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  • Open Access

    ARTICLE

    Short Text Mining for Classifying Educational Objectives and Outcomes

    Yousef Asiri*

    Computer Systems Science and Engineering, Vol.41, No.1, pp. 35-50, 2022, DOI:10.32604/csse.2022.020100

    Abstract Most of the international accreditation bodies in engineering education (e.g., ABET) and outcome-based educational systems have based their assessments on learning outcomes and program educational objectives. However, mapping program educational objectives (PEOs) to student outcomes (SOs) is a challenging and time-consuming task, especially for a new program which is applying for ABET-EAC (American Board for Engineering and Technology the American Board for Engineering and Technology—Engineering Accreditation Commission) accreditation. In addition, ABET needs to automatically ensure that the mapping (classification) is reasonable and correct. The classification also plays a vital role in the assessment of students’ learning. Since the PEOs are… More >

  • Open Access

    ARTICLE

    Towards Aspect Based Components Integration Framework for Cyber-Physical System

    Sadia Ali1, Yaser Hafeez1, Muhammad Bilal2, Saqib Saeed3, Kyung Sup Kwak4,*

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 653-668, 2022, DOI:10.32604/cmc.2022.018779

    Abstract Cyber-Physical Systems (CPS) comprise interactive computation, networking, and physical processes. The integrative environment of CPS enables the smart systems to be aware of the surrounding physical world. Smart systems, such as smart health care systems, smart homes, smart transportation, and smart cities, are made up of complex and dynamic CPS. The components integration development approach should be based on the divide and conquer theory. This way multiple interactive components can reduce the development complexity in CPS. As reusability enhances efficiency and consistency in CPS, encapsulation of component functionalities and a well-designed user interface is vital for the better end-user's Quality… More >

  • Open Access

    REVIEW

    Analyzing Customer Reviews on Social Media via Applying Association Rule

    Nancy Awadallah Awad1,*, Amena Mahmoud2

    CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 1519-1530, 2021, DOI:10.32604/cmc.2021.016974

    Abstract The rapid growth of the use of social media opens up new challenges and opportunities to analyze various aspects and patterns in communication. In-text mining, several techniques are available such as information clustering, extraction, summarization, classification. In this study, a text mining framework was presented which consists of 4 phases retrieving, processing, indexing, and mine association rule phase. It is applied by using the association rule mining technique to check the associated term with the Huawei P30 Pro phone. Customer reviews are extracted from many websites and Facebook groups, such as re-view.cnet.com, CNET. Facebook and amazon.com technology, where customers from… More >

  • Open Access

    ARTICLE

    Automatic Surveillance of Pandemics Using Big Data and Text Mining

    Abdullah Alharbi1,*, Wael Alosaimi1, M. Irfan Uddin2

    CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 303-317, 2021, DOI:10.32604/cmc.2021.016230

    Abstract COVID-19 disease is spreading exponentially due to the rapid transmission of the virus between humans. Different countries have tried different solutions to control the spread of the disease, including lockdowns of countries or cities, quarantines, isolation, sanitization, and masks. Patients with symptoms of COVID-19 are tested using medical testing kits; these tests must be conducted by healthcare professionals. However, the testing process is expensive and time-consuming. There is no surveillance system that can be used as surveillance framework to identify regions of infected individuals and determine the rate of spread so that precautions can be taken. This paper introduces a… More >

  • Open Access

    ARTICLE

    COVID-19 Public Sentiment Insights: A Text Mining Approach to the Gulf Countries

    Saleh Albahli1, Ahmad Algsham1, Shamsulhaq Aeraj1, Muath Alsaeed1, Muath Alrashed1, Hafiz Tayyab Rauf2,*, Muhammad Arif3, Mazin Abed Mohammed4

    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 1613-1627, 2021, DOI:10.32604/cmc.2021.014265

    Abstract Social media has been the primary source of information from mainstream news agencies due to the large number of users posting their feedback. The COVID-19 outbreak did not only bring a virus with it but it also brought fear and uncertainty along with inaccurate and misinformation spread on social media platforms. This phenomenon caused a state of panic among people. Different studies were conducted to stop the spread of fake news to help people cope with the situation. In this paper, a semantic analysis of three levels (negative, neutral, and positive) is used to gauge the feelings of Gulf countries… More >

