Bandler was a mathematics and computer science students while John Grinder is a linguistics professor. NLP helps in the teaching and learning process, especially in the classroom management. NLP was first introduced in Malaysia in the 21st century and since there are many training centres such as Akademi NLP Malaysia which train Malaysian universities and polytechnic lecturers and NLP Malaysia Centre of Excellence (NLPMC) which was the first to train NLP in Malay language

Constraint programming in computational linguistics

Constraint programming is a programming paradigm that was originally invented in computer science to deal with hard combinatorial problems. Recently, constraint programming has evolved into a technology which permits to solve hard industrial scheduling and optimization problems. We argue that existing constraint programming technology can be useful for applications in natural language processing. Some problems whose treatment with traditional methods requires great care to avoid combinatorial explosion of (potential) readings seem to be solvable in an efficient and elegant manner using constraint programming. We illustrate our claim by two recent examples, one from the area of underspecified semantics and one from parsing

Towards the integration of functions, relations and types in an AI programming language

This paper describes the design and implementation of the programming language PC-Life. This language integrates the functional and the Logic-oriented programming style and feature types supporting inheritance. This combination yields a language particularly suited to knowledge representation, especially for application in computational linguistics

Semantic Variation in Online Communities of Practice

We introduce a framework for quantifying semantic variation of common words in Communities of Practice and in sets of topic-related communities. We show that while some meaning shifts are shared across related communities, others are community-specific, and therefore independent from the discussed topic. We propose such findings as evidence in favour of sociolinguistic theories of socially-driven semantic variation. Results are evaluated using an independent language modelling task. Furthermore, we investigate extralinguistic features and show that factors such as prominence and dissemination of words are related to semantic variation.Comment: 13 pages, Proceedings of the 12th International Conference on Computational Semantics (IWCS 2017