Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (10)
  • Open Access


    A Deep Learning Based Sentiment Analytic Model for the Prediction of Traffic Accidents

    Nadeem Malik1,*, Saud Altaf1, Muhammad Usman Tariq2, Ashir Ahmed3, Muhammad Babar4

    CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 1599-1615, 2023, DOI:10.32604/cmc.2023.040455

    Abstract The severity of traffic accidents is a serious global concern, particularly in developing nations. Knowing the main causes and contributing circumstances may reduce the severity of traffic accidents. There exist many machine learning models and decision support systems to predict road accidents by using datasets from different social media forums such as Twitter, blogs and Facebook. Although such approaches are popular, there exists an issue of data management and low prediction accuracy. This article presented a deep learning-based sentiment analytic model known as Extra-large Network Bi-directional long short term memory (XLNet-Bi-LSTM) to predict traffic collisions based on data collected from… More >

  • Open Access


    Chimp Optimization Algorithm Based Feature Selection with Machine Learning for Medical Data Classification

    Firas Abedi1, Hayder M. A. Ghanimi2, Abeer D. Algarni3, Naglaa F. Soliman3,*, Walid El-Shafai4,5, Ali Hashim Abbas6, Zahraa H. Kareem7, Hussein Muhi Hariz8, Ahmed Alkhayyat9

    Computer Systems Science and Engineering, Vol.47, No.3, pp. 2791-2814, 2023, DOI:10.32604/csse.2023.038762

    Abstract Data mining plays a crucial role in extracting meaningful knowledge from large-scale data repositories, such as data warehouses and databases. Association rule mining, a fundamental process in data mining, involves discovering correlations, patterns, and causal structures within datasets. In the healthcare domain, association rules offer valuable opportunities for building knowledge bases, enabling intelligent diagnoses, and extracting invaluable information rapidly. This paper presents a novel approach called the Machine Learning based Association Rule Mining and Classification for Healthcare Data Management System (MLARMC-HDMS). The MLARMC-HDMS technique integrates classification and association rule mining (ARM) processes. Initially, the chimp optimization algorithm-based feature selection (COAFS)… More >

  • Open Access


    An Adaptive Privacy Preserving Framework for Distributed Association Rule Mining in Healthcare Databases

    Hasanien K. Kuba1, Mustafa A. Azzawi2, Saad M. Darwish3,*, Oday A. Hassen4, Ansam A. Abdulhussein5

    CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 4119-4133, 2023, DOI:10.32604/cmc.2023.033182

    Abstract It is crucial, while using healthcare data, to assess the advantages of data privacy against the possible drawbacks. Data from several sources must be combined for use in many data mining applications. The medical practitioner may use the results of association rule mining performed on this aggregated data to better personalize patient care and implement preventive measures. Historically, numerous heuristics (e.g., greedy search) and metaheuristics-based techniques (e.g., evolutionary algorithm) have been created for the positive association rule in privacy preserving data mining (PPDM). When it comes to connecting seemingly unrelated diseases and drugs, negative association rules may be more informative… More >

  • Open Access


    Effective Diagnosis of Lung Cancer via Various Data-Mining Techniques

    Subramanian Kanageswari1, D. Gladis2, Irshad Hussain3,*, Sultan S. Alshamrani4, Abdullah Alshehri5

    Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 415-428, 2023, DOI:10.32604/iasc.2023.032053

    Abstract One of the leading cancers for both genders worldwide is lung cancer. The occurrence of lung cancer has fully augmented since the early 19th century. In this manuscript, we have discussed various data mining techniques that have been employed for cancer diagnosis. Exposure to air pollution has been related to various adverse health effects. This work is subject to analysis of various air pollutants and associated health hazards and intends to evaluate the impact of air pollution caused by lung cancer. We have introduced data mining in lung cancer to air pollution, and our approach includes preprocessing, data mining, testing… More >

  • Open Access


    Association Rule Analysis-Based Identification of Influential Users in the Social Media

