What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Machine learning
- Natural language processing
His primary scientific interests are in Artificial intelligence, Natural language processing, Coreference, Resolution and Machine learning.
With his scientific publications, his incorporates both Artificial intelligence and Ideology.
His Natural language processing research is multidisciplinary, relying on both Argumentation mining, Information retrieval and Identification.
He undertakes multidisciplinary studies into Coreference and Noun phrase in his work.
His study in Resolution is interdisciplinary in nature, drawing from both Winograd Schema Challenge, Heuristics, Salience and Pronoun.
Vincent Ng has included themes like Classifier and Partition in his Machine learning study.
His most cited work include:
- Improving Machine Learning Approaches to Coreference Resolution (614 citations)
- Automatic Keyphrase Extraction: A Survey of the State of the Art (301 citations)
- Examining the Role of Linguistic Knowledge Sources in the Automatic Identification and Classification of Reviews (209 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, Coreference, Resolution and Machine learning.
His Artificial intelligence research includes themes of Data mining and Identification.
By researching both Natural language processing and Noun phrase, Vincent Ng produces research that crosses academic boundaries.
In his study, Vincent Ng carries out multidisciplinary Coreference and Event research.
His biological study spans a wide range of topics, including Ranking and Context.
His Machine learning study incorporates themes from Baseline, Inference and Integer programming.
He most often published in these fields:
- Artificial intelligence (69.39%)
- Natural language processing (53.06%)
- Coreference (33.33%)
What were the highlights of his more recent work (between 2017-2021)?
- Artificial intelligence (69.39%)
- Natural language processing (53.06%)
- Quality (8.16%)
In recent papers he was focusing on the following fields of study:
His primary areas of study are Artificial intelligence, Natural language processing, Quality, Coreference and Information retrieval.
His studies in Artificial intelligence integrate themes in fields like Machine learning and Key.
The various areas that Vincent Ng examines in his Natural language processing study include Argumentation mining, Training set, State and Heuristics.
His study connects Inference and Coreference.
The Information retrieval study combines topics in areas such as Sentiment analysis and SemEval.
His Resolution research includes elements of Topic model, Context, Preprocessor and Salient.
Between 2017 and 2021, his most popular works were:
- Modeling and Prediction of Online Product Review Helpfulness: A Survey (29 citations)
- Abstractive Summarization: A Survey of the State of the Art. (24 citations)
- Event Coreference Resolution: A Survey of Two Decades of Research. (21 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Machine learning
- Natural language processing
Artificial intelligence, Quality, Natural language processing, Automated essay scoring and State are his primary areas of study.
His research in the fields of Resolution overlaps with other disciplines such as Euler's formula.
His Quality research incorporates elements of Product reviews, Helpfulness, Data science, Triage and Machine learning.
His research on Natural language processing often connects related topics like Coreference.
His work deals with themes such as Argument and Argumentative, which intersect with Automated essay scoring.
His State research incorporates elements of Representation, Meaning, Automatic summarization and Machine translation.
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