"Challenges and future in deep learning for sentiment analysis: a comprehensive review and a proposed novel hybrid approach"

Artificial Intelligence Review, Journal Year: 2024, Volume and Issue: 57(3)

Published: Feb. 19, 2024

Abstract Social media is used to categorise products or services, but analysing vast comments time-consuming. Researchers use sentiment analysis via natural language processing, evaluating methods and results conventionally through literature reviews assessments. However, our approach diverges by offering a thorough analytical perspective with critical analysis, research findings, identified gaps, limitations, challenges future prospects specific deep learning-based in recent times. Furthermore, we provide in-depth investigation into categorizing prevalent data, pre-processing methods, text representations, learning models, applications. We conduct evaluation of advances architectures, assessing their pros cons. Additionally, offer meticulous methodologies, integrating insights on applied tools, strengths, weaknesses, performance results, detailed feature-based examination. present discussion the challenges, drawbacks, factors contributing successful enhancement accuracy within realm analysis. A comparative article clearly shows that capsule-based RNN approaches give best an 98.02% which CNN RNN-based models. implemented various advanced deep-learning models across four benchmarks identify top performers. introduced innovative CRDC (Capsule Deep Bi structured RNN) model, demonstrated superior compared other methods. Our proposed achieved remarkable different databases: IMDB (88.15%), Toxic (98.28%), CrowdFlower (92.34%), ER (95.48%). Hence, this method holds promise for automated potential deployment.

Language: Английский

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Customer profiling, segmentation, and sales prediction using AI in direct marketing

Neural Computing and Applications, Journal Year: 2023, Volume and Issue: 36(9), P. 4995 - 5005

Published: Dec. 23, 2023

Abstract In the current business environment, where customer is primary focus, effective communication between marketing and senior management vital for success. Effective profiling a cornerstone of strategic decision-making digital start-ups seeking sustainable growth satisfaction. This research investigates clustering customers based on recency, frequency, monetary (RFM) analysis employs validation metrics to derive optimal clusters. The K-means algorithm, coupled with Elbow method, Silhouette coefficient, Gap Statistics facilitates identification distinct segments. study unveils three clusters unique characteristics: new (Cluster A), best B), intermittent C). For platform-based Edutech start-ups, Cluster A underscores importance tailored learning content support, B emphasizes personalized incentives, C suggests re-engagement strategies. By understanding addressing diverse needs these clusters, can forge enduring connections, optimize engagement, fuel growth.

Language: Английский

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Machine learning applied to tourism: A systematic review

Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery, Journal Year: 2024, Volume and Issue: 14(5)

Published: July 4, 2024

Abstract The application of machine learning techniques in the field tourism is experiencing a remarkable growth, as they allow to propose efficient solutions problems present this sector, by means an intelligent analysis data their specific context. increase work requires exhaustive through quantitative approach research activity, contributing deeper understanding progress field. Thus, different approaches will be analyzed, such planning, forecasting, recommendation, prevention, and security, among others. As result analysis, other findings, greater impact supervised tourism, more specifically those based on neural networks, has been confirmed. results study would researchers not only have most up‐to‐date accurate overview but also identify appropriate apply domain interest, well similar with which compare own solutions. This article categorized under: Application Areas > Society Culture Technologies Machine Learning Business Industry

Language: Английский

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Hotel digital intelligence capability: dimension exploration and scale development

Journal of Hospitality and Tourism Technology, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 15, 2025

Purpose This study aims to explore the dimensional structure of hotel digital intelligence capability and develop a measurement scale. Design/methodology/approach adopts qualitative quantitative approaches conduct an exploratory inquiry into structural dimensions with help grounded theory. Based on this, several questionnaires were developed test scale verify its validity. Findings The results reveal that comprises four dimensions: data collection processing capability, customer service personalization decision support sustainable development capability. consists factors 13 items, reliability validity tests demonstrating ideal levels. Originality/value not only provides new perspective understand but also develops corresponding scale, laying solid theoretical basis for managers scientifically evaluate this achieve competitive advantage.

