What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Programming language
- Computer network
Minos Garofalakis mainly focuses on Data mining, Data stream mining, XML, Query optimization and Information retrieval.
His Data mining research incorporates themes from Tuple, Wavelet, Theoretical computer science and Data set.
His Wavelet research is multidisciplinary, incorporating perspectives in Scheme and Set.
His studies in Data stream mining integrate themes in fields like Middleware, Sample and World Wide Web.
His research on Query optimization also deals with topics like
- Query expansion together with Joins and Very large database,
- Active networking which connect with Distributed computing.
His research integrates issues of Efficient XML Interchange, XML database and XML schema in his study of XML validation.
His most cited work include:
- Approximate Query Processing Using Wavelets (489 citations)
- SPIRIT: Sequential Pattern Mining with Regular Expression Constraints (450 citations)
- Adaptive cleaning for RFID data streams (390 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of study are Data mining, Distributed computing, Data stream mining, Theoretical computer science and Probabilistic logic.
The study incorporates disciplines such as Lossy compression, Data set, Wavelet and Artificial intelligence in addition to Data mining.
His Distributed computing research includes themes of Network topology, Scheduling, Computer network and Fair-share scheduling.
His study in Data stream mining is interdisciplinary in nature, drawing from both Sketch, Data stream, Task and Big data.
His work deals with themes such as Set, Tree, Construct, XML and Query optimization, which intersect with Theoretical computer science.
Minos Garofalakis interconnects Probabilistic database, Graphical model, Uncertain data and Tuple in the investigation of issues within Probabilistic logic.
He most often published in these fields:
- Data mining (28.21%)
- Distributed computing (20.51%)
- Data stream mining (20.09%)
What were the highlights of his more recent work (between 2014-2020)?
- Data stream mining (20.09%)
- Distributed computing (20.51%)
- Big data (6.84%)
In recent papers he was focusing on the following fields of study:
His primary areas of investigation include Data stream mining, Distributed computing, Big data, Complex event processing and Analytics.
Minos Garofalakis interconnects Process, Scalability, Theoretical computer science, Sketch and Real-time computing in the investigation of issues within Data stream mining.
His Theoretical computer science research is multidisciplinary, relying on both XML, String and Mathematical optimization.
His Distributed computing study incorporates themes from Domain and STREAMS.
His studies in Automatic summarization integrate themes in fields like Structure and Data mining.
Minos Garofalakis combines subjects such as Data modeling and Database with his study of Data mining.
Between 2014 and 2020, his most popular works were:
- Issues in complex event processing (62 citations)
- Practical Private Range Search Revisited (61 citations)
- Data Stream Management – Processing High-Speed Data Streams (35 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Programming language
- Computer network
Minos Garofalakis focuses on Complex event processing, Data stream mining, Big data, Data science and Data stream.
His Complex event processing study which covers Analytics that intersects with Graph, Network topology, Predictive analytics and Scalability.
Data stream mining is a subfield of Data mining that Minos Garofalakis investigates.
His Big data study also includes fields such as
- Event together with Query optimization,
- Identification and related Event recognition, State, Pipeline and Variety.
In his work, Distributed computing is strongly intertwined with Real-time computing, which is a subfield of Data stream.
His Distributed computing research incorporates themes from Telecommunications network, Norm, Sketch and Joins.
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