What is he best known for?
The fields of study he is best known for:
- Operating system
- Computer network
- The Internet
His primary scientific interests are in Data mining, Computer network, Distributed computing, Database and Cluster analysis.
His work on Data stream mining as part of general Data mining study is frequently linked to Space, bridging the gap between disciplines.
His Computer network research includes elements of Tree, Algorithm, Real-time computing and Internet protocol suite.
His Database study combines topics in areas such as File server and Outlier.
Rajeev Rastogi has researched Cluster analysis in several fields, including Similarity measure and Pattern recognition.
His k-medians clustering research incorporates elements of Data stream clustering, Categorical variable and Single-linkage clustering.
His most cited work include:
- CURE: an efficient clustering algorithm for large databases (1834 citations)
- Efficient algorithms for mining outliers from large data sets (1514 citations)
- ROCK: a robust clustering algorithm for categorical attributes (1206 citations)
What are the main themes of his work throughout his whole career to date?
The scientist’s investigation covers issues in Computer network, Data mining, Distributed computing, Database and Theoretical computer science.
His studies deal with areas such as Real-time computing and Mesh networking as well as Computer network.
While the research belongs to areas of Data mining, Rajeev Rastogi spends his time largely on the problem of Artificial intelligence, intersecting his research to questions surrounding Product.
His Distributed computing research focuses on subjects like Serializability, which are linked to Two-phase locking and Global serializability.
His biological study spans a wide range of topics, including Cluster analysis and Concurrency.
In Theoretical computer science, Rajeev Rastogi works on issues like Data stream mining, which are connected to Data stream.
He most often published in these fields:
- Computer network (24.35%)
- Data mining (21.40%)
- Distributed computing (16.24%)
What were the highlights of his more recent work (between 2007-2020)?
- Data mining (21.40%)
- Artificial intelligence (10.33%)
- Information retrieval (7.38%)
In recent papers he was focusing on the following fields of study:
His primary areas of investigation include Data mining, Artificial intelligence, Information retrieval, Computer network and Machine learning.
His Data mining study incorporates themes from Value, Structure, Theoretical computer science and Benchmark.
His Artificial intelligence study integrates concerns from other disciplines, such as Scheme, Logistic regression and Pattern recognition.
Rajeev Rastogi combines subjects such as Web page, Set, Printer-friendly, Cluster analysis and URL normalization with his study of Information retrieval.
His work investigates the relationship between Cluster analysis and topics such as Vertex that intersect with problems in Database and The Internet.
The Computer network study combines topics in areas such as Distributed computing, Greedy algorithm and Mesh networking.
Between 2007 and 2020, his most popular works were:
- Graph summarization with bounded error (261 citations)
- Recommendations to boost content spread in social networks (106 citations)
- Entity disambiguation with hierarchical topic models (89 citations)
In his most recent research, the most cited papers focused on:
- Operating system
- Computer network
- The Internet
His scientific interests lie mostly in Computer network, Data mining, Information retrieval, Theoretical computer science and Web page.
The Network topology research Rajeev Rastogi does as part of his general Computer network study is frequently linked to other disciplines of science, such as Directional antenna, therefore creating a link between diverse domains of science.
His work deals with themes such as Field and Presentation, which intersect with Data mining.
He interconnects Static web page, Semantic URL, URL normalization, Printer-friendly and World Wide Web in the investigation of issues within Information retrieval.
His research in Theoretical computer science intersects with topics in Quartic graph, Social network, Heuristics, Graph and Null graph.
His research investigates the connection between Web page and topics such as Information extraction that intersect with problems in Matching, Data model and Value.
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