H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 39 Citations 8,006 132 World Ranking 4822 National Ranking 2398

Overview

What is she best known for?

The fields of study she is best known for:

  • Artificial intelligence
  • Natural language processing
  • Machine learning

Artificial intelligence, Natural language processing, Information retrieval, Question answering and WordNet are her primary areas of study. Sanda M. Harabagiu works mostly in the field of Artificial intelligence, limiting it down to topics relating to Relation and, in certain cases, Textual entailment and Filter. Her study in Natural language processing is interdisciplinary in nature, drawing from both Negation and Contradiction.

Her work on Automatic summarization as part of her general Information retrieval study is frequently connected to Net, thereby bridging the divide between different branches of science. Her Question answering research incorporates themes from Context and Semantics. In the field of WordNet, her study on eXtended WordNet overlaps with subjects such as Resource and Falcon.

Her most cited work include:

  • Using Predicate-Argument Structures for Information Extraction (339 citations)
  • FALCON: Boosting Knowledge for Answer Engines (252 citations)
  • Performance issues and error analysis in an open-domain question answering system (210 citations)

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

Sanda M. Harabagiu mainly focuses on Artificial intelligence, Natural language processing, Information retrieval, Question answering and WordNet. Her study on Artificial intelligence is mostly dedicated to connecting different topics, such as Machine learning. Her research links Semantics with Natural language processing.

In general Information retrieval, her work in Automatic summarization, Ranking, Unified Medical Language System and Relevance is often linked to Medical record linking many areas of study. Her research investigates the connection between Question answering and topics such as Inference that intersect with issues in Knowledge-based systems. The concepts of her Information extraction study are interwoven with issues in Relation, Knowledge base and Knowledge acquisition.

She most often published in these fields:

  • Artificial intelligence (66.87%)
  • Natural language processing (57.67%)
  • Information retrieval (35.58%)

What were the highlights of her more recent work (between 2014-2020)?

  • Artificial intelligence (66.87%)
  • Natural language processing (57.67%)
  • Deep learning (6.75%)

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

Sanda M. Harabagiu spends much of her time researching Artificial intelligence, Natural language processing, Deep learning, Information retrieval and Electroencephalography. Sanda M. Harabagiu combines subjects such as Machine learning, Computer vision and Identification with her study of Artificial intelligence. Her Natural language processing research incorporates elements of Dependency, Semantics and Knowledge graph.

Her Deep learning research is multidisciplinary, relying on both Clinical trial and Negation. She interconnects Probabilistic logic, Data science and Knowledge representation and reasoning in the investigation of issues within Information retrieval. Her Probabilistic logic study incorporates themes from Question answering, Clinical decision support system, Inference and Medical algorithm.

Between 2014 and 2020, her most popular works were:

  • Medical Question Answering for Clinical Decision Support (33 citations)
  • Multi-modal Patient Cohort Identification from EEG Report and Signal Data. (12 citations)
  • The Role of a Deep-Learning Method for Negation Detection in Patient Cohort Identification from Electroencephalography Reports. (11 citations)

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

  • Artificial intelligence
  • Machine learning
  • Natural language processing

Sanda M. Harabagiu focuses on Artificial intelligence, Deep learning, Electroencephalography, Natural language processing and Medical record. Many of her studies on Artificial intelligence apply to Computer vision as well. Her work deals with themes such as Ontology, Relevance and Identification, which intersect with Deep learning.

She focuses mostly in the field of Natural language processing, narrowing it down to topics relating to Variety and, in certain cases, Data mining, Annotation and Modality. Her study looks at the relationship between Probabilistic logic and topics such as Information retrieval, which overlap with Knowledge representation and reasoning. Her work on Question answering is being expanded to include thematically relevant topics such as Data science.

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

Using Predicate-Argument Structures for Information Extraction

Mihai Surdeanu;Sanda Harabagiu;John Williams;Paul Aarseth.
meeting of the association for computational linguistics (2003)

511 Citations

FALCON: Boosting Knowledge for Answer Engines

Sanda M. Harabagiu;Dan I. Moldovan;Marius. Paşca;Rada Mihalcea.
text retrieval conference (2000)

452 Citations

Performance issues and error analysis in an open-domain question answering system

Dan Moldovan;Marius Paşca;Sanda Harabagiu;Mihai Surdeanu.
ACM Transactions on Information Systems (2003)

413 Citations

LASSO: A Tool for Surfing the Answer Net

Dan I. Moldovan;Sanda M. Harabagiu;Marius. Paşca;Rada Mihalcea.
text retrieval conference (1999)

328 Citations

Question answering based on semantic structures

Srini Narayanan;Sanda Harabagiu.
international conference on computational linguistics (2004)

279 Citations

Experiments with open-domain textual Question Answering

Sanda M. Harabagiu;Marius A. Paşca;Steven J. Maiorano.
international conference on computational linguistics (2000)

272 Citations

Methods for Using Textual Entailment in Open-Domain Question Answering

Sanda Harabagiu;Andrew Hickl.
meeting of the association for computational linguistics (2006)

262 Citations

LCC Tools for Question Answering.

Dan I. Moldovan;Sanda M. Harabagiu;Roxana Girju;Paul Morarescu.
text retrieval conference (2002)

262 Citations

COGEX: a logic prover for question answering

Dan Moldovan;Christine Clark;Sanda Harabagiu;Steve Maiorano.
north american chapter of the association for computational linguistics (2003)

254 Citations

The structure and performance of an open-domain question answering system

Dan Moldovan;Sanda Harabagiu;Marius Pasca;Rada Mihalcea.
meeting of the association for computational linguistics (2000)

246 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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