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  • Open Access

    ARTICLE

    Shallow Neural Network and Ontology-Based Novel Semantic Document Indexing for Information Retrieval

    Anil Sharma1,*, Suresh Kumar2

    Intelligent Automation & Soft Computing, Vol.34, No.3, pp. 1989-2005, 2022, DOI:10.32604/iasc.2022.026095

    Abstract Information Retrieval (IR) systems are developed to fetch the most relevant content matching the user’s information needs from a pool of information. A user expects to get IR results based on the conceptual contents of the query rather than keywords. But traditional IR approaches index documents based on the terms that they contain and ignore semantic descriptions of document contents. This results in a vocabulary gap when queries and documents use different terms to describe the same concept. As a solution to this problem and to improve the performance of IR systems, we have designed a Shallow Neural Network and… More >

  • Open Access

    ARTICLE

    Ontology-Based Semantic Search Framework for Disparate Datasets

    Paramjeet Kaur1, Parma Nand1, Salman Naseer2, Akber Abid Gardezi3, Fawaz Alassery4, Habib Hamam5, Omar Cheikhrouhou6, Muhammad Shafiq7,*

    Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1717-1728, 2022, DOI:10.32604/iasc.2022.023063

    Abstract The public sector provides open data to create new opportunities, stimulate innovation, and implement new solutions that benefit academia and society. However, open data is usually available in large quantities and often lacks quality, accuracy, and completeness. It may be difficult to find the right data to analyze a target. There are many rich open data repositories, but they are difficult to understand and use because these data can only be used with a complex set of keyword search options, and even then, irrelevant or insufficient data may eventually be retrieved. To alleviate this situation, ontology-based semantic search has been… More >

  • Open Access

    ARTICLE

    Modelling and Verification of Context-Aware Intelligent Assistive Formalism

    Shahid Yousaf1,*, Hafiz Mahfooz Ul Haque2, Abbas Khalid1, Muhammad Adnan Hashmi3, Eraj Khan1

    CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3355-3373, 2022, DOI:10.32604/cmc.2022.023019

    Abstract Recent years have witnessed the expeditious evolution of intelligent smart devices and autonomous software technologies with the expanded domains of computing from workplaces to smart computing in everyday routine life activities. This trend has been rapidly advancing towards the new generation of systems where smart devices play vital roles in acting intelligently on behalf of the users. Context-awareness has emerged from the pervasive computing paradigm. Context-aware systems have the ability to acquire contextual information from the surrounding environment autonomously, perform reasoning on it, and then adapt their behaviors accordingly. With the proliferation of context-aware systems and smart sensors, real-time monitoring… More >

  • Open Access

    ARTICLE

    Interactive Middleware Services for Heterogeneous Systems

    Vasanthi Raghupathy1,*, Osamah Ibrahim Khalaf2, Carlos Andrés Tavera Romero3, Sudhakar Sengan4, Dilip Kumar Sharma5

    Computer Systems Science and Engineering, Vol.41, No.3, pp. 1241-1253, 2022, DOI:10.32604/csse.2022.021997

    Abstract Computing has become more invisible, widespread and ubiquitous since the inception of the Internet of Things (IoT) and Web of Things. Multiple devices that surround us meet user’s requirements everywhere. Multiple Middleware Framework (MF) designs have come into existence because of the rapid development of interactive services in Heterogeneous Systems. This resulted in the delivery of interactive services throughout Heterogeneous Environments (HE). Users are given free navigation between devices in a widespread environment and continuously interact with each other from any chosen device. Numerous interactive devices with recent interactive platforms (for example, Smart Phones, Mobile Phones, Personal Computer (PC) and… More >

  • Open Access

    ARTICLE

    Enhanced Neuro-Fuzzy-Based Crop Ontology for Effective Information Retrieval

    K. Ezhilarasi1,*, G. Maria Kalavathy2

    Computer Systems Science and Engineering, Vol.41, No.2, pp. 569-582, 2022, DOI:10.32604/csse.2022.020280

    Abstract Ontology is the progression of interpreting the conceptions of the information domain for an assembly of handlers. Familiarizing ontology as information retrieval (IR) aids in augmenting the searching effects of user-required relevant information. The crux of conventional keyword matching-related IR utilizes advanced algorithms for recovering facts from the Internet, mapping the connection between keywords and information, and categorizing the retrieval outcomes. The prevailing procedures for IR consume considerable time, and they could not recover information proficiently. In this study, through applying a modified neuro-fuzzy algorithm (MNFA), the IR time is mitigated, and the retrieval accuracy is enhanced for trouncing the… More >