Language: Английский

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Mining online hotel reviews using big data and machine learning: An empirical study from an emerging country

Annals of Tourism Research Empirical Insights, Journal Year: 2025, Volume and Issue: 6(1), P. 100170 - 100170

Published: March 6, 2025

Language: Английский

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Emotions Matter: A Systematic Review and Meta-Analysis of the Detection and Classification of Students’ Emotions in STEM during Online Learning

Education Sciences, Journal Year: 2023, Volume and Issue: 13(9), P. 914 - 914

Published: Sept. 8, 2023

In recent years, the rapid growth of online learning has highlighted need for effective methods to monitor and improve student experiences. Emotions play a crucial role in shaping students’ engagement, motivation, satisfaction environments, particularly complex STEM subjects. this context, sentiment analysis emerged as promising tool detect classify emotions expressed textual visual forms. This study offers an extensive literature review using preferred reporting items systematic reviews meta-analyses (PRISMA) technique on The analyses applicability, challenges, limitations text- facial-based techniques educational settings by reviewing 57 peer-reviewed research articles out 236 articles, published between 2015 2023, initially identified through comprehensive search strategy. Through scrutiny process, these were selected based their relevance contribution topic. review’s findings indicate that holds significant potential improving experiences, encouraging personalised learning, promoting environment. Educators administrators can gain valuable insights into perceptions employing computational analyse interpret text facial expressions. However, also identifies several challenges associated with settings. These include accurate emotion detection interpretation, addressing cultural linguistic variations, ensuring data privacy ethics, reliance high-quality sources. Despite highlights immense transforming experiences subjects recommends further development area.

Language: Английский

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Retail Industry Analytics: Unraveling Consumer Behavior through RFM Segmentation and Machine Learning

Published: May 30, 2024

Language: Английский

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Sociodemographic relationships of motivations, satisfaction, and loyalty in religious tourism: A study of the pilgrimage to the city Mecca

PLoS ONE, Journal Year: 2023, Volume and Issue: 18(3), P. e0283720 - e0283720

Published: March 30, 2023

Religious tourism is a growing sector of the market because many social and cultural changes in 21st century. Pilgrimage centers worldwide are considered important at levels religion, heritage, culture tourism. Despite popularity journeys to pilgrimage their global importance, there still lack knowledge about dimensionality impact socio-demographic factors on visiting these centers. This study aims (i) establish motivational dimensions Mecca (ii) identify relationship between aspects pilgrims motivation (iii) determine pilgrims, satisfaction, loyalty. The research was carried out who had visited Mecca. sample consisted 384 online surveys. Factor analysis multiple regression method were applied analyze data. results show three dimensions: religious, social, cultural, shopping. Additionally, evidence age, marital status average daily expenditure per person with some variables. Similarly, found other variables such as satisfaction helps companies pay attention pilgrims' characteristics match them motivation, loyalty during planning process.

Language: Английский

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Deep Learning for Table Detection and Structure Recognition: A Survey

ACM Computing Surveys, Journal Year: 2024, Volume and Issue: 56(12), P. 1 - 41

Published: April 10, 2024

Tables are everywhere, from scientific journals, articles, websites, and newspapers all the way to items we buy at supermarket. Detecting them is thus of utmost importance automatically understanding content a document. The performance table detection has substantially increased thanks rapid development deep learning networks. goals this survey provide profound comprehension major developments in field Table Detection, offer insight into different methodologies, systematic taxonomy approaches. Furthermore, an analysis both classic new applications field. Lastly, datasets source code existing models organized reader with compass on vast literature. Finally, go over architecture utilizing various object structure recognition methods create effective efficient system, as well set trends keep up state-of-the-art algorithms future research. We have also public GitHub repository where will be updating most recent publications, open data, code. available https://github.com/abdoelsayed2016/table-detection-structure-recognition.

Language: Английский

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A method for exploring consumer satisfaction factors using online reviews: A study on anti-cold drugs

Journal of Retailing and Consumer Services, Journal Year: 2024, Volume and Issue: 81, P. 103895 - 103895

Published: July 30, 2024

Language: Английский

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