Formal techniques for consistency checking of orchestrations of semantic Web services

Hammal, Youcef; Mansour, Khadidja Salah; Abdelli, Abdelkrim; Mokdad, Lynda

doi:10.1016/j.jocs.2020.101165

Cited by 14 publications

(5 citation statements)

References 11 publications

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“…Hammal et al [21] proposes a conventional technique for their regularity checking by first deciphering synthesized administration into imparting mechanism utilizing an iterative cycle driven by control structures of these dialects. Lampropoulos et al [22] present a work that how augmented reality base work can be improved by coordination of deep learning, linguistic web, and informative graphs.…”

Section: Literature Reviewmentioning

confidence: 99%

Semantic Analysis of Urdu English Tweets Empowered by Machine Learning

Tabassum¹,

Alyas²,

Hamid³

et al. 2021

Intelligent Automation &Amp; Soft Computing

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Development in the field of opinion mining and sentiment analysis has been rapid and aims to explore views or texts on various social media sites through machine-learning techniques with the sentiment, subjectivity analysis and calculations of polarity. Sentiment analysis is a natural language processing strategy used to decide if the information is positive, negative, or neutral and it is frequently performed on literature information to help organizations screen brand, item sentiment in client input, and comprehend client needs. In this paper, two strategies for sentiment analysis is proposed for word embedding and a bag of words on Urdu and English tweets. Word embedding is a notable arrangement of procedures that can remember words linguistics dependent on the spread theory which expresses that word is utilized and happens within the same settings tend to indicate comparable implications. Bag of words is an approach used in natural language processing to retrieve information and features from written documents. For the bag of words, machine learning techniques like naive bayes, decision tree, k-nearest neighbor, and support vector machine is used to enhance the accuracy. For word embedding the neural network technique is proposed by the combination of recurrent neural network (RNN) with long-short term memory (LSTM) for sentimental analysis of tweets. Datasets of Urdu and English tweets are used for negative and positive classification tweets with machine learning techniques. The contribution of this paper involves the implementation of a hybrid approach that focused on a sentiment analyzer to overcome social network challenges and also provided the comparative analysis of different machine learning algorithms. The results indicate improvement while using the combination of RNN with the help of LSTM showed accuracy 87% on the Urdu dataset and 92% on the English dataset.

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Section: Literature Reviewmentioning

confidence: 99%

Semantic Analysis of Urdu English Tweets Empowered by Machine Learning

Tabassum¹,

Alyas²,

Hamid³

et al. 2021

Intelligent Automation &Amp; Soft Computing

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“…The usability and consistency of web design were presented based on availability [8,9]. The user's usability must be based on how to design and how to design it easy and user-friendly as in (Fig 1).…”

Section: Introductionmentioning

confidence: 99%

Enhancing sustainability in web design: a comparative exploration of multimedia systems and technology management

Hu,

Malik,

Noman

et al. 2023

Second International Conference on Sustainable Technology and Management (ICSTM 2023)

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Enhancing Sustainable User Experience through Multimedia Integration: A Study on Interactive Design and User Engagement in Web Pages. As multimedia becomes increasingly popular on the Internet, the incorporation of animation, video, and audio alongside traditional text and image media presents new opportunities to promote sustainability. This paper delves into the sustainable integration of multimedia technologies in web pages, aiming to introduce their design and evaluate their impact on user experience, particularly in terms of interactivity. Business professionals seeking sustainable practices are increasingly interested in content that not only engages but also aligns with their environmentally conscious target audience. Hence, this study explores the motivation mechanics of sustainable consumer behaviour while assessing the perceived sustainability of emerging multimedia services. By understanding sustainable consumer participation in multimedia content, the research aims to inspire and improve sustainable interactive design for web pages. Through extensive analysis, the paper reveals valuable insights into the influence of sustainable multimedia design on user engagement and satisfaction. The findings highlight that integrating sustainable multimedia elements into web pages can significantly enhance the overall user experience and improve the effectiveness of online communication. This study advocates for the strategic incorporation of sustainable multimedia in web design to create easily understandable and visually appealing content that resonates with sustainability-conscious users.

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“…These modern systems have enabled individuals, organizations and connected objects to produce and publish huge amounts of data to the web through web application interfaces (APIs) and public endpoints. This development has enabled users to communicate, receive and share data [1,2]. The Internet of Things (IoT), for example, is an emerging technology that represents an innovative solution allowing the connection of billions of physical devices in the digital world using various networks with heterogeneous objects [3,4].…”

Section: Introductionmentioning

confidence: 99%

Information Management under uncertain large-scale cloud environment

OMRI

Omri

Benslimane

et al. 2022

Preprint

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“Uncertainty” is related to working with inaccurate data, imprecise and incomplete information, and unreliable results that can lead to irrational decisions. Several approaches to managing uncertain data on the web have been proposed in the literature to resolve this problem. These approaches have failed to find the solution to this problem with accuracy and performance. Our study aims to propose a new probabilistic approach to manage web information resources in an uncertain large-scale cloud environment. Our approach is based on three main steps: (1) modeling uncertain web resources, (2) computing HTTP request model, and (3) interpretation and evaluation of uncertain web resources in a context of classic hypertext navigation. The experimental study shows that the analysis of the execution time necessary for the composition of the services, by our approach, is negligible, compared to that of the other studied approaches. The algorithm which deals with the impact of the variation in the number of nodes, which we have proposed, has also been evaluated and checks all the possibilities in polynomial time and can adapt to many possibilities of multiplexing of values.

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Formal techniques for consistency checking of orchestrations of semantic Web services

Cited by 14 publications

References 11 publications

Semantic Analysis of Urdu English Tweets Empowered by Machine Learning

Semantic Analysis of Urdu English Tweets Empowered by Machine Learning

Enhancing sustainability in web design: a comparative exploration of multimedia systems and technology management

Information Management under uncertain large-scale cloud environment

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