Ontological Based Approach of Integrating Big Data: Issues and Prospects

Ahmed, Jeelani; Ahmed, Muqeem

doi:10.1007/978-981-15-1420-3_38

Cited by 3 publications

(2 citation statements)

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“…The use of semantic technologies in the new digital marketing era is one of the approaches outstanding given their usefulness in decision making [30,31], data analysis [32][33][34], data integration [35][36][37], and knowledge extraction [38,39]. In decision making, semantic technologies provided the support for data integration with reasoning methods for efficiently querying the knowledge base, strategies to separate the relevant dimensions (technical, financial, political), and means to communicate the comprehensible decision options to stakeholders [30].…”

Section: Political Marketingmentioning

confidence: 99%

“…People refers to technical skills to manage and understand the management of the big data technologies; process is related to all actions, from data acquisition to reflection or visualization, performed in the technological and business environments; and, finally, technology is about the several techniques and technologies for collecting, storing, processing, and analyzing the data. In recent years, the challenges associated to big data analysis have increased due to a variety of reasons including the difficulty of managing such amount of data with traditional data processing applications, the variability of data sources, and the complexity of reusing application systems [37]. Semantic web technologies provide an easier way to search, reuse, combine, and share information, which brings added value and benefits helping to counter the challenges of big data [33].…”

Section: Political Marketingmentioning

confidence: 99%

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Integroly: Automatic Knowledge Graph Population from Social Big Data in the Political Marketing Domain

Guedea-Noriega

García‐Sánchez

2022

Applied Sciences

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Social media sites have become platforms for conversation and channels to share experiences and opinions, promoting public discourse. In particular, their use has increased in political topics, such as citizen participation, proselytism, or political discussions. Political marketing involves collecting, monitoring, processing, and analyzing large amounts of voters’ data. However, the extraction, integration, processing, and storage of these torrents of relevant data in the political domain is a very challenging endeavor. In the recent years, the semantic technologies as ontologies and knowledge graphs (KGs) have proven effective in supporting knowledge extraction and management, providing solutions in heterogeneous data sources integration and the complexity of finding meaningful relationships. This work focuses on providing an automated solution for the population of a political marketing-related KG from Spanish texts through Natural Language Processing (NLP) techniques. The aim of the proposed framework is to gather significant data from semi-structured and unstructured digital media sources to feed a KG previously defined sustained by an ontological model in the political marketing domain. Twitter and political news sites were used to test the usefulness of the automatic KG population approach. The resulting KG was evaluated through 18 quality requirements, which ensure the optimal integration of political knowledge.

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Section: Political Marketingmentioning

confidence: 99%

Section: Political Marketingmentioning

confidence: 99%

Integroly: Automatic Knowledge Graph Population from Social Big Data in the Political Marketing Domain

Guedea-Noriega

García‐Sánchez

2022

Applied Sciences

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The role of Artificial Intelligence in Education: Current Trends and Future Prospects

Yousuf

Wahid

2021

2021 International Conference on Information Science and Communications Technologies (ICISCT)

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A Study on E-Learning and Recommendation System

Madhavi¹,

Nagesh²,

Govardhan

2022

RACSC

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Introduction: Today’s technology and the internet are proliferating due to which information access is becoming easier for many people, and creating new challenges and opportunities in all fields, especially when working with education. For example, the e-learning education system can personalized in order to acquire knowledge level and learner’s requirements in a learning process. The learning experience, as per the individual learner’s goals, should be adopted. Background: In the current educational environment, e-learning is playing a significant role. For many researchers, it has become one of the most important subjects, as using e-learning whole education system would revolutionize. There are many areas of e-learning in which research work is going on, such as Mass Communication, Information and Technology (IT), Education and Distance Education. Objective: To meet the various needs of the learners such as talents, interests, goals and needs, an e-learning system has to design a personalized learning system by considering various educational experiences. Many methods such as ontologies, clustering, classification and association rules have used along with filtering techniques to enhance the personalization and performance of the learner. Methods: This paper presents a detailed review of literature of previous work that has done in e-learning area especially on recommendation system. Current research works on e-learning to discover the research developments in this discipline have discussed in this work. Conclusion: One of the vital functions of the current e-learning system is creating a personalized resource recommendation system. In this paper, we reviewed some crucial papers on both e-learning and recommendation systems. Future research work of this paper would be designing efficient and precise e-learning and recommendation system to deal with the problem of substantial personalized information resources and further e-Learning plays vital role in preventing virus spread during COVID-19 pandemic.

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Ontological Based Approach of Integrating Big Data: Issues and Prospects

Cited by 3 publications

References 20 publications

Integroly: Automatic Knowledge Graph Population from Social Big Data in the Political Marketing Domain

Integroly: Automatic Knowledge Graph Population from Social Big Data in the Political Marketing Domain

The role of Artificial Intelligence in Education: Current Trends and Future Prospects

A Study on E-Learning and Recommendation System

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