Modelling Grammaticality-grading in Natural Language Systems Using a Vector Space Approach

Journal Title: Journal of Advances in Mathematics and Computer Science - Year 2017, Vol 23, Issue 3

Abstract

There exist several natural language processing systems that focus on checking the grammaticality (grammatical correctness or incorrectness) of natural language texts. Studies however showed that most existing systems do not assign specific scores to the grammaticality of the analysed text. Such scores would for instance prove very useful to second language learners and tutors, for judging the progress made in the learning process and assigning performance scores respectively. The current study was embarked upon to address this problem. A grammaticality grading model which comprised of 6 equations was developed using a vector space approach. The model was implemented in a natural language processing system. Correlation analysis showed that the grading (in %) performed using the developed model correlated at a coefficient of determination (R2) value of 0.9985 with the percentage of grammatical sentences in evaluated texts. The developed model is therefore deemed suitable for grammaticality grading in natural language texts. The developed model would readily find use in computer aided language learning and automated essay scoring.

Authors and Affiliations

Moses Kehinde Aregbesola, Rafiu Adesina Ganiyu, Stephen Olatunde Olabiyisi, Elijah Olusayo Omidiora, Oluwaseun Olubisi Alo

Keywords

Related Articles

Results of Existence Fixed Point for Integral Type Contractive Condition with w-distance

In this paper, we prove the existence of xed point for mappings de ned on complete metric spaces with w-distance that satisfying a general contractive inequality of integral type.

Comparison among Unstructured TVD, ENO and UNO Schemes in Two-dimensions

In this work, unstructured TVD, ENO and UNO schemes are applied to solve the Euler equations in two-dimensions. They are implemented on a finite volume context and cell centered data base. The algorithms of Yee, Warming...

Modeling of Tomato Prices in Ashanti Region, Ghana, Using Seasonal Autoregressive Integrated Moving Average Model

The pricing of seasonal and perishable crops such as tomatoes is of paramount concern to emerging economies. In this paper, we have formulated a model for the prices of tomatoes in the Ashanti Region of Ghana. We applied...

The 7 and 8 Families of Hybrid Block Methods for Numerical Solution of Initial Value Problems in Stiff Equations

An independent hybrid block Simpson’s methods with a very closely accurate members of order p=q+2 as a block was formulated. This was obtained through increasing the number k in the multi-step collocation (MC). Maple sof...

Empirical Performance of Internal Sorting Algorithm

Internal Sorting Algorithms are used when the list of records is small enough to be maintained entirely in primary memory for the duration of the sort, while External Sorting Algorithms are used when the list of records...

Download PDF file
  • EP ID EP322043
  • DOI 10.9734/JAMCS/2017/32927
  • Views 100
  • Downloads 0

How To Cite

Moses Kehinde Aregbesola, Rafiu Adesina Ganiyu, Stephen Olatunde Olabiyisi, Elijah Olusayo Omidiora, Oluwaseun Olubisi Alo (2017). Modelling Grammaticality-grading in Natural Language Systems Using a Vector Space Approach. Journal of Advances in Mathematics and Computer Science, 23(3), 1-15. https://europub.co.uk./articles/-A-322043