Home / Journals / CSSE / Vol.34, No.3, 2019
  • Open Access

    ARTICLE

    A Two-Level Morphological Description of Bashkir Turkish

    Can Eyupoglu
    Computer Systems Science and Engineering, Vol.34, No.3, pp. 113-121, 2019, DOI:10.32604/csse.2019.34.113
    Abstract In recent years, the topic of Natural Language Processing (NLP) has attracted increasing interest. Many NLP applications including machine translation, machine learning, speech recognition, sentiment analysis, semantic search and natural language generation have been developed for most of the existing languages. Besides, two-level morphological description of the language to be used is required for these applications. However, there is no comprehensive study of Bashkir Turkish in the literature. In this paper, a two-level description of Bashkir Turkish morphology is described. The description based on a root word lexicon of Bashkir Turkish is implemented using Extensible Markup Language (XML) and appended… More >

  • Open Access

    ARTICLE

    A Novel Fuzzy Rough Sets Theory Based CF Recommendation System

    C. Raja Kumar1, VE. Jayanthi2
    Computer Systems Science and Engineering, Vol.34, No.3, pp. 123-129, 2019, DOI:10.32604/csse.2019.34.123
    Abstract Collaborative Filtering (CF) is one of the popular methodology in recommender systems. It suffers from the data sparsity problem, recommendation inaccuracy and big-error in predictions. In this paper, the efficient advisory tool is implemented for the younger generation to choose their right career based on their knowledge. It acquires the notions of indiscernible relation from Fuzzy Rough Sets Theory (FRST) and propose a novel algorithm named as Fuzzy Rough Set Theory Based Collaborative Filtering Algorithm (FRSTBCF). To evaluate the model, data is prepared using the cross validation method. Based on that, ratings are evaluated by calculating the MAE (mean average… More >

  • Open Access

    ARTICLE

    Non-Deterministic Outlier Detection Method Based on the Variable Precision Rough Set Model

    Alberto Fernández Oliva1, Francisco Maciá Pérez2, José Vicente Berná-Martinez2,*, Miguel Abreu Ortega3
    Computer Systems Science and Engineering, Vol.34, No.3, pp. 131-144, 2019, DOI:10.32604/csse.2019.34.131
    Abstract This study presents a method for the detection of outliers based on the Variable Precision Rough Set Model (VPRSM). The basis of this model is the generalisation of the standard concept of a set inclusion relation on which the Rough Set Basic Model (RSBM) is based. The primary contribution of this study is the improvement in detection quality, which is achieved due to the generalisation allowed by the classification system that allows a certain degree of uncertainty. From this method, a computationally efficient algorithm is proposed. The experiments performed with a real scenario and a comparison of the results with… More >

  • Open Access

    ARTICLE

    Application of Radial Basis Function Networks with Feature Selection for GDP Per Capita Estimation Based on Academic Parameters

    Abdullah Erdal Tümer1,∗, Aytekin Akku¸s2
    Computer Systems Science and Engineering, Vol.34, No.3, pp. 145-150, 2019, DOI:10.32604/csse.2019.34.145
    Abstract In this work, a system based on Radial Basis Function Network was developed to estimate Gross Domestic Product per capita. The data set based on 180 academic parameters of 13 Organisation for Economic Co-operation and Development countries was used to verify the effectiveness and accuracy of the proposed method. Gross Domestic Product per capita was studied to be estimated for the first time with academic parameters in this study. The system has been optimized using feature selection method to eliminate unimportant features. Radial Basis Function network results and Radial Basis Function network with feature selection method results were compared. The… More >

  • Open Access

    ARTICLE

    Teensensor: Gaussian Processes for Micro-Blog Based Teen’S Acute and Chronic Stress Detection

    Yuanyuan Xue1,2, Qi Li1, LingFeng1
    Computer Systems Science and Engineering, Vol.34, No.3, pp. 151-164, 2019, DOI:10.32604/csse.2019.34.151
    Abstract Stress is a common problem all over the world. More and more teenagers today have to cope with different stressor events coming from school, family, peer relation, self-cognition, romantic relation, etc. Over-stress without proper guidance will lead to a series of potential problems including physical and mental disorders, and even suicide due to the shortage of teen’ s psychological endurance and controllability. Therefore, it is necessary and important to timely sense adolescents’ stress and help them release the stress properly. In this paper, we present a micro-blog based system called TeenSensor, aiming to detect teens acute and chronic stress from… More >

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