What is he best known for?
The fields of study he is best known for:
- Operating system
- Database
- Statistics
His scientific interests lie mostly in Data mining, Scalability, Location-based service, Database and Database server.
Mohamed F. Mokbel combines subjects such as Spatial analysis, Search engine indexing, High-level programming language and Taxonomy with his study of Data mining.
The Scalability study combines topics in areas such as Database storage structures, Spatial database, Set, Temporal database and Big data.
His Set research integrates issues from Real-time computing and Theoretical computer science.
His studies deal with areas such as Computer security and Collaborative filtering, Recommender system, World Wide Web as well as Location-based service.
His Database study combines topics from a wide range of disciplines, such as Cloud computing, Undo and Anonymity.
His most cited work include:
- The new Casper: query processing for location services without compromising privacy (970 citations)
- Location-based and preference-aware recommendation using sparse geo-social networking data (535 citations)
- A peer-to-peer spatial cloaking algorithm for anonymous location-based service (435 citations)
What are the main themes of his work throughout his whole career to date?
Mohamed F. Mokbel spends much of his time researching Data mining, Database, Scalability, World Wide Web and Search engine indexing.
The concepts of his Data mining study are interwoven with issues in Grid, Overhead and Set.
The Database study combines topics in areas such as Information retrieval and Preference.
His studies in Scalability integrate themes in fields like Database server, Distributed computing, Location-based service, Temporal database and Server.
In the field of World Wide Web, his study on Recommender system, Social media and Microblogging overlaps with subjects such as Popularity.
His Search engine indexing research focuses on subjects like Visualization, which are linked to User interface.
He most often published in these fields:
- Data mining (27.16%)
- Database (23.05%)
- Scalability (21.40%)
What were the highlights of his more recent work (between 2016-2021)?
- Data mining (27.16%)
- Big data (7.41%)
- Search engine indexing (13.99%)
In recent papers he was focusing on the following fields of study:
The scientist’s investigation covers issues in Data mining, Big data, Search engine indexing, Database and Spatial analysis.
His study in Data mining is interdisciplinary in nature, drawing from both Probabilistic logic, Scalability, Process and Set.
His Big data study also includes fields such as
- Tree that connect with fields like Tuple and Data modeling,
- Cluster analysis that connect with fields like Information space, Online transaction processing and Mobile computing,
- Analytics that intertwine with fields like Computer security and Telecommunications service.
His research integrates issues of Visualization, Temporal database and Key in his study of Search engine indexing.
He is involved in the study of Database that focuses on SQL in particular.
His Spatial analysis research is multidisciplinary, incorporating elements of Range query, Data structure, Data science and Markov chain.
Between 2016 and 2021, his most popular works were:
- ST-Hadoop: a MapReduce framework for spatio-temporal data (30 citations)
- Spatial coding-based approach for partitioning big spatial data in Hadoop (18 citations)
- Parallel Processing over Spatial-Temporal Datasets from Geo, Bio, Climate and Social Science Communities: A Research Roadmap (15 citations)
In his most recent research, the most cited papers focused on:
- Operating system
- Database
- Statistics
His primary scientific interests are in Data mining, Spatial analysis, Search engine indexing, Distributed File System and Database.
His Data mining study frequently links to related topics such as Set.
To a larger extent, Mohamed F. Mokbel studies World Wide Web with the aim of understanding Search engine indexing.
Mohamed F. Mokbel has included themes like Information retrieval and Database design in his World Wide Web study.
The study incorporates disciplines such as Space partitioning, Block, Spatial database, Temporal database and Key in addition to Distributed File System.
His work on Database engine as part of his general Database study is frequently connected to Database search engine, thereby bridging the divide between different branches of science.
This overview was generated by a machine learning system which analysed the scientist’s
body of work. If you have any feedback, you can
contact us
here.
