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  • Open Access

    ARTICLE

    Integrating Ontology-Based Approaches with Deep Learning Models for Fine-Grained Sentiment Analysis

    Longgang Zhao1, Seok-Won Lee2,*

    CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 1855-1877, 2024, DOI:10.32604/cmc.2024.056215 - 15 October 2024

    Abstract Although sentiment analysis is pivotal to understanding user preferences, existing models face significant challenges in handling context-dependent sentiments, sarcasm, and nuanced emotions. This study addresses these challenges by integrating ontology-based methods with deep learning models, thereby enhancing sentiment analysis accuracy in complex domains such as film reviews and restaurant feedback. The framework comprises explicit topic recognition, followed by implicit topic identification to mitigate topic interference in subsequent sentiment analysis. In the context of sentiment analysis, we develop an expanded sentiment lexicon based on domain-specific corpora by leveraging techniques such as word-frequency analysis and word embedding. More >

  • Open Access

    ARTICLE

    Ontology-Based Crime News Semantic Retrieval System

    Fiaz Majeed1, Afzaal Ahmad1, Muhammad Awais Hassan2, Muhammad Shafiq3,*, Jin-Ghoo Choi3, Habib Hamam4,5,6,7

    CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 601-614, 2023, DOI:10.32604/cmc.2023.036074 - 31 October 2023

    Abstract Every day, the media reports tons of crimes that are considered by a large number of users and accumulate on a regular basis. Crime news exists on the Internet in unstructured formats such as books, websites, documents, and journals. From such homogeneous data, it is very challenging to extract relevant information which is a time-consuming and critical task for the public and law enforcement agencies. Keyword-based Information Retrieval (IR) systems rely on statistics to retrieve results, making it difficult to obtain relevant results. They are unable to understand the user's query and thus face word… More >

  • Open Access

    ARTICLE

    Exploring Splicing Variants and Novel Genes in Sacred Lotus Based on RNA-seq Data

    Xinyi Zhang, Zimeng Yu, Pingfang Yang*

    Phyton-International Journal of Experimental Botany, Vol.92, No.6, pp. 1665-1679, 2023, DOI:10.32604/phyton.2023.029482 - 11 April 2023

    Abstract Sacred lotus (Nelumbo nucifera) is a typical aquatic plant, belonging to basal eudicot plant, which is ideal for genome and genetic evolutionary study. Understanding lotus gene diversity is important for the study of molecular genetics and breeding. In this research, public RNA-seq data and the annotated reference genome were used to identify the genes in lotus. A total of 26,819 consensus and 1,081 novel genes were identified. Meanwhile, a comprehensive analysis of gene alternative splicing events was conducted, and a total of 19,983 “internal” alternative splicing (AS) events and 14,070 “complete” AS events were detected in… More >

  • Open Access

    ARTICLE

    Ontology-Based News Linking for Semantic Temporal Queries

    Muhammad Islam Satti1, Jawad Ahmed2, Hafiz Syed Muhammad Muslim1, Akber Abid Gardezi3, Shafiq Ahmad4, Abdelaty Edrees Sayed4, Salman Naseer5, Muhammad Shafiq6,*

    CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3913-3929, 2023, DOI:10.32604/cmc.2023.033001 - 31 October 2022

    Abstract Daily newspapers publish a tremendous amount of information disseminated through the Internet. Freely available and easily accessible large online repositories are not indexed and are in an un-processable format. The major hindrance in developing and evaluating existing/new monolingual text in an image is that it is not linked and indexed. There is no method to reuse the online news images because of the unavailability of standardized benchmark corpora, especially for South Asian languages. The corpus is a vital resource for developing and evaluating text in an image to reuse local news systems in general and… More >

  • Open Access

    ARTICLE

    Ontological Model for Cohesive Smart Health Services Management

    Muhammad Raza Naqvi1, Muhammad Waseem Iqbal2,*, Syed Khuram Shahzad3, M. Usman Ashraf4, Khalid Alsubhi5, Hani Moaiteq Aljahdali6

    CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3679-3695, 2023, DOI:10.32604/cmc.2023.030340 - 31 October 2022

