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  • Open Access


    Asymmetric Consortium Blockchain and Homomorphically Polynomial-Based PIR for Secured Smart Parking Systems

    T. Haritha, A. Anitha*

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3923-3939, 2023, DOI:10.32604/cmc.2023.036278

    Abstract In crowded cities, searching for the availability of parking lots is a herculean task as it results in the wastage of drivers’ time, increases air pollution, and traffic congestion. Smart parking systems facilitate the drivers to determine the information about the parking lot in real time and book them depending on the requirement. But the existing smart parking systems necessitate the drivers to reveal their sensitive information that includes their mobile number, personal identity, and desired destination. This disclosure of sensitive information makes the existing centralized smart parking systems more vulnerable to service providers’ security breaches, single points of failure,… More >

  • Open Access


    Natural Language Processing with Optimal Deep Learning-Enabled Intelligent Image Captioning System

    Radwa Marzouk1, Eatedal Alabdulkreem2, Mohamed K. Nour3, Mesfer Al Duhayyim4,*, Mahmoud Othman5, Abu Sarwar Zamani6, Ishfaq Yaseen6, Abdelwahed Motwakel6

    CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 4435-4451, 2023, DOI:10.32604/cmc.2023.033091

    Abstract The recent developments in Multimedia Internet of Things (MIoT) devices, empowered with Natural Language Processing (NLP) model, seem to be a promising future of smart devices. It plays an important role in industrial models such as speech understanding, emotion detection, home automation, and so on. If an image needs to be captioned, then the objects in that image, its actions and connections, and any silent feature that remains under-projected or missing from the images should be identified. The aim of the image captioning process is to generate a caption for image. In next step, the image should be provided with… More >

  • Open Access


    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

    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 specifically for the Urdu language.… More >

  • Open Access


    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


    Contextual Text Mining Framework for Unstructured Textual Judicial Corpora through Ontologies

    Zubair Nabi1, Ramzan Talib1,*, Muhammad Kashif Hanif1, Muhammad Awais2

    Computer Systems Science and Engineering, Vol.43, No.3, pp. 1357-1374, 2022, DOI:10.32604/csse.2022.025712

    Abstract Digitalization has changed the way of information processing, and new techniques of legal data processing are evolving. Text mining helps to analyze and search different court cases available in the form of digital text documents to extract case reasoning and related data. This sort of case processing helps professionals and researchers to refer the previous case with more accuracy in reduced time. The rapid development of judicial ontologies seems to deliver interesting problem solving to legal knowledge formalization. Mining context information through ontologies from corpora is a challenging and interesting field. This research paper presents a three tier contextual text… More >

  • Open Access


    Application of Quicksort Algorithm in Information Retrieval

    Jiajun Xie1, Zuyan Li1, Han Wu1, Linhan Li2, Bin Pan1, Peng Guo3,Guang Sun1,*

    Journal on Big Data, Vol.3, No.4, pp. 135-145, 2021, DOI:10.32604/jbd.2021.017017

    Abstract With the development and progress of today’s network information technology, a variety of large-scale network databases have emerged with the situation, such as Baidu Library and Weipu Database, the number of documents in the inventory has reached nearly one million. So how do you quickly and effectively retrieve the information you want in such a huge database? This requires finding efficient algorithms to reduce the computational complexity of the computer during Information Retrieval, improve retrieval efficiency, and adapt to the rapid expansion of document data. The Quicksort Algorithm gives different weights to each position of the document, and multiplies the… More >

  • Open Access


    Deep Neural Network and Pseudo Relevance Feedback Based Query Expansion

    Abhishek Kumar Shukla*, Sujoy Das

    CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3557-3570, 2022, DOI:10.32604/cmc.2022.022411

    Abstract The neural network has attracted researchers immensely in the last couple of years due to its wide applications in various areas such as Data mining, Natural language processing, Image processing, and Information retrieval etc. Word embedding has been applied by many researchers for Information retrieval tasks. In this paper word embedding-based skip-gram model has been developed for the query expansion task. Vocabulary terms are obtained from the top “k” initially retrieved documents using the Pseudo relevance feedback model and then they are trained using the skip-gram model to find the expansion terms for the user query. The performance of the… More >

  • Open Access


    Personalized Information Retrieval from Friendship Strength of Social Media Comments

    Fiaz Majeed1, Noman Yousaf2, Muhammad Shafiq3,*, Mohammed Ahmed Basheikh4, Wazir Zada Khan5, Akber Abid Gardezi6, Waqar Aslam7, Jin-Ghoo Choi3

    Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 15-30, 2022, DOI:10.32604/iasc.2022.015685

    Abstract Social networks have become an important venue to express the feelings of their users on a large scale. People are intuitive to use social networks to express their feelings, discuss ideas, and invite folks to take suggestions. Every social media user has a circle of friends. The suggestions of these friends are considered important contributions. Users pay more attention to suggestions provided by their friends or close friends. However, as the content on the Internet increases day by day, user satisfaction decreases at the same rate due to unsatisfactory search results. In this regard, different recommender systems have been developed… More >

  • Open Access


    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


    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 >

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