Papers by Keyword: Systematic Review

Abstract: Writing matching has evolved dramatically from simple string comparison algorithms to sophisticated natural language processing techniques. This comprehensive literature review examines matching methods over the last 20 years, with special emphasis on transitioning from traditional frameworks to modern NLP methods to identify opportunities for practical theoretical integration and development exploring both models' fundamental principles, strengths and limitations. Our systematic review covers three main areas: (1) classical text matching algorithms, including Levenstein distance, Boyer-Moore, and Knuth-Morris-Pratt; (2) modern NLP techniques, such as transformer-based models and contextual ontologies; and (3) emerging hybrid approaches that seek to integrate these approaches. Intensive analysis of more than 40 papers from leading areas in information retrieval, natural language processing, and algorithmic evolution reveals key patterns in adopting text-matching strategies and highlights promising directions for future research. The study highlights a significant difference between the computational efficiency of traditional methods and the logical comprehension capabilities of modern NLP methods. Our study examines various attempts to bridge this gap and discusses the challenges and opportunities in integrating classical and modern approaches. We examine how different approaches manage the trade-off between computational complexity, logical clarity, and application-specific requirements.

Abstract: The aim of this research paper focused on using PRISMA to reveal most artificial intelligence techniques that were used for fingerprint classification. Biometric technology such as fingerprints plays a key role in authenticating and identifying people’s identities. Therefore, with the increasing number of population and the usage of biometrics for authentication, fingerprint classification systems are becoming important and indispensable for recognizing and authenticating individuals. Therefore, Artificial Super-Intelligence (ASI) techniques such as bioinspired algorithm, deep learning and machine learning were used to improve fingerprint classification accuracy. The proposed method aimed to assess fingerprint classification models based on ASI. The researchers employed PRISMA approach, which is based on systematic analysis and is used to select, evaluate and analyze journals. Although IEEEXplore and Web of Science were utilized to extract journal articles from 2019 to 2023. As a result, 1350 articles were found in both databases. Furthermore, a total of 35 publications were assessed to determine their eligibility and 19 articles were eliminated with reasons and 16 matched the requirements for a meta-analysis. Our findings demonstrate and highlight the need for developing a new approach to improve fingerprint classification accuracy.

Abstract: This article provides a systematic review of Enterprise Architecture (EA) assessment model. The review main goal is to identify the existing EA assessment models and to categorise the models according to EA phases as well as to analyse the models limitation. The review result shows that there are 16 EA assessment models proposed across both industry and academic areas that fit in three EA phases mentioned.

Abstract: Use Interval Number Comparison Matrix to conduct a quantitative and comparative analysis on solar water heating system of civil buildings for the following six aspects: Systems and Building Integrated, System Application Performance, System Security, System Durability, System Economy, and System Components. By constructing a hierarchical model, we establish an interval number comparison matrix, determine the consistency and solve their weight vector. Based on the possibility, it finally make out the degree of evaluation index, provides the design and evaluation of actual solar heating system with decision-making basis.