Efficient calculation of sentence semantic similarity: a proposed scheme based on machine learning approaches and NLP te

Journal Title: Scientific Journal of Review - Year 2014, Vol 3, Issue 3

Abstract

Sentence semantic similarity plays a crucial role in a variety of applications such as Machine Translation, Information Retrieval, Question Answering and Multi-document Summarization. Considering the variability of natural language expression, sentence semantic similarity detection is not a trivial task. This paper tries to make use of Natural Language Processing (NLP) as well as machine learning techniques in order to propose a scheme for sentence semantic similarity. In the first part of the proposed scheme, i.e., the NLP section, different sets of linguistic features including string-based, semantic-based, Named Entity-based and syntax-based features are extracted. In the second part, machine learning algorithms are used to construct classification models on the extracted set of features. Experimental results in the first part indicate that extracted features are valid for sentence semantic similarity. Moreover, by comparing the performance of different classification algorithms in the second part, KNN seems to be the most successful algorithm. Overall, experimental results indicate that the proposed approach can be used to improve the performance of sentence semantic similarity detection especially in terms of accuracy.

Authors and Affiliations

M. Roostaee| Department of Computer Science and Engineering and IT, School of Electrical Engineering and Computer, Shiraz, Iran., S. M. Fakhrahmad| Department of Computer Science and Engineering and IT, School of Electrical Engineering and Computer, Shiraz, Iran., M. H. Sadreddini*| Department of Computer Science and Engineering and IT, School of Electrical Engineering and Computer, Shiraz, Iran., A. Khalili| Department of Computer Science and Engineering and IT, School of Electrical Engineering and Computer, Shiraz, Iran.

Keywords

Related Articles

Introduced flora, and geographic distribution qalajeh protected area in Kermanshah province

In this study, Flora Qalajeh protected area in the province of Kermanshah, was evaluated, the area along.. 33.56 N, and longitude 46.20. E. Is located. Study showed that, in the study area, 46 black, 156 genera, 243 spec...

Effects of temperature and day length on development rate of safflower cultivars

Cropdevelopment is qualitative changes planned that makes the plant to ripening. Under irrigated conditionsexpected only climate elements able to change of plant growth and developmentand under these conditions, temperat...

Combination of air ionization and engineering physics methods for optimization agroindustry

Air/water ionization technology (AIT) in the greenhouse farms is one of the offering methods of increasing healthy crops and much more productions as usual methods in agricultural industry. AIT is a hi-tech equipment f...

A study of personality aspects of the prophet of Islam (PBUH) in the holy Qur’an and its comparison with the poetry of w

With the emergence of Islam faith throughout the Arabia Peninsula, the Arabian poetry entered a new era. The poets who eulogized Arab tribes’ ideals at the Pre-Islamic Ignorance Age, at the dawn of Islam changed their...

Survey affects of effective factors on contracts for development of south pars gas field

Exploration and extraction contracts are the main tool for using foreign new technologies for development of offshore oil and gas resources. Some factors such as risk aversion of owner country and foreign company, oil an...

Download PDF file
  • EP ID EP89
  • DOI 10.14196/sjr.v3i3.1259
  • Views 555
  • Downloads 39

How To Cite

M. Roostaee, S. M. Fakhrahmad, M. H. Sadreddini*, A. Khalili (2014). Efficient calculation of sentence semantic similarity: a proposed scheme based on machine learning approaches and NLP te. Scientific Journal of Review, 3(3), 94-106. https://europub.co.uk/articles/-A-89