What is she best known for?
The fields of study she is best known for:
- Artificial intelligence
- The Internet
- Programming language
Kalina Bontcheva spends much of her time researching Artificial intelligence, Natural language processing, Social media, Information extraction and Data science.
Her Artificial intelligence research is multidisciplinary, incorporating elements of Machine learning and Task.
Her work carried out in the field of Natural language processing brings together such families of science as Ontology and Ontology, Information retrieval, Process ontology.
Her Social media research is multidisciplinary, incorporating perspectives in Information access, Classifier and Internet privacy.
Her Information extraction study incorporates themes from Context, Software engineering and Unicode.
Her research in Data science intersects with topics in Crowdsourcing, World Wide Web, Semantic Web, Annotation and Semantics.
Her most cited work include:
- A framework and graphical development environment for robust NLP tools and applications. (1520 citations)
- GATE: an Architecture for Development of Robust HLT applications (335 citations)
- Detection and Resolution of Rumours in Social Media: A Survey (284 citations)
What are the main themes of her work throughout her whole career to date?
Her scientific interests lie mostly in Artificial intelligence, Natural language processing, Social media, Information retrieval and Task.
Her Artificial intelligence research incorporates themes from Context, Machine learning and Named-entity recognition.
Her Natural language processing research includes themes of Ontology and Annotation.
Her studies deal with areas such as Ontology and Semantic Web as well as Ontology.
Her Social media course of study focuses on Internet privacy and Disinformation.
Her research on Information retrieval frequently connects to adjacent areas such as Pipeline.
She most often published in these fields:
- Artificial intelligence (39.59%)
- Natural language processing (31.02%)
- Social media (25.31%)
What were the highlights of her more recent work (between 2018-2021)?
- Social media (25.31%)
- Task (17.14%)
- Artificial intelligence (39.59%)
In recent papers she was focusing on the following fields of study:
Her main research concerns Social media, Task, Artificial intelligence, Criminology and Brexit.
Kalina Bontcheva combines subjects such as Social network, Baseline, Data science and Internet privacy with her study of Social media.
Her Task research integrates issues from Information retrieval and Fake news.
Her study in Information retrieval is interdisciplinary in nature, drawing from both Information access and Pipeline.
Kalina Bontcheva has researched Artificial intelligence in several fields, including Mechanism, Machine learning and Natural language processing.
Her study focuses on the intersection of Natural language processing and fields such as Annotation with connections in the field of Harm.
Between 2018 and 2021, her most popular works were:
- SemEval-2019 Task 7: RumourEval, Determining Rumour Veracity and Support for Rumours (71 citations)
- Gaussian Processes for Rumour Stance Classification in Social Media (16 citations)
- Team Bertha von Suttner at SemEval-2019 Task 4: Hyperpartisan News Detection using ELMo Sentence Representation Convolutional Network (13 citations)
In her most recent research, the most cited papers focused on:
- Artificial intelligence
- The Internet
- Programming language
Kalina Bontcheva mostly deals with Social media, Task, SemEval, Internet privacy and Artificial intelligence.
Her Social media research entails a greater understanding of World Wide Web.
Her Task research includes elements of Journalism, Interface, Service and Social network.
The study incorporates disciplines such as Normalization, Sentence, Natural language processing, Ranking and Convolutional neural network in addition to SemEval.
The concepts of her Internet privacy study are interwoven with issues in Variety and Disinformation.
Kalina Bontcheva interconnects Event, Machine learning and Mechanism in the investigation of issues within Artificial intelligence.
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