  • Open Access

    ARTICLE

    Decision Support System Tool for Arabic Text Recognition

    Fatmah Baothman*, Sarah Alssagaff, Bayan Ashmeel

    Intelligent Automation & Soft Computing, Vol.27, No.2, pp. 519-531, 2021, DOI:10.32604/iasc.2021.014828

    Abstract The National Center for Education Statistics study reported that 80% of students change their major or institution at least once before getting a degree, which requires a course equivalency process. This error-prone process varies among disciplines, institutions, regions, and countries and requires effort and time. Therefore, this study aims to overcome these issues by developing a decision support tool called TiMELY for automatic Arabic text recognition using artificial intelligence techniques. The developed tool can process a complete document analysis for several course descriptions in multiple file formats, such as Word, Text, Pages, JPEG, GIF, and JPG. We applied a comparative… More >

  • Open Access

    ARTICLE

    A Novel Framework for Biomedical Text Mining

    Janyl Jumadinova1, Oliver Bonham-Carter1, Hanzhong Zheng1,2,*, Michael Camara1, Dejie Shi3

    Journal on Big Data, Vol.2, No.4, pp. 145-155, 2020, DOI:10.32604/jbd.2020.010090

    Abstract Text mining has emerged as an effective method of handling and extracting useful information from the exponentially growing biomedical literature and biomedical databases. We developed a novel biomedical text mining model implemented by a multi-agent system and distributed computing mechanism. Our distributed system, TextMed, comprises of several software agents, where each agent uses a reinforcement learning method to update the sentiment of relevant text from a particular set of research articles related to specific keywords. TextMed can also operate on different physical machines to expedite its knowledge extraction by utilizing a clustering technique. We collected the biomedical textual data from… More >

  • Open Access

    ARTICLE

    Understanding the Language of ISIS: An Empirical Approach to Detect Radical Content on Twitter Using Machine Learning

    Zia Ul Rehman1,2, Sagheer Abbas1, Muhammad Adnan Khan3,*, Ghulam Mustafa2, Hira Fayyaz4, Muhammad Hanif1,2, Muhammad Anwar Saeed5

    CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1075-1090, 2021, DOI:10.32604/cmc.2020.012770

    Abstract The internet, particularly online social networking platforms have revolutionized the way extremist groups are influencing and radicalizing individuals. Recent research reveals that the process initiates by exposing vast audiences to extremist content and then migrating potential victims to confined platforms for intensive radicalization. Consequently, social networks have evolved as a persuasive tool for extremism aiding as recruitment platform and psychological warfare. Thus, recognizing potential radical text or material is vital to restrict the circulation of the extremist chronicle. The aim of this research work is to identify radical text in social media. Our contributions are as follows: (i) A new… More >

  • Open Access

    ARTICLE

    Word Embedding Based Knowledge Representation with Extracting Relationship Between Scientific Terminologies

    Mucheol Kim*, Junho Kim, Mincheol Shin

    Intelligent Automation & Soft Computing, Vol.26, No.1, pp. 141-147, 2020, DOI:10.31209/2019.100000135

    Abstract With the trends of big data era, many people want to acquire the reliable and refined information from web environments. However, it is difficult to find appropriate information because the volume and complexity of web information is increasing rapidly. So many researchers are focused on text mining and personalized recommendation for extracting users’ interests. The proposed approach extracted semantic relationship between scientific terminologies with word embedding approach. We aggregated science data in BT for supporting users’ wellness. In our experiments, query expansion is performed with relationship between scientific terminologies with user’s intention. More >

  • Open Access

    ARTICLE

    LRV: A Tool for Academic Text Visualization to Support the Literature Review Process

    Tahani Almutairi1,*, Maha Al-yahya2

    CMC-Computers, Materials & Continua, Vol.59, No.3, pp. 741-751, 2019, DOI:10.32604/cmc.2019.06239

    Abstract Text visualization is concerned with the representation of text in a graphical form to facilitate comprehension of large textual data. Its aim is to improve the ability to understand and utilize the wealth of text-based information available. An essential task in any scientific research is the study and review of previous works in the specified domain, a process that is referred to as the literature survey process. This process involves the identification of prior work and evaluating its relevance to the research question. With the enormous number of published studies available online in digital form, this becomes a cumbersome task… More >

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