The scientist’s investigation covers issues in Artificial intelligence, Machine learning, Data mining, Information retrieval and Natural language processing. His multidisciplinary approach integrates Artificial intelligence and Component in his work. His studies deal with areas such as Legal expert system and Fuzzy control system as well as Machine learning.
The concepts of his Data mining study are interwoven with issues in Textual information, Document classification, Unsupervised learning and Trading strategy. In his study, Text graph is strongly linked to World Wide Web, which falls under the umbrella field of Information retrieval. His Automatic summarization and Topic model study, which is part of a larger body of work in Natural language processing, is frequently linked to Pronunciation, bridging the gap between disciplines.
Wai Lam spends much of his time researching Artificial intelligence, Information retrieval, Machine learning, Data mining and Natural language processing. When carried out as part of a general Artificial intelligence research project, his work on Sentence, Bayesian network and Automatic summarization is frequently linked to work in Component, therefore connecting diverse disciplines of study. The study incorporates disciplines such as Ranking, World Wide Web, Categorization and Document clustering in addition to Information retrieval.
His Machine learning research focuses on Benchmark and how it connects with Sentiment analysis. His studies in Data mining integrate themes in fields like Graphical model, Information extraction and Web page. His study in Graphical model is interdisciplinary in nature, drawing from both Probabilistic logic, Discriminative model, Inference and Conditional random field.
Wai Lam focuses on Artificial intelligence, Information retrieval, Natural language processing, Question answering and Benchmark. His Artificial intelligence study frequently draws connections to adjacent fields such as Machine learning. In the field of Information retrieval, his study on Snippet overlaps with subjects such as Component.
His biological study spans a wide range of topics, including E-commerce, Ranking, Relevance and Data science. His Benchmark study integrates concerns from other disciplines, such as Sentiment analysis, Smoothing, Autoencoder, Knowledge base and Relation. His Sentence research is multidisciplinary, relying on both Semantics, Word and Lexicon.
Wai Lam spends much of his time researching Artificial intelligence, Information retrieval, Sentence, Benchmark and Sentiment analysis. In general Artificial intelligence study, his work on Automatic summarization often relates to the realm of Quality, thereby connecting several areas of interest. His study explores the link between Information retrieval and topics such as Training set that cross with problems in Generative model.
He interconnects Semantics and Word in the investigation of issues within Sentence. His biological study deals with issues like Machine learning, which deal with fields such as Language model and End-to-end principle. His Sentiment analysis research incorporates themes from Dependency and Relation, Data mining.
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LEARNING BAYESIAN BELIEF NETWORKS: AN APPROACH BASED ON THE MDL PRINCIPLE
Wai Lam;Fahiem Bacchus.
computational intelligence (1994)
MEAD - A Platform for Multidocument Multilingual Text Summarization
Dragomir R. Radev;Timothy Allison;Sasha Blair-Goldensohn;John Blitzer.
language resources and evaluation (2004)
Using a generalized instance set for automatic text categorization
Wai Lam;Chao Yang Ho.
international acm sigir conference on research and development in information retrieval (1998)
A multilevel approach to intelligent information filtering: model, system, and evaluation
J. Mostafa;S. Mukhopadhyay;M. Palakal;W. Lam.
ACM Transactions on Information Systems (1997)
Transformation Networks for Target-Oriented Sentiment Classification
Xin Li;Lidong Bing;Wai Lam;Bei Shi.
meeting of the association for computational linguistics (2018)
Fuzzy concepts in expert systems
K.S. Leung;W. Lam.
IEEE Computer (1988)
Automatic text categorization and its application to text retrieval
Wai Lam;M. Ruiz;P. Srinivasan.
IEEE Transactions on Knowledge and Data Engineering (1999)
Evaluation Challenges in Large-Scale Document Summarization
Dragomir R. Radev;Simone Teufel;Horacio Saggion;Wai Lam.
meeting of the association for computational linguistics (2003)
News Sensitive Stock Trend Prediction
Gabriel Pui Cheong Fung;Jeffrey Xu Yu;Wai Lam.
knowledge discovery and data mining (2002)
Deep Multi-Task Learning for Aspect Term Extraction with Memory Interaction
Xin Li;Wai Lam.
empirical methods in natural language processing (2017)
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