What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Operating system
- Database
His primary areas of study are Data mining, Online analytical processing, Data cube, Data warehouse and Wireless sensor network.
The Data mining study combines topics in areas such as Semantics and Data compression.
His Online analytical processing research integrates issues from Data science, Data stream, Data structure, Privacy preserving and Big data.
His Big data research includes themes of Analytics and Cloud computing.
His research in Data cube intersects with topics in Scalability, Set and Data domain.
His work is dedicated to discovering how Data warehouse, Business intelligence are connected with Cluster analysis, k-means clustering, Competitive intelligence, Benchmark and Secure multi-party computation and other disciplines.
His most cited work include:
- Analytics over large-scale multidimensional data: the big data revolution! (249 citations)
- Big data: a research agenda (98 citations)
- Data warehousing and OLAP over big data: current challenges and future research directions (88 citations)
What are the main themes of his work throughout his whole career to date?
Alfredo Cuzzocrea mostly deals with Big data, Data mining, Data science, Online analytical processing and Data warehouse.
The study incorporates disciplines such as Context, World Wide Web, Variety, Artificial intelligence and Cloud computing in addition to Big data.
His work in Data mining tackles topics such as Wireless sensor network which are related to areas like Distributed computing.
His Data science study combines topics from a wide range of disciplines, such as Information privacy and Knowledge extraction.
His studies deal with areas such as Privacy preserving, Data cube and Benchmark as well as Online analytical processing.
His research on Data warehouse often connects related topics like Relational database.
He most often published in these fields:
- Big data (28.69%)
- Data mining (26.63%)
- Data science (26.80%)
What were the highlights of his more recent work (between 2016-2021)?
- Big data (28.69%)
- Data science (26.80%)
- Artificial intelligence (12.89%)
In recent papers he was focusing on the following fields of study:
His primary scientific interests are in Big data, Data science, Artificial intelligence, Machine learning and Context.
Alfredo Cuzzocrea has researched Big data in several fields, including Information privacy, Data warehouse, Online analytical processing, Variety and Cloud computing.
Alfredo Cuzzocrea regularly links together related areas like Data cube in his Online analytical processing studies.
His Data science research incorporates elements of Privacy preserving, Big data management and Data analysis.
His Artificial intelligence research is multidisciplinary, incorporating perspectives in Pattern recognition, Task and Natural language processing.
The concepts of his Machine learning study are interwoven with issues in Business process and Graph.
Between 2016 and 2021, his most popular works were:
- Fighting fake news spread in online social networks: Actual trends and future research directions (21 citations)
- Game Data Mining: Clustering and Visualization of Online Game Data in Cyber-Physical Worlds (19 citations)
- AI-Based Sensor Information Fusion for Supporting Deep Supervised Learning. (17 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Operating system
- Machine learning
Big data, Data science, Artificial intelligence, Machine learning and Variety are his primary areas of study.
His Big data study combines topics from a wide range of disciplines, such as Predictive analytics, Social network, Knowledge extraction, Uncertain data and Data analysis.
His study in the fields of Analytics under the domain of Data science overlaps with other disciplines such as Popularity.
His Artificial intelligence research is multidisciplinary, relying on both Algorithm and Phishing.
In his study, Conceptual architecture, Performance indicator, Robustness, Usability and Scalability is strongly linked to Business process, which falls under the umbrella field of Machine learning.
His work focuses on many connections between Variety and other disciplines, such as Volume, that overlap with his field of interest in Online analytical processing.
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