What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- World War II
- Statistics
The scientist’s investigation covers issues in Data mining, Relational database, Information retrieval, World Wide Web and Web navigation.
Mark Levene mostly deals with Association rule learning in his studies of Data mining.
His Association rule learning research includes elements of Time complexity and Estimator.
His Relational database study combines topics from a wide range of disciplines, such as Data modeling, Theoretical computer science, Data model, Algorithm and Data integrity.
His Information retrieval research is multidisciplinary, relying on both Rank and Set.
His Web navigation research is multidisciplinary, incorporating elements of Discrete mathematics, Multimedia, Markov chain, Web mining and Calculus.
His most cited work include:
- Comparing university rankings (217 citations)
- Data Mining of User Navigation Patterns (189 citations)
- Methods for comparing rankings of search engine results (148 citations)
What are the main themes of his work throughout his whole career to date?
Mark Levene focuses on Information retrieval, World Wide Web, Theoretical computer science, Artificial intelligence and Relational database.
His Information retrieval study frequently draws parallels with other fields, such as Ranking.
His World Wide Web study frequently links to other fields, such as Multimedia.
His research in Artificial intelligence intersects with topics in Machine learning, Suffix tree and Natural language processing.
As a part of the same scientific family, he mostly works in the field of Relational database, focusing on Algorithm and, on occasion, Functional dependency.
The study incorporates disciplines such as Data mining, Web mining and Markov chain in addition to Web navigation.
He most often published in these fields:
- Information retrieval (14.12%)
- World Wide Web (13.54%)
- Theoretical computer science (11.24%)
What were the highlights of his more recent work (between 2014-2021)?
- Human dynamics (4.32%)
- Econometrics (4.03%)
- Statistical model (3.75%)
In recent papers he was focusing on the following fields of study:
His primary areas of study are Human dynamics, Econometrics, Statistical model, Artificial intelligence and Generative model.
His study on Human dynamics also encompasses disciplines like
- Stochastic process together with Survival function, Range and Set,
- Data set which intersects with area such as Mixture model and Exponential function.
His Artificial intelligence study integrates concerns from other disciplines, such as Machine learning and Natural language processing.
His Data science research is multidisciplinary, incorporating elements of World Wide Web and Set.
His research investigates the connection between World Wide Web and topics such as Language model that intersect with problems in Domain.
His Domain knowledge research incorporates themes from Ranking and Information retrieval.
Between 2014 and 2021, his most popular works were:
- A novel bibliometric index with a simple geometric interpretation. (25 citations)
- Estimating the number of clusters using diversity (16 citations)
- The hw-rank: an h-index variant for ranking web pages (11 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- World War II
- Statistics
His primary areas of investigation include Generative model, Human dynamics, Econometrics, Statistical model and Theoretical computer science.
Mark Levene has included themes like Sentiment analysis and Test in his Econometrics study.
The concepts of his Statistical model study are interwoven with issues in General election, Empirical evidence, Multiplicative function, Weibull distribution and Interpretation.
He integrates many fields, such as Theoretical computer science and Function, in his works.
His study focuses on the intersection of Survival function and fields such as Reliability with connections in the field of Set.
His Artificial intelligence research includes elements of Cognitive psychology, Phenomenon and Categorical variable.
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