  • Open Access

    ARTICLE

    Ontology Based Ocean Knowledge Representation for Semantic Information Retrieval

    Anitha Velu*, Menakadevi Thangavelu

    CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4707-4724, 2022, DOI:10.32604/cmc.2022.020095

    Abstract The drastic growth of coastal observation sensors results in copious data that provide weather information. The intricacies in sensor-generated big data are heterogeneity and interpretation, driving high-end Information Retrieval (IR) systems. The Semantic Web (SW) can solve this issue by integrating data into a single platform for information exchange and knowledge retrieval. This paper focuses on exploiting the SW base system to provide interoperability through ontologies by combining the data concepts with ontology classes. This paper presents a 4-phase weather data model: data processing, ontology creation, SW processing, and query engine. The developed Oceanographic Weather Ontology helps to enhance data… More >

  • Open Access

    ARTICLE

    Ontology Driven Testing Strategies for IoT Applications

    Muhammad Raza Naqvi1, Muhammad Waseem Iqbal2, Muhammad Usman Ashraf3, Shafiq Ahmad4, Ahmed T. Soliman4, Shahzada Khurram5, Muhammad Shafiq6,*, Jin-Ghoo Choi6

    CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5855-5869, 2022, DOI:10.32604/cmc.2022.019188

    Abstract Internet-of-Things (IoT) has attained a major share in embedded software development. The new era of specialized intelligent systems requires adaptation of customized software engineering approaches. Currently, software engineering has merged the development phases with the technologies provided by industrial automation. The improvements are still required in testing phase for the software developed to IoT solutions. This research aims to assist in developing the testing strategies for IoT applications, therein ontology has been adopted as a knowledge representation technique to different software engineering processes. The proposed ontological model renders 101 methodology by using Protégé. After completion, the ontology was evaluated in… More >

  • Open Access

    ARTICLE

    Using DEMATEL for Contextual Learner Modeling in Personalized and Ubiquitous Learning

    Saurabh Pal1, Pijush Kanti Dutta Pramanik1, Musleh Alsulami2, Anand Nayyar3,*, Mohammad Zarour4, Prasenjit Choudhury1

    CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 3981-4001, 2021, DOI:10.32604/cmc.2021.017966

    Abstract With the popularity of e-learning, personalization and ubiquity have become important aspects of online learning. To make learning more personalized and ubiquitous, we propose a learner model for a query-based personalized learning recommendation system. Several contextual attributes characterize a learner, but considering all of them is costly for a ubiquitous learning system. In this paper, a set of optimal intrinsic and extrinsic contexts of a learner are identified for learner modeling. A total of 208 students are surveyed. DEMATEL (Decision Making Trial and Evaluation Laboratory) technique is used to establish the validity and importance of the identified contexts and find… More >

  • Open Access

    ARTICLE

    Ontology-Based System for Educational Program Counseling

    Mamoona Majid1, Muhammad Faisal Hayat2, Farrukh Zeeshan Khan3, Muneer Ahmad4,*, NZ Jhanjhi5, Mohammad Arif Sobhan Bhuiyan6, Mehedi Masud7, Mohammed A. AlZain8

    Intelligent Automation & Soft Computing, Vol.30, No.1, pp. 373-386, 2021, DOI:10.32604/iasc.2021.017840

    Abstract Choosing the right university program can be very challenging for students. This is especially the case in developing countries such as India and Pakistan, where university admission depends on not only the program of interest but also other factors such as the candidate’s financial standing. Since information on the Internet can be highly scattered, university candidates often need counseling from qualified people to decide their educational programs. Traditional database systems cannot effectively organize the large unstructured data related to university programs. It is challenging, then, for prospective students to acquire the information needed to make good decisions to consider factors… More >

  • Open Access

    ARTICLE

    Semantic Modeling of Events Using Linked Open Data

    Sehrish Jamil1, Salma Noor1,*, Iftikhar Ahmed2, Neelam Gohar1, Fouzia1

    Intelligent Automation & Soft Computing, Vol.29, No.2, pp. 511-524, 2021, DOI:10.32604/iasc.2021.017770

    Abstract Significant happenings in terms of spatio-temporal factors are called events. In the digital age, these events and their associated features are scattered in various databases on the Internet. The event data are in heterogeneous formats, which are often not machine-readable. This leads to a lack of unification of event-related knowledge across different domains and results in a research gap in terms of event modeling and representation. Specialized event models are needed to overcome this gap and integrate relevant information of different similar events occurring worldwide. Our research explores the problem of heterogeneity in specialized event modeling and takes modeling for… More >

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