What is he best known for?
The fields of study he is best known for:
- Database
- Artificial intelligence
- Programming language
His primary scientific interests are in Data quality, Data mining, Artificial intelligence, World Wide Web and Distributed computing.
His Data mining research incorporates themes from Data processing and Joins.
His Artificial intelligence research incorporates elements of Data modeling and Machine learning.
When carried out as part of a general World Wide Web research project, his work on Data Web is frequently linked to work in Manifesto, therefore connecting diverse disciplines of study.
His studies deal with areas such as Data processing system, Parallel processing, Parallel computing and Bloom filter as well as Distributed computing.
His research in Interface intersects with topics in Query language, Relational model, Data type and Set.
His most cited work include:
- Rayyan-a web and mobile app for systematic reviews. (1796 citations)
- NADEEF: a commodity data cleaning system (213 citations)
- Guided data repair (169 citations)
What are the main themes of his work throughout his whole career to date?
Mourad Ouzzani focuses on Data mining, Database, World Wide Web, Information retrieval and Data integration.
His work on Functional dependency as part of general Data mining study is frequently linked to Tuple and Data quality, therefore connecting diverse disciplines of science.
His Database study combines topics from a wide range of disciplines, such as Query expansion, Data structure and Data curation.
His work on Search engine indexing as part of general Information retrieval research is frequently linked to Web query classification, bridging the gap between disciplines.
He combines subjects such as Data management and Artificial intelligence with his study of Data integration.
In the subject of general Web service, his work in Web standards, Web development and Service-oriented architecture is often linked to Business, thereby combining diverse domains of study.
He most often published in these fields:
- Data mining (19.79%)
- Database (19.79%)
- World Wide Web (18.72%)
What were the highlights of his more recent work (between 2016-2021)?
- Artificial intelligence (10.70%)
- Scalability (9.63%)
- Data integration (12.30%)
In recent papers he was focusing on the following fields of study:
Mourad Ouzzani mainly focuses on Artificial intelligence, Scalability, Data integration, Data mining and Distributed computing.
His Artificial intelligence research is multidisciplinary, incorporating perspectives in Machine learning and Data management.
His studies in Data integration integrate themes in fields like Data warehouse and Data discovery.
His Data mining research includes themes of Disparate system, Data integrity and Key.
His biological study spans a wide range of topics, including Data retrieval, SPARQL, RDF and Query optimization.
His study explores the link between Deep learning and topics such as Data curation that cross with problems in Data structure, SQL, Database and Big data.
Between 2016 and 2021, his most popular works were:
- A service computing manifesto: the next 10 years (120 citations)
- Distributed representations of tuples for entity resolution (79 citations)
- The data civilizer system (78 citations)
In his most recent research, the most cited papers focused on:
- Database
- Artificial intelligence
- Programming language
The scientist’s investigation covers issues in Artificial intelligence, Tuple, Data integration, Machine learning and Feature engineering.
His Artificial intelligence research integrates issues from Natural language processing, String and Data editing.
Tuple is intertwined with Transfer of learning, Classifier and Feature vector in his study.
Data quality and Data virtualization are fields of study that overlap with his Data integration research.
His research integrates issues of Training set, Data mining, Data profiling, Functional dependency and Dirty data in his study of Machine learning.
His study looks at the relationship between Feature engineering and fields such as Word, as well as how they intersect with chemical problems.
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