    Saqib Iqbal1, Rehan Khan2, Hikmat Ullah Khan2,*, Fawaz Khaled Alarfaj4, Abdullah Mohammed Alomair3, Muzamil Ahmed2

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 6479-6493, 2022, DOI:10.32604/cmc.2022.030881

    Abstract The exchange of information is an innate and natural process that assist in content dispersal. Social networking sites emerge to enrich their users by providing the facility for sharing information and social interaction. The extensive adoption of social networking sites also resulted in user content generation. There are diverse research areas explored by the researchers to investigate the influence of social media on users and confirmed that social media sites have a significant impact on markets, politics and social life. Facebook is extensively used platform to share information, thoughts and opinions through posts and comments. The identification of influential users… More >

  • Open Access


    Association Rule Mining Frequent-Pattern-Based Intrusion Detection in Network

    S. Sivanantham1,*, V. Mohanraj2, Y. Suresh2, J. Senthilkumar2

    Computer Systems Science and Engineering, Vol.44, No.2, pp. 1617-1631, 2023, DOI:10.32604/csse.2023.025893

    Abstract In the network security system, intrusion detection plays a significant role. The network security system detects the malicious actions in the network and also conforms the availability, integrity and confidentiality of data information resources. Intrusion identification system can easily detect the false positive alerts. If large number of false positive alerts are created then it makes intrusion detection system as difficult to differentiate the false positive alerts from genuine attacks. Many research works have been done. The issues in the existing algorithms are more memory space and need more time to execute the transactions of records. This paper proposes a… More >

  • Open Access


    Preserving Data Confidentiality in Association Rule Mining Using Data Share Allocator Algorithm

    D. Dhinakaran1,*, P. M. Joe Prathap2

    Intelligent Automation & Soft Computing, Vol.33, No.3, pp. 1877-1892, 2022, DOI:10.32604/iasc.2022.024509

    Abstract These days, investigations of information are becoming essential for various associations all over the globe. By and large, different associations need to perform information examinations on their joined data sets. Privacy and security have become a relentless concern wherein business experts do not desire to contribute their classified transaction data. Therefore, there is a requirement to build a proficient methodology that can process the broad mixture of data and convert those data into meaningful knowledge to the user without forfeiting the security and privacy of individuals’ crude information. We devised two unique protocols for frequent mining itemsets in horizontally partitioned… More >

  • Open Access


    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


    CARM: Context Based Association Rule Mining for Conventional Data

    Muhammad Shaheen1,*, Umair Abdullah2

    CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3305-3322, 2021, DOI:10.32604/cmc.2021.016766

    Abstract This paper is aimed to develop an algorithm for extracting association rules, called Context-Based Association Rule Mining algorithm (CARM), which can be regarded as an extension of the Context-Based Positive and Negative Association Rule Mining algorithm (CBPNARM). CBPNARM was developed to extract positive and negative association rules from Spatio-temporal (space-time) data only, while the proposed algorithm can be applied to both spatial and non-spatial data. The proposed algorithm is applied to the energy dataset to classify a country’s energy development by uncovering the enthralling interdependencies between the set of variables to get positive and negative associations. Many association rules related… More >

  • Open Access


    Finding Temporal Influential Users in Social Media Using Association Rule Learning

    Babar Shazad1, Hikmat Ullah khan2, Zahoor-ur-Rehman1, Muhammad Farooq2, Ahsan Mahmood1, Irfan Mehmood3,*, Seungmin Rho3, Yunyoung Nam4,*

    Intelligent Automation & Soft Computing, Vol.26, No.1, pp. 87-98, 2020, DOI:10.31209/2019.100000130

    Abstract The social media has become an integral part of our daily life. The social web users interact and thus influence each other influence in many aspects. Blogging is one of the most important features of the social web. The bloggers share their views, opinions and ideas in the form of blog posts. The influential bloggers are the leading bloggers who influence the other bloggers in their online communities. The relevant literature presents several studies related to identification of top influential bloggers in last decade. The research domain of finding the top influential bloggers mainly focuses on feature centric models. This… More >

Displaying 1-10 on page 1 of 10. Per Page