Welcome to Semantics In Information Retrieval Research Site
Welcome! Semantics in IR is a research initiative carried out by myself and our dedicated team of students in the areas of semantically enhanced information retrieval, and its related applications. The research at SIIR focuses on both theorectical and applied methods to make textual information more meaningful and understandable.
By laying semantics as our ground work, our research concentrates on the techniques, modelling and representation of various layers of meanings:
- lexical, syntactic, semantic, context (Natural Language Processing)
- synonym, taxonomy, classes, ontological (Conceptual Processing)
- aspect polarity, temporal semantic (Sentiment Processing)
Please drop me an email at khganATusm.my if you are interested to join our exciting projects.
Gan Keng Hoon
School of Computer Sciences, USM.
Prospective Students
We are pleased to announce the following research topics for new Phd or Msc research candidates.- Optimizing Text Preprocessing Pipeline
- Concepts Extraction and Mapping in Scientific Article
- Abstract Generation from Scientific Article
- SDG Text Mining and Classification for Experts Collaboration
Visitors
Projects
Deep Search of Experts Profile
"Who is good at at Hidden Markov Model?". Deep experts search looks up information about experts at academic institute, about their research and teaching expertise.
TalkAbout: Cross Domain Opinion Mining and Sentiment Analysis
People talk about people, service, products in reviews and comment feeds. Talk About is an opinion mining and sentiment analysis platform that focuses on cross domain sentiment analysis on the items that people commented.
The two worlds of data, unstructured and structured data, are now gaining more attentions to be adopted as a whole by leveraging the advantage of both types of data. For example, natural language interfaces for system requires the connection between unstructured query and structured APIs, enterprise search analytics requires the consolidation of both structured and unstructured company data etc. The BRIDGE project focuses on the design of data representation, the semantics and processes that bridges the two ends of data, such as transformation, interpretation and mapping.
Demo
We are pleased to release the beta version of expert search 4. (1 October 2019)
Try the system @ http://ir.cs.usm.my/exsearch4/index.php Feedbacks are welcomed.
Who are behind the system? Visit the the project page to find out.
What You Can Do With Semantic Annotation to Improve Information Retrieval.
Richer Text
Good annotations make text richer. There are many forms of annotations that can be applied on text, e.g. linguistic information, concepts, meaning, formatting etc. However, too many annotations may mess up the text as well. Our research directions in text annotation include
Speech & Video
Coming soon...
Image
Coming soon...
News
Presentation by Fatima at CS Journal Club D2K Track
16 December 2023
Research Group Meeting at D2K Lab
3 October 2022
(left to right) Ige, Asma, Gan, Eman, Sani
Latest Publications
Vivian Lee Lay Shan, Gan Keng Hoon, Tan Tien Ping, Rosni Abdullah: Using Informative Score for Instance Selection Strategy in Semi-Supervised Sentiment Classification. Computers, Materials and Continua, 74(3):4801-4818, Tech Science Press (2023). Q2 IF:3.860 (JCR 2021) New
Fatima N Al-Aswadi, Chan Huah Yong, Gan Keng Hoon, Wafa' Za'al Alma'aitah: Enhancing relevant concepts extraction for ontology learning using domain time relevance. Information Processing and Management, 60(1), Elsevier (2023). Q1 IF:7.466 (JCR 2021) New
Sylvia Wong Shiau Ching, Tan Jing-Ru, Gan Keng Hoon, Tan Tien-Ping: Text analytics of vaccine myths on reddit. Handbook of Research on Artificial Intelligence Applications in Literary Works and Social Media, 277-201, IGI Global (2023). New
Tee Tze Huat, Belicia Yeap Qiao Bei, Gan Keng Hoon, Tan Tien Ping: Learning to Automatically Generating Genre-Specific Song Lyrics: A Comparative Study. Communications in Computer and Information Science, 1686:62-75, 4th Iberoamerican and the 3rd Indo-American Knowledge Graphs and Semantic Web Conference, KGSWC 2022, Madrid, 21-23 November 2022. New
Fatima N Al-Aswadi, Chan Huah Yong, Gan Keng Hoon: From Ontology to Knowledge Graph Trend: Ontology as Foundation Layer for Knowledge Graph. Communications in Computer and Information Science, 1686:330-340, 4th Iberoamerican and the 3rd Indo-American Knowledge Graphs and Semantic Web Conference, KGSWC 2022, Madrid, 21-23 November 2022. New
Lee Kah Win, Gan Keng Hoon: Text Classification of Medical Transcriptions using N-Gram Machine Learning Approach. 4th IEEE International Conference on Artificial Intelligence in Engineering and Technology, IICAIET 2022, Kota Kinabalu, 13-15 September 2022. New
Ong Song-Quan, Maisarah Binti Mohamed Pauzi, Gan Keng Hoon: Text mining in mosquito-borne disease: A systematic review. Acta Tropica, 231, Elsevier B.V. (2022). Q2 IF:3.222 (JCR 2021)
Ong Song-Quan, Maisarah Binti Mohamed Pauzi, Gan Keng Hoon: Text Mining and Determinants of Sentiments towards the COVID-19 Vaccine Booster of Twitter Users in Malaysia. Healthcare, 10(6), MDPI (2022). Q2 IF:3.160 (JCR 2021)
Social Data
Massive social data are generated each second. These data can be utilized to improve the understanding of people behaviour and make better prediction in the future. Deep understanding of users behaviour, for example their preferences, comments about products, etc. shall benefit the building of intelligent systems like personalization and recommending system.
Our research directions in social data annotation include