H-Index & Metrics Best Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science D-index 88 Citations 33,382 433 World Ranking 288 National Ranking 175

Research.com Recognitions

Awards & Achievements

1997 - IEEE Fellow For contributions to the theory and practice of neural networks.

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Machine learning
  • The Internet

His main research concerns Artificial intelligence, Information retrieval, World Wide Web, Artificial neural network and Machine learning. His biological study spans a wide range of topics, including Natural language processing and Pattern recognition. His study connects Citation and Information retrieval.

His work on Search engine, Web development, Web standards and Web analytics as part of general World Wide Web research is frequently linked to Scientific literature, thereby connecting diverse disciplines of science. The various areas that C. Lee Giles examines in his Search engine study include Web page, Focused crawler and Index. His Artificial neural network study deals with Finite-state machine intersecting with Connectionism.

His most cited work include:

  • Accessibility of information on the web (1215 citations)
  • Searching the World Wide Web (933 citations)
  • Efficient identification of Web communities (732 citations)

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

The scientist’s investigation covers issues in Information retrieval, Artificial intelligence, World Wide Web, Search engine and Machine learning. His Information retrieval study incorporates themes from Metadata and Data mining. His studies in Artificial intelligence integrate themes in fields like Pattern recognition and Natural language processing.

His World Wide Web study frequently draws connections between related disciplines such as Data science. His Search engine study frequently involves adjacent topics like Web page. His research in Recurrent neural network intersects with topics in Finite-state machine and Time delay neural network.

He most often published in these fields:

  • Information retrieval (36.12%)
  • Artificial intelligence (28.86%)
  • World Wide Web (23.05%)

What were the highlights of his more recent work (between 2015-2021)?

  • Artificial intelligence (28.86%)
  • Information retrieval (36.12%)
  • Machine learning (12.16%)

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

His primary scientific interests are in Artificial intelligence, Information retrieval, Machine learning, Recurrent neural network and Task. C. Lee Giles interconnects Pattern recognition and Natural language processing in the investigation of issues within Artificial intelligence. C. Lee Giles focuses mostly in the field of Information retrieval, narrowing it down to topics relating to Metadata and, in certain cases, Big data.

His studies in Big data integrate themes in fields like Scalability and World Wide Web. C. Lee Giles has included themes like Adversarial system, Neural coding and Robustness in his Machine learning study. His research on Recurrent neural network concerns the broader Artificial neural network.

Between 2015 and 2021, his most popular works were:

  • Learning to read irregular text with attention mechanisms (98 citations)
  • Adversary Resistant Deep Neural Networks with an Application to Malware Detection (88 citations)
  • Learning to Extract Semantic Structure from Documents Using Multimodal Fully Convolutional Neural Networks (79 citations)

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

  • Artificial intelligence
  • Machine learning
  • The Internet

His primary areas of investigation include Artificial intelligence, Machine learning, Recurrent neural network, Pattern recognition and Adversarial system. His work carried out in the field of Artificial intelligence brings together such families of science as Task and Natural language processing. His Machine learning study integrates concerns from other disciplines, such as Concept map, Identification and Knowledge graph.

His study in Pattern recognition is interdisciplinary in nature, drawing from both Graph and Text detection. C. Lee Giles combines subjects such as Artificial neural network, Deep neural networks, Regularization and Robustness with his study of Adversarial system. Construct and Information retrieval are two areas of study in which C. Lee Giles engages in interdisciplinary research.

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.

Best Publications

Accessibility of information on the Web

Steve Lawrence;C. Lee Giles.
Intelligence (2000)

2673 Citations

Searching the World Wide Web

Steve Lawrence;C. Lee Giles.
Science (1998)

1722 Citations

Efficient identification of Web communities

Gary William Flake;Steve Lawrence;C. Lee Giles.
knowledge discovery and data mining (2000)

1194 Citations

Digital libraries and autonomous citation indexing

S. Lawrence;C. Lee Giles;K. Bollacker.
IEEE Computer (1999)

1032 Citations

Focused Crawling Using Context Graphs

Michelangelo Diligenti;Frans Coetzee;Steve Lawrence;C. Lee Giles.
very large data bases (2000)

945 Citations

CiteSeer: an automatic citation indexing system

C. Lee Giles;Kurt D. Bollacker;Steve Lawrence.
acm international conference on digital libraries (1998)

918 Citations

Learning, invariance, and generalization in high-order neural networks

C. Lee Giles;Tom Maxwell.
Applied Optics (1987)

874 Citations

Overfitting in Neural Nets: Backpropagation, Conjugate Gradient, and Early Stopping

Rich Caruana;Steve Lawrence;C. Lee Giles.
neural information processing systems (2000)

798 Citations

Collaborative filtering by personality diagnosis: a hybrid memory- and model-based approach

David M. Pennock;Eric Horvitz;Steve Lawrence;C. Lee Giles.
uncertainty in artificial intelligence (2000)

704 Citations

Winners don't take all: Characterizing the competition for links on the web

David M. Pennock;Gary William Flake;Steve Lawrence;Eric J. Glover.
Proceedings of the National Academy of Sciences of the United States of America (2002)

626 Citations

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