Towards an ontology based framework for searching multimedia contents on the web

Shrivastav, Shikhar; Kumar, Sandeep; Kumar, Kuldeep

doi:10.1007/s11042-017-4350-5

Cited by 6 publications

(2 citation statements)

References 26 publications

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“…[58] emphasize the importance of considering individual preferences and multiple pathologies in understanding and addressing these challenges. [59] explored the challenges of managing multimedia content, while [60] identified the main challenge of retrieving, analyzing, organizing, and indexing information. Producers often produce large amounts of multimedia content without considering management.…”

Section: (12) Web Servicesmentioning

confidence: 99%

Innovative Emerging Ontology-driven Frameworks: A Systematic Literature Review

Mokgetse,

Hlomani,

Sigwele

2023

IJEEI

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Previous research has shown that ontologies and related semantic web technologies have positioned themselves as good solutions for data integration and resource reusability. Pitfalls and traps in modelling domains can be avoided if researchers and scholars adopt and use ontology-driven frameworks for their research. This research work aims to review currently developed or proposed ontology-driven frameworks, and clearly illustrate their development, application, and practicality. The review then ultimately addresses three main research questions driving the literature review through a synthesis of information that exists about ontology-driven frameworks. Search strings were used to obtain articles from online electronic databases. The PRISMA chart was used for the final selection of the 60 articles for review. A method of scoring called the Assessment of Multiple System Reviews (AMSTAR) was used on the included studies for quality assessment. The AMSTAR mean overall result was 9, the median 10, and the standard deviation 0.99. The results reveal a downward trend of ontologies in 2010, with Web Ontology Language (OWL) being the most used language for ontology-driven frameworks and systems, with over 70% usage.

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Section: (12) Web Servicesmentioning

confidence: 99%

Innovative Emerging Ontology-driven Frameworks: A Systematic Literature Review

Mokgetse,

Hlomani,

Sigwele

2023

IJEEI

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“…Szeto and Wong [4] used string matching algorithm to find patterns in musical databases. Srivastava et al [5] proposed a framework for searching multimedia contents, such as text, image, and audio. The authors used query-based algorithms that involve string matching approach to search texts.…”

Section: Introductionmentioning

confidence: 99%

Exact String Matching Algorithms: Survey, Issues, and Future Research Directions

et al. 2019

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String matching has been an extensively studied research domain in the past two decades due to its various applications in the fields of text, image, signal, and speech processing. As a result, choosing an appropriate string matching algorithm for current applications and addressing challenges is difficult. Understanding different string matching approaches (such as exact string matching and approximate string matching algorithms), integrating several algorithms, and modifying algorithms to address related issues are also difficult. This paper presents a survey on single-pattern exact string matching algorithms. The main purpose of this survey is to propose new classification, identify new directions and highlight the possible challenges, current trends, and future works in the area of string matching algorithms with a core focus on exact string matching algorithms.

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On Two-Dimensional Approximate Pattern Matching Using Fuzzy Automata

John Kaspar,

Sheena Christy

2024

Lecture Notes in Networks and Systems

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Towards an ontology based framework for searching multimedia contents on the web

Cited by 6 publications

References 26 publications

Innovative Emerging Ontology-driven Frameworks: A Systematic Literature Review

Innovative Emerging Ontology-driven Frameworks: A Systematic Literature Review

Exact String Matching Algorithms: Survey, Issues, and Future Research Directions

On Two-Dimensional Approximate Pattern Matching Using Fuzzy Automata

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