D-Index & Metrics Best Publications

D-Index & Metrics D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines.

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Computer Science D-index 39 Citations 8,391 215 World Ranking 6015 National Ranking 141

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Statistics
  • Machine learning

Eric Gaussier focuses on Artificial intelligence, Natural language processing, Information retrieval, Word and Speech recognition. His research integrates issues of Term, Relation and Pattern recognition in his study of Artificial intelligence. His Natural language processing study combines topics from a wide range of disciplines, such as Linguistics and Cluster analysis.

His Information retrieval study incorporates themes from Deep linguistic processing, Terminology extraction, Set and Index. Eric Gaussier focuses mostly in the field of Word, narrowing it down to topics relating to String and, in certain cases, Theoretical computer science. The Speech recognition study combines topics in areas such as Sentence, Transfer-based machine translation, Conditional probability, Constraint and Contiguity.

His most cited work include:

  • A probabilistic interpretation of precision, recall and F -score, with implication for evaluation (670 citations)
  • Complex embeddings for simple link prediction (531 citations)
  • Complex Embeddings for Simple Link Prediction (288 citations)

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

The scientist’s investigation covers issues in Artificial intelligence, Natural language processing, Information retrieval, Machine learning and Data mining. His Artificial intelligence research incorporates elements of Series and Pattern recognition. His research in Natural language processing intersects with topics in Representation, Terminology, Speech recognition and Word.

As part of the same scientific family, he usually focuses on Machine learning, concentrating on Similarity learning and intersecting with Robustness. His work focuses on many connections between Data mining and other disciplines, such as Set, that overlap with his field of interest in Relation. His Theoretical computer science research includes elements of Factorization, Hermitian matrix and Dot product.

He most often published in these fields:

  • Artificial intelligence (57.76%)
  • Natural language processing (30.17%)
  • Information retrieval (20.26%)

What were the highlights of his more recent work (between 2018-2021)?

  • Artificial intelligence (57.76%)
  • Information retrieval (20.26%)
  • Embedding (3.88%)

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

His scientific interests lie mostly in Artificial intelligence, Information retrieval, Embedding, Natural language processing and Representation. His Artificial intelligence study which covers Pattern recognition that intersects with Extreme value theory. Eric Gaussier has included themes like Arabic and Document clustering in his Information retrieval study.

As a part of the same scientific family, Eric Gaussier mostly works in the field of Embedding, focusing on Terminology and, on occasion, Ranking. His Natural language processing study integrates concerns from other disciplines, such as Representation, Layer and Process. The study incorporates disciplines such as Value, Theoretical computer science and Categorical variable in addition to Representation.

Between 2018 and 2021, his most popular works were:

  • Deep k-Means: Jointly clustering with k-Means and learning representations (11 citations)
  • Word-embedding-based pseudo-relevance feedback for Arabic information retrieval: (10 citations)
  • On Inductive Abilities of Latent Factor Models for Relational Learning (7 citations)

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

  • Artificial intelligence
  • Statistics
  • Machine learning

Artificial intelligence, Word, Information retrieval, Arabic and Pattern recognition are his primary areas of study. His work carried out in the field of Artificial intelligence brings together such families of science as Multivariate statistics and Scale invariance. His Word study combines topics in areas such as Context, Linguistics, Syntax and Discourse relation.

The concepts of his Information retrieval study are interwoven with issues in Word embedding and Relevance feedback. His Pattern recognition research incorporates themes from Joint, k-means clustering, Cluster analysis, Natural language and Extreme value theory.

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

A probabilistic interpretation of precision, recall and F -score, with implication for evaluation

Cyril Goutte;Eric Gaussier.
european conference on information retrieval (2005)

1431 Citations

A probabilistic interpretation of precision, recall and F -score, with implication for evaluation

Cyril Goutte;Eric Gaussier.
european conference on information retrieval (2005)

1431 Citations

Complex embeddings for simple link prediction

Théo Trouillon;Johannes Welbl;Sebastian Riedel;Éric Gaussier.
international conference on machine learning (2016)

1169 Citations

Complex embeddings for simple link prediction

Théo Trouillon;Johannes Welbl;Sebastian Riedel;Éric Gaussier.
international conference on machine learning (2016)

1169 Citations

An overview of the BIOASQ large-scale biomedical semantic indexing and question answering competition

George Tsatsaronis;Georgios Balikas;Prodromos Malakasiotis;Ioannis Partalas.
BMC Bioinformatics (2015)

388 Citations

An overview of the BIOASQ large-scale biomedical semantic indexing and question answering competition

George Tsatsaronis;Georgios Balikas;Prodromos Malakasiotis;Ioannis Partalas.
BMC Bioinformatics (2015)

388 Citations

Relation between PLSA and NMF and implications

Eric Gaussier;Cyril Goutte.
international acm sigir conference on research and development in information retrieval (2005)

378 Citations

Relation between PLSA and NMF and implications

Eric Gaussier;Cyril Goutte.
international acm sigir conference on research and development in information retrieval (2005)

378 Citations

Word sequence kernels

Nicola Cancedda;Eric Gaussier;Cyril Goutte;Jean Michel Renders.
Journal of Machine Learning Research (2003)

321 Citations

Word sequence kernels

Nicola Cancedda;Eric Gaussier;Cyril Goutte;Jean Michel Renders.
Journal of Machine Learning Research (2003)

321 Citations

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