What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Machine learning
- Statistics
His scientific interests lie mostly in Artificial intelligence, Information retrieval, Social media, Search engine and Ranking.
Yi Chang has researched Artificial intelligence in several fields, including Machine learning, Human–computer interaction and Natural language processing.
His biological study spans a wide range of topics, including Ranking and Classifier.
His Social media research incorporates elements of Multimedia, Data science and Social network.
His Search engine study combines topics in areas such as Data stream and Data Web.
His Ranking research integrates issues from Semi-supervised learning, Active learning and Key.
His most cited work include:
- Abusive Language Detection in Online User Content (507 citations)
- Yahoo! Learning to Rank Challenge Overview (353 citations)
- Time is of the essence: improving recency ranking using Twitter data (194 citations)
What are the main themes of his work throughout his whole career to date?
His main research concerns Information retrieval, Artificial intelligence, Machine learning, Ranking and Search engine.
While the research belongs to areas of Information retrieval, Yi Chang spends his time largely on the problem of Ranking, intersecting his research to questions surrounding Click-through rate.
The study incorporates disciplines such as Pattern recognition, Recommender system and Natural language processing in addition to Artificial intelligence.
His study in Machine learning is interdisciplinary in nature, drawing from both Web search engine, Adaptation and Big data.
In his research, Cluster analysis is intimately related to Data mining, which falls under the overarching field of Ranking.
His Search engine research entails a greater understanding of World Wide Web.
He most often published in these fields:
- Information retrieval (40.08%)
- Artificial intelligence (36.29%)
- Machine learning (22.78%)
What were the highlights of his more recent work (between 2017-2021)?
- Artificial intelligence (36.29%)
- Information retrieval (40.08%)
- Theoretical computer science (8.02%)
In recent papers he was focusing on the following fields of study:
The scientist’s investigation covers issues in Artificial intelligence, Information retrieval, Theoretical computer science, Natural language processing and Machine learning.
His studies link Pattern recognition with Artificial intelligence.
He interconnects Adversarial system, Training set, Matching, Probabilistic logic and Social media in the investigation of issues within Information retrieval.
His Theoretical computer science research is multidisciplinary, incorporating elements of Perspective, Task and Graph.
His Natural language processing research incorporates themes from Semantics, Word and Dialog box.
His Machine learning research includes themes of Heuristics and Robustness.
Between 2017 and 2021, his most popular works were:
- Zero-shot User Intent Detection via Capsule Neural Networks (84 citations)
- Target-Sensitive Memory Networks for Aspect Sentiment Classification (67 citations)
- GraphLIME: Local Interpretable Model Explanations for Graph Neural Networks (39 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Machine learning
- Statistics
Artificial intelligence, Natural language processing, Theoretical computer science, Artificial neural network and Network analysis are his primary areas of study.
He combines subjects such as Machine learning and Pattern recognition with his study of Artificial intelligence.
His Machine learning study incorporates themes from Class, Data classification and Big data.
The concepts of his Natural language processing study are interwoven with issues in Semantics and Representation.
His study looks at the relationship between Theoretical computer science and topics such as Graph, which overlap with Network embedding and Deep learning.
The various areas that he examines in his Artificial neural network study include User intent, Knowledge transfer, Dialog box and Shot.
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