＊ About SWRC :
Semantic Web Research Center (SWRC) at KAIST is highly committed to leading the next coming generations of semantic web applications and services, based on the profound development of a wide variety of applied technologies such as machine reading and deep understanding, machine learning, natural language processing, ontology and knowledge engineering, cognitive computing, question answering and so on. Our Center strongly encourages interested students and researchers to actively participate in, and to further become forerunners of both national and international representation in the field of semantic web and other related studies.

＊ Exobrain WiseKB Project (2013-) :
Exobrain, more specifically WiseKB, Project by SWRC aims to construct and expand knowledge bases through self-machine-learning of knowledge from the collected big data, and to develop relevant technologies to be able to further verify these knowledge.

＊ Bio & Medical Informatics Project (2015-) :
SWRC's Bio & Medical Informatics Project is about automatic extraction and detection of terms from electronic medical records (EMR) to discover hidden / interesting correlations of multi-faceted data.

＊ Korean DBpedia Project (2010-) :
The main objective of Korean DBpedia Project by SWRC is to extract structured datasets from Wikipedia sentences in Korean.

＊ Eurostar (2015-) :
In this research project, we will develop a resource-aware and generic multimodal question answering (QA) framework for mobile devices. QAMEL will support speech, text, and gestures as input. Moreover, QAMEL will use the distribution of the data to improve the execution of queries in both offline and online modes. We will deliver an open-source framework that implements