Instance Genetic Selection for Fuzzy Rule-based Systems Optimization to Opinion Classification

Cerqueira, Tayane Leite; Bertoni, Fabiana Cristina; Pires, Matheus Giovanni

doi:10.1109/tla.2020.9099762

Cited by 12 publications

(2 citation statements)

References 18 publications

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“…Cerqueira et al [29] proposed the techniques for finding the news on the websites and reading it without the users among all. To perform this fuzzy systems are used to get the changes made on websites in real-time.…”

Section: Literature Surveymentioning

confidence: 99%

Web Information Extraction methods using Web Content Mining (WCM) for Webapplications

Raghavendra¹,

Niranjanamurthy²

2022

IJCDS

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In the digital world era, data was generated by humans and machines are huge in volume and have been accessed through websites on the internet platform. Most of the transactions happened on web product items, web news, and web advertisements. Web Information Extraction (WIE) is the technique where the information on websites is extracted accurately within a time using Web Content Mining (WCM) concept. Every second, new data has been generated in different locations and the contents of the websites have changed rapidly at various intervals during processing time. The live time and location of the data have changed each time when internet users processing web applications. So extracting the information from the web page or website is a challenging one with accuracy and latency on websites. Classic algorithms and data mining techniques are used to preprocess the generated data with a certain time but the validity of those has not been maintained on the web server. Perhaps, their special features have taken for doing extraction using web mining techniques. The recently advanced concepts such as Deep Learning with Recurrent Neural Networks (RNN) are used to perform Web Information Extraction on various websites over the large network by keeping hold of the data status at each second in memory while doing the processing. The technique Long Short-Term Memory (LSTM) is used to hold the status in intermediate memory then all generated data in web applications send this status to RNN for further classifications. Classification methods are used in Artificial Neural Networks (ANN), it would train the input data from the large network and segregate them based on the algorithms used by the user. Finally, the deep learning concept is combined with all recent trends with input models as an embedded layer. Social media information is up-to-date with its originality and validity also keeps track fully in larger networks by using this technique. This paper suggested the best methods to implement the web information extraction concepts in web content mining from different websites on larger clusters/networks using deep learning LSTM techniques.

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Section: Literature Surveymentioning

confidence: 99%

Web Information Extraction methods using Web Content Mining (WCM) for Webapplications

Raghavendra¹,

Niranjanamurthy²

2022

IJCDS

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“…The main motivation behind incorporating the Fuzzy set theory into the original AHP is based on the argument that human judgments and preferences cannot be accurately represented by crisp numbers due to the uncertainty inherent in human perception [55]. The Fuzzy set theory implements data classes with unclear limits, that is, fuzzy limits [56].…”

Section: Literature Reviewmentioning

confidence: 99%

Supplier Selection Risk: A New Computer-Based Decision-Making System with Fuzzy Extended AHP

2021

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Supplier risks have attracted significant attention in the supply chain risk management literature. In this article, we propose a new computational system based on the ‘Fuzzy Extended Analytic Hierarchy Process (FEAHP)’ method for supplier selection while considering the relevant risks. We sought to evaluate the opportunities and limitations of using the FEAHP method in supplier selection and analyzed the support of the system developed through the real case of a Brazilian oil and natural gas company. The computational approach based on FEAHP automates supplier selection by determining a hierarchy of criteria, sub-criteria, and alternatives. First, the criteria and sub-criteria specific to the selection problem were identified by the experts taking the relevant literature as a starting point. Next, the experts performed a pair-wise comparison of the predefined requirements using a linguistic scale. This evaluation was then quantified by calculating the priority weights of criteria, sub-criteria, and alternatives. The best decision alternative is the one with the highest final score. Sensitivity analysis was performed to verify the results of the proposed model. The FEAHP computer approach automated the supplier selection process in a rational, flexible, and agile way, as perceived by the focal company. From this, we hypothesized that using this system can provide helpful insights in choosing the best suppliers in an environment of risk and uncertainty, thereby maximizing supply chain performance.

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Optimal trained long short-term memory for opinion mining: a hybrid semantic knowledgebase approach

Menaga

Ambati²,

Bojja³

2022

Int J Intell Robot Appl

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Instance Genetic Selection for Fuzzy Rule-based Systems Optimization to Opinion Classification

Cited by 12 publications

References 18 publications

Web Information Extraction methods using Web Content Mining (WCM) for Webapplications

Web Information Extraction methods using Web Content Mining (WCM) for Webapplications

Supplier Selection Risk: A New Computer-Based Decision-Making System with Fuzzy Extended AHP

Optimal trained long short-term memory for opinion mining: a hybrid semantic knowledgebase approach

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