H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 35 Citations 6,479 165 World Ranking 6063 National Ranking 2895

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Machine learning
  • World Wide Web

His primary areas of investigation include Cluster analysis, Web mining, Personalization, World Wide Web and Artificial intelligence. His studies in Cluster analysis integrate themes in fields like Algorithm, Data mining and Fuzzy set, Fuzzy logic. His work carried out in the field of Data mining brings together such families of science as Field and Outlier.

His work deals with themes such as Web intelligence and Data Web, which intersect with Web mining. His Personalization study combines topics in areas such as Recommender system, Information retrieval, Collaborative filtering, Web server and User profile. His research integrates issues of Machine learning, Scalability and Pattern recognition in his study of Artificial intelligence.

His most cited work include:

  • Low-complexity fuzzy relational clustering algorithms for Web mining (311 citations)
  • Fuzzy and possibilistic shell clustering algorithms and their application to boundary detection and surface approximation. II (206 citations)
  • Mining search engine query logs for query recommendation (206 citations)

What are the main themes of his work throughout his whole career to date?

His primary scientific interests are in Artificial intelligence, Cluster analysis, Data mining, World Wide Web and Web mining. His Artificial intelligence research incorporates elements of Machine learning, Computer vision and Pattern recognition. His work in Cluster analysis tackles topics such as Algorithm which are related to areas like Determining the number of clusters in a data set and Pattern recognition.

When carried out as part of a general Data mining research project, his work on Data stream mining is frequently linked to work in Clickstream, therefore connecting diverse disciplines of study. The concepts of his Web mining study are interwoven with issues in Personalization, Web analytics, Knowledge extraction, Data science and Data Web. The Personalization study which covers Recommender system that intersects with Social media.

He most often published in these fields:

  • Artificial intelligence (34.50%)
  • Cluster analysis (33.00%)
  • Data mining (27.50%)

What were the highlights of his more recent work (between 2014-2021)?

  • Artificial intelligence (34.50%)
  • Recommender system (21.00%)
  • Machine learning (16.50%)

In recent papers he was focusing on the following fields of study:

His primary areas of study are Artificial intelligence, Recommender system, Machine learning, Collaborative filtering and Big data. Olfa Nasraoui interconnects Iterated function, Pattern recognition and Personalization in the investigation of issues within Artificial intelligence. Olfa Nasraoui has included themes like Social media, Educational data mining, Data mining and Open educational resources in his Recommender system study.

The various areas that Olfa Nasraoui examines in his Data mining study include Subnetwork and Information retrieval. The study incorporates disciplines such as Data set and Taxonomy in addition to Machine learning. The Big data study combines topics in areas such as World Wide Web, Learning object and Semantic Web.

Between 2014 and 2021, his most popular works were:

  • Deep Learning of Part-Based Representation of Data Using Sparse Autoencoders With Nonnegativity Constraints (123 citations)
  • Using Explainability for Constrained Matrix Factorization (41 citations)
  • Explainable Matrix Factorization for Collaborative Filtering (31 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Machine learning
  • World Wide Web

The scientist’s investigation covers issues in Artificial intelligence, Recommender system, Machine learning, Data mining and Collaborative filtering. His Artificial intelligence study combines topics from a wide range of disciplines, such as Iterated function and Transparency. His research in Recommender system intersects with topics in Learning object, Learning analytics, Learning Management, Educational data mining and Open educational resources.

His Machine learning research incorporates themes from Special case and Taxonomy. Olfa Nasraoui works mostly in the field of Data mining, limiting it down to topics relating to Interpretability and, in certain cases, Boltzmann machine. His Matrix decomposition research overlaps with other disciplines such as State, Information retrieval, Quality, Focus and Factorization.

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.

Top Publications

Automatic Recommendations for E-Learning Personalization Based on Web Usage Mining Techniques and Information Retrieval

Mohamed Koutheair Khribi;Mohamed Jemni;Olfa Nasraoui.
Educational Technology & Society (2009)

485 Citations

Low-complexity fuzzy relational clustering algorithms for Web mining

R. Krishnapuram;A. Joshi;O. Nasraoui;L. Yi.
IEEE Transactions on Fuzzy Systems (2001)

450 Citations

Fuzzy and possibilistic shell clustering algorithms and their application to boundary detection and surface approximation. II

R. Krishnapuram;H. Frigui;O. Nasraoui.
IEEE Transactions on Fuzzy Systems (1995)

295 Citations

Mining search engine query logs for query recommendation

Zhiyong Zhang;Olfa Nasraoui.
the web conference (2006)

280 Citations

A Web Usage Mining Framework for Mining Evolving User Profiles in Dynamic Web Sites

O. Nasraoui;M. Soliman;E. Saka;A. Badia.
IEEE Transactions on Knowledge and Data Engineering (2008)

270 Citations

Unsupervised learning of prototypes and attribute weights

Hichem Frigui;Olfa Nasraoui.
Pattern Recognition (2004)

268 Citations

The fuzzy c spherical shells algorithm: A new approach

R. Krishnapuram;O. Nasraoui;H. Frigui.
IEEE Transactions on Neural Networks (1992)

248 Citations

Deep Learning of Part-Based Representation of Data Using Sparse Autoencoders With Nonnegativity Constraints

Ehsan Hosseini-Asl;Jacek M. Zurada;Olfa Nasraoui.
IEEE Transactions on Neural Networks (2016)

170 Citations

EXTRACTING WEB USER PROFILES USING RELATIONAL COMPETITIVE FUZZY CLUSTERING

Olfa Nasraoui;Hichem Frigui;Raghu Krishnapuram;Anupam Joshi.
International Journal on Artificial Intelligence Tools (2000)

159 Citations

Advances in Web Mining and Web Usage Analysis

Haizheng Zhang;Myra Spiliopoulou;Bamshad Mobasher;C. Lee Giles.
(2008)

140 Citations

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking h-index is inferred from publications deemed to belong to the considered discipline.

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