    Abstract Health care has become an essential social-economic concern for all stakeholders (e.g., patients, doctors, hospitals etc.), health needs, private care and the elderly class of society. The massive increase in the usage of health care Internet of things (IoT) applications has great technological evolvement in human life. There are various smart health care services like remote patient monitoring, diagnostic, disease-specific remote treatments and telemedicine. These applications are available in a split fashion and provide solutions for variant diseases, medical resources and remote service management. The main objective of this research is to provide a management… More >

  • Open Access

    ARTICLE

    An Ontology-Based Question Answering System for University Admissions Advising

    Thi Thanh Sang Nguyen*, Dang Huu Trong Ho, Ngoc Tram Anh Nguyen

    Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 601-616, 2023, DOI:10.32604/iasc.2023.032080 - 29 September 2022

    Abstract Question-Answer systems are now very popular and crucial to support human in automatically responding frequent questions in many fields. However, these systems depend on learning methods and training data. Therefore, it is necessary to prepare such a good dataset, but it is not an easy job. An ontology-based domain knowledge base is able to help to reason semantic information and make effective answers given user questions. This study proposes a novel chatbot model involving ontology to generate efficient responses automatically. A case study of admissions advising at the International University–VNU HCMC is taken into account… More >

  • Open Access

    ARTICLE

    Web Page Recommendation Using Distributional Recurrent Neural Network

    Chaithra1,*, G. M. Lingaraju2, S. Jagannatha3

    Computer Systems Science and Engineering, Vol.45, No.1, pp. 803-817, 2023, DOI:10.32604/csse.2023.028770 - 16 August 2022

    Abstract In the data retrieval process of the Data recommendation system, the matching prediction and similarity identification take place a major role in the ontology. In that, there are several methods to improve the retrieving process with improved accuracy and to reduce the searching time. Since, in the data recommendation system, this type of data searching becomes complex to search for the best matching for given query data and fails in the accuracy of the query recommendation process. To improve the performance of data validation, this paper proposed a novel model of data similarity estimation and… More >

  • Open Access

    ARTICLE

    An Ontology Based Cyclone Tracks Classification Using SWRL Reasoning and SVM

    N. Vanitha1,*, C. R. Rene Robin1, D. Doreen Hephzibah Miriam2

    Computer Systems Science and Engineering, Vol.44, No.3, pp. 2323-2336, 2023, DOI:10.32604/csse.2023.028309 - 01 August 2022

    Abstract Abstract: Tropical cyclones (TC) are often associated with severe weather conditions which cause great losses to lives and property. The precise classification of cyclone tracks is significantly important in the field of weather forecasting. In this paper we propose a novel hybrid model that integrates ontology and Support Vector Machine (SVM) to classify the tropical cyclone tracks into four types of classes namely straight, quasi-straight, curving and sinuous based on the track shape. Tropical Cyclone TRacks Ontology (TCTRO) described in this paper is a knowledge base which comprises of classes, objects and data properties that More >

  • Open Access

    ARTICLE

    An Ontology Based Multilayer Perceptron for Object Detection

    P. D. Sheena Smart1,*, K. K. Thanammal2, S. S. Sujatha2

    Computer Systems Science and Engineering, Vol.44, No.3, pp. 2065-2080, 2023, DOI:10.32604/csse.2023.028053 - 01 August 2022

    Abstract In object detection, spatial knowledge assisted systems are effective. Object detection is a main and challenging issue to analyze object-related information. Several existing object detection techniques were developed to consider the object detection problem as a classification problem to perform feature selection and classification. But these techniques still face, less computational efficiency and high time consumption. This paper resolves the above limitations using the Fuzzy Tversky index Ontology-based Multi-Layer Perception method which improves the accuracy of object detection with minimum time. The proposed method uses a multilayer for finding the similarity score. A fuzzy membership More >

  • Open Access

    EDITORIAL

    INTRODUCTION

    Plumejeaud-Perreau, C, Gravier, J, Masson, E, Nahassia, L, Rodier, X, Saux, E, Fargette, M, Libourel, T, Mathian, H, Nuninger, L, Sanders, L

    Revue Internationale de Géomatique, Vol.31, No.1, pp. 7-19, 2022, DOI:10.3166/rig31.7-19

    Abstract This article has no abstract. More >

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