What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Natural language processing
- Machine learning
Hsin-Hsi Chen spends much of his time researching Artificial intelligence, Natural language processing, Information retrieval, Sentence and Automatic summarization.
His research investigates the link between Artificial intelligence and topics such as Machine learning that cross with problems in Conditional random field and Mood.
His study explores the link between Natural language processing and topics such as Word that cross with problems in Speech recognition.
His Information retrieval research includes elements of Test and Heuristic.
Hsin-Hsi Chen interconnects Sentiment analysis, Opinion analysis and Emotion classification in the investigation of issues within Sentence.
As a part of the same scientific study, Hsin-Hsi Chen usually deals with the Automatic summarization, concentrating on World Wide Web and frequently concerns with Feature and Internet privacy.
His most cited work include:
- Opinion Extraction, Summarization and Tracking in News and Blog Corpora. (399 citations)
- FRank: a ranking method with fidelity loss (178 citations)
- Emotion Classification Using Web Blog Corpora (172 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of study are Artificial intelligence, Natural language processing, Information retrieval, Sentence and Word.
As part of his studies on Artificial intelligence, Hsin-Hsi Chen often connects relevant subjects like Machine learning.
His Natural language processing study combines topics from a wide range of disciplines, such as Speech recognition and Translation.
His Information retrieval research is multidisciplinary, incorporating elements of Set and Web page, World Wide Web.
Hsin-Hsi Chen works in the field of Word, namely Word embedding.
Hsin-Hsi Chen studies Automatic summarization, namely Multi-document summarization.
He most often published in these fields:
- Artificial intelligence (64.50%)
- Natural language processing (57.99%)
- Information retrieval (27.91%)
What were the highlights of his more recent work (between 2015-2021)?
- Artificial intelligence (64.50%)
- Natural language processing (57.99%)
- Artificial neural network (4.88%)
In recent papers he was focusing on the following fields of study:
His primary scientific interests are in Artificial intelligence, Natural language processing, Artificial neural network, Social media and Word.
Artificial intelligence is closely attributed to Machine learning in his work.
The various areas that Hsin-Hsi Chen examines in his Natural language processing study include Domain and Knowledge base.
His study in Artificial neural network is interdisciplinary in nature, drawing from both Context, F1 score and Task analysis.
His study on Social media also encompasses disciplines like
- Finance that connect with fields like Taxonomy, Numeral system, Sentiment analysis and Market sentiment,
- Personal knowledge base, which have a strong connection to Event and Recall,
- Lifelog together with Life events, Multimodal learning and Information retrieval.
His Sentence research incorporates themes from Chinese as a foreign language, Word usage and Machine translation.
Between 2015 and 2021, his most popular works were:
- Irony Detection with Attentive Recurrent Neural Networks (16 citations)
- Numeracy-600K: Learning Numeracy for Detecting Exaggerated Information in Market Comments (12 citations)
- A Neural Network Approach to Early Risk Detection of Depression and Anorexia on Social Media Text. (9 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Natural language processing
- Machine learning
Hsin-Hsi Chen focuses on Artificial intelligence, Natural language processing, Artificial neural network, Social media and Word.
The study of Artificial intelligence is intertwined with the study of Machine learning in a number of ways.
His research ties Representation and Natural language processing together.
His Social media research integrates issues from Lifelog, Personal knowledge base, Knowledge base, Event and Natural language.
His Word research focuses on subjects like Numeral system, which are linked to Taxonomy, Finance and Embedding.
Hsin-Hsi Chen has researched Word embedding in several fields, including Recurrent neural network, WordNet, Information retrieval, Semantic similarity and Multimodal learning.
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