Archives
:: International Transaction Journal of Engineering, Management, & Applied Sciences & Technologies
http://TuEngr.com
ISSN 2228-9860
eISSN 1906-9642
CODEN: ITJEA8
FEATURE PEER-REVIEWED ARTICLE
Vol.13(4)(2022) |
AI-Feature: A Software for Automatic Extraction of Features Attributes from Social Medial Texts Using AI Services
Fahim K Sufi (Federal Government, Melbourne, AUSTRALIA),
Musleh AlSulami (Umm Al-Qura University, Makkah, Makkah, SAUDI ARABIA).
Disciplinary: Artificial Intelligence.
doi: 10.14456/ITJEMAST.2022.69
Keywords: Automated Feature Extraction, Sentiment Analysis, Named Entity Recognition, Category Classification, Feature Attribute Generation, Preprocessing for AI Algorithm
AbstractAI-Feature uses artificial intelligence (AI) based services like entity detection, sentiment analysis and category classification to generate an elaborate set of feature attributes that can be further analyzed by Artificial Intelligence (AI) or Machine Learning (ML) based algorithms for producing deep intelligence and insights. A data scientist, data engineer or data analyst can use AI-Feature for pre-processing text input from social media, websites, blog posts or any number of media messages, on which AI-based algorithms can operate seamlessly. AI-Feature makes the task of feature attribute extraction fully automated with Microsoft Power Automate.Paper ID: 13A4F
Cite this article:
Sufi, F.K. AlSulami, M. (2022). AI-Feature: A Software for Automatic Extraction of Features Attributes from Social Medial Texts Using AI Services. International Transaction Journal of Engineering, Management, & Applied Sciences & Technologies, 13(4), 13A4F, 1-8. http://TUENGR.COM/V13/13A4F.pdf DOI: 10.14456/ITJEMAST.2022.69
References
- F. K. Sufi and M. Alsulami, "Knowledge Discovery of Global Landslides Using Automated Machine Learning Algorithms," IEEE Access, vol. 9, pp. 131400-131419, 2021.
- F. Sufi and I. Khalil, "Diagnosis of cardiovascular abnormalities from compressed ECG: a data mining-based approach," IEEE transactions on information technology in biomedicine, vol. 15, no. 1, pp. 33-39, 2010.
- F. Sufi and I. Khalil, "A clustering based system for instant detection of cardiac abnormalities from compressed ECG," Expert Systems with Applications, vol. 38, no. 5, pp. 4705-4713, 2011.
- F. Sufi and I. Khalil, "Faster person identification using compressed ECG in time critical wireless telecardiology applications," Journal of Network and Computer Applications, vol. 34, no. 1, pp. 282-293, 2011.
- F. K. Sufi and M. Alsulami, "Automated Multidimensional Analysis of Global Events with Entity Detection, Sentiment Analysis and Anomaly Detection," IEEE Access, vol. 9, pp. 152449-152460, November 2021.
- F. K. Sufi, "AI-Landslide: Software for acquiring hidden insights from global landslide data using Artificial Intelligence," Software Impacts, vol. 10, no. 100177, 2001.
- E. Batbaatar and K. H. Ryu, "Ontology-Based Healthcare Named Entity Recognition from Twitter Messages Using a Recurrent Neural Network Approach," International Journal of Environmental Research and Public Health, vol. 16, no. 3628, 2019.
- D. Cameron, G. A. Smith, R. Daniulaityte, A. P. Sheth, D. Dave, L. Chen, G. Anand, R. Carlson, K. Z. Watkins and R. Falck, "PREDOSE: A Semantic Web Platform for Drug Abuse Epidemiology using Social Media," J Biomed Inform, vol. 46, no. 6, 2013.
- X. Chen, et al., "Mining Patients' Narratives in Social Media for Pharmacovigilance: Adverse Effects and Misuse of Methylphenidate," Frontiers in Pharmacology, vol. 9, no. 541, 2018.
- Microsoft Documentation, "Microsoft Power Automate," 2021. https://docs.microsoft.com/en-us/power-automate (Accessed August 2021).
- B. Pang, L. Lee and S. Vaithyanathan, "Thumbs up?: Sentiment classification using machine learning techniques," in Conf. Empirical Methods Natural Lang. Process., 2002.
- P. D. Turney, "Thumbs up or thumbs down?: Semantic orientation applied," in 40th Annu. Meeting, 2002.
- U. Naseem, I. Razzak, M. Khushi, P. W. Eklund and J. Kim, "COVIDSenti: A Large-Scale Benchmark Twitter," IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS, 2020.
- M. Ebrahimi, A. H. Yazdavar and A. Sheth, "Challenges of Sentiment Analysis for Dynamic Events," IEEE Intelligent Systems, vol. 32, no. 5, 2017.
- M. Documentation, "Category Classification Model," 2021. [Online]. Available: https://docs.microsoft.com/en-us/ai-builder/prebuilt-category-classification. (Accessed Oct 2021).
- T. Hong, J.-A. Choi, K. Lim and P. Kim, "Enhancing Personalized Ads Using Interest Category Classification of SNS Users Based on Deep Neural Networks," Sensors, vol. 21, no. 199, 2021.
- F. Sufi, "AI-Feature: GitHub Source Files," 2021. https://github.com/DrSufi/DisasterAI (Accessed Oct 2021).
- F. K. Sufi, "Analyzing Natural Disaster related Tweets with AI and NLP based Services," IEEE Dataport. DOI: 10.21227/p0ed-cb23, 2021.
- F. K. Sufi, "AI-based Automated Extraction of Entities, Entity Categories and Sentiments on COVID-19 Situation," IEEE Dataport, no. DOI: 10.21227/sawp-ax73, 2021.
Other issues:
Vol.13(3)(2022)
Vol.13(2)(2022)
Vol.13(1)(2022)
Archives
Call-for-Papers
Call-for-Scientific PapersCall-for-Research Papers: ITJEMAST invites you to submit high quality papers for full peer-review and possible publication in areas pertaining engineering, science, management and technology, especially interdisciplinary/cross-disciplinary/multidisciplinary subjects.
To publish your work in the next available issue, your manuscripts together with copyright transfer document signed by all authors can be submitted via email to Editor @ TuEngr.com (no space between). (please see all detail from Instructions for Authors)
Publication and peer-reviewed process:
After the peer-review process, articles will be on-line published in the available next issue. However, the International Transaction Journal of Engineering, Management, & Applied Sciences & Technologies cannot guarantee the exact publication time as the process may take longer time, subject to peer-review approval and adjustment of the submitted articles.