Academic Journal
Challenges And Opportunities In Analytic-Predictive Environments Of Big Data And Natural Language Processing For Social Network Rating Systems
| العنوان: | Challenges And Opportunities In Analytic-Predictive Environments Of Big Data And Natural Language Processing For Social Network Rating Systems |
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| المؤلفون: | Jiménez Martín, José Luis, González Carrasco, Israel, López Cuadrado, José Luis |
| بيانات النشر: | IEEE |
| سنة النشر: | 2018 |
| المجموعة: | Universidad Carlos III de Madrid: e-Archivo |
| مصطلحات موضوعية: | Big data analytics, Big data predictive, Natural language processing, Social network rating systems, Informática |
| الوصف: | Social Media is playing a key role in today's society. Many of the events that are taking place in diverse human activities could be explained by the study of these data. Big Data is a relatively new parading in Computer Science that is gaining increasing interest by the scientific community. Big Data Predictive Analytics is a Big Data discipline that is mostly used to analyze what is in the huge amounts of data and then perform predictions based on such analysis using advanced mathematics and computing techniques. The study of Social Media Data involves disciplines like Natural Language Processing, by the integration of this area to academic studies, useful findings have been achieved. Social Network Rating Systems are online platforms that allow users to know about goods and services, the way in how users review and rate their experience is a field of evolving research. This paper presents a deep investigation in the state of the art of these areas to discover and analyze the current status of the research that has been developed so far by academics of diverse background. |
| نوع الوثيقة: | article in journal/newspaper |
| اللغة: | English |
| تدمد: | 1548-0992 |
| Relation: | Jimenez Marquez, J. L., Gonzalez Carrasco, I., & Lopez Cuadrado, J. L. (2018). Challenges and opportunities in analytic-predictive environments of big data and natural language processing for social network rating systems. IEEE Latin America Transactions, 16(2), 592–597.; http://hdl.handle.net/10016/39550; https://doi.org/10.1109/TLA.2018.8327417; 592; 597; IEEE Latin America Transactions; 16; AR/0000021410 |
| DOI: | 10.1109/TLA.2018.8327417 |
| الاتاحة: | http://hdl.handle.net/10016/39550 https://doi.org/10.1109/TLA.2018.8327417 |
| Rights: | © Copyright 2018 IEEE - All rights reserved. ; open access |
| رقم الانضمام: | edsbas.1803E8B0 |
| قاعدة البيانات: | BASE |
| تدمد: | 15480992 |
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| DOI: | 10.1109/TLA.2018.8327417 |