Most companies use social media data for business. Sentiment analysis automatically gathers analyses and summarizes this type of data. Managing unstructured social media data is difficult. Noisy data is a challenge to sentiment analysis. Since over 50% of the sentiment analysis process is data pre-processing, processing big social media data is challenging too. If pre-processing is carried out correctly, data accuracy may improve. Also, sentiment analysis workflow is highly dependent. Because no pre-processing technique works well in all situations or with all data sources, choosing the most important ones is crucial. Prioritization is an excellent technique for choosing the most important ones. As one of many Multi-Criteria Decision Making (MCDM) methods, the Analytic Hierarchy Process (AHP) is preferred for handling complicated decision-making challenges using several criteria. The Consistency Ratio (CR) scores were used to examine pair-wise comparisons to evaluate the AHP. This study used two judgment scales to get the most consistent judgment. Firstly, the Saaty judgment scale (SS), then the Generalized Balanced Scale (GBS). It investigated whether two different AHP judgment scales would affect decision-making. The main criteria for prioritizing pre-processing techniques in sentiment analysis are Punctuation, Spelling, Number, and Context. These four criteria also contain sub-criteria. GBS pair-wise comparisons are closer to the CR value than SS, reducing the alternatives’ weight ratios. This paper explains how AHP aids logical decision-making. Prioritizing pre-processing techniques with AHP can be a paradigm for other sentiment analysis stages. In short, this paper adds another contribution to the Big Data Analytics domain.
The research talks about the interest and its impact on polygamy as a legitimate social psychological issue, where she talked about the concept of polygamy, and evidence of the legitimacy of polygamy, and clarify the conditions, and then touched on the great interests for which the law allowed polygamy, and mentioned some practical models in polygamy, including What is in the interest of men in pluralism, including in the interest of women in pluralism, including in the interests of both sexes in pluralism .
In this paper we show that if ? Xi is monotonically T2-space then each Xi is monotonically T2-space, too. Moreover, we show that if ? Xi is monotonically normal space then each Xi is monotonically normal space, too. Among these results we give a new proof to show that the monotonically T2-space property and monotonically normal space property are hereditary property and topologically property and give an example of T2-space but not monotonically T2-space.
A disagreement has arisen among scholars regarding the ruling on historical statues and monuments in Muslim countries, especially after the Taliban blew up some huge historical statues, and we have witnessed different positions that reach the point of contradiction, each claiming to be right, and now that the crisis has passed and the intensity of the dispute has subsided, I see It is appropriate to discuss this issue calmly, without drifting behind this or that party, to find out the legal position on these statues and monuments.
I presented the most prominent modern opinions related to the subject and discussed them in this research, which I called (Sharia’s position on historical statues and monuments), in which I tried to reach
This study aims to enhance the RC5 algorithm to improve encryption and decryption speeds in devices with limited power and memory resources. These resource-constrained applications, which range in size from wearables and smart cards to microscopic sensors, frequently function in settings where traditional cryptographic techniques because of their high computational overhead and memory requirements are impracticable. The Enhanced RC5 (ERC5) algorithm integrates the PKCS#7 padding method to effectively adapt to various data sizes. Empirical investigation reveals significant improvements in encryption speed with ERC5, ranging from 50.90% to 64.18% for audio files and 46.97% to 56.84% for image files, depending on file size. A substanti
... Show MoreDust is a frequent contributor to health risks and changes in the climate, one of the most dangerous issues facing people today. Desertification, drought, agricultural practices, and sand and dust storms from neighboring regions bring on this issue. Deep learning (DL) long short-term memory (LSTM) based regression was a proposed solution to increase the forecasting accuracy of dust and monitoring. The proposed system has two parts to detect and monitor the dust; at the first step, the LSTM and dense layers are used to build a system using to detect the dust, while at the second step, the proposed Wireless Sensor Networks (WSN) and Internet of Things (IoT) model is used as a forecasting and monitoring model. The experiment DL system
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