Chaithra^1,*, 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 >

N. Vanitha^1,*, 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 >

P. D. Sheena Smart^1,*, 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 >

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 >

Hai Long¹, Zhe Wang¹, Yidi Cui^2,3, Junhui Wang⁴, Bo Gao⁵, Chao Chen⁵, Yan Zhu^5,*, Heinrich Herre¹

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5197-5217, 2022, DOI:10.32604/cmc.2022.029365 - 28 July 2022

Abstract Psoriasis is a chronic, non-communicable, painful, disfiguring and disabling disease for which there is no cure, with great negative impact on patients’ quality of life (QoL). Diagnosis and treatment with traditional Chinese medical technique based on syndrome differentiation has been used in practice for a long time and proven effective, though, up to now, there are only a few available studies about the use of semantic technologies and the knowledge systems that use Traditional Chinese Medicine (TCM)-syndrome differentiation for information retrieval and automated reasoning. In this paper we use semantic techniques based on ontologies to… More >

Anil Sharma^1,*, Suresh Kumar²

Intelligent Automation & Soft Computing, Vol.34, No.3, pp. 1989-2005, 2022, DOI:10.32604/iasc.2022.026095 - 25 May 2022

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… More >

Paramjeet Kaur¹, Parma Nand¹, Salman Naseer², Akber Abid Gardezi³, Fawaz Alassery⁴, Habib Hamam⁵, Omar Cheikhrouhou⁶, Muhammad Shafiq^7,*

Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1717-1728, 2022, DOI:10.32604/iasc.2022.023063 - 09 December 2021

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,… More >

Shahid Yousaf^1,*, 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 - 07 December 2021

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… More >

Vasanthi Raghupathy^1,*, 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 - 10 November 2021

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… More >

K. Ezhilarasi^1,*, G. Maria Kalavathy²

Computer Systems Science and Engineering, Vol.41, No.2, pp. 569-582, 2022, DOI:10.32604/csse.2022.020280 - 25 October 2021

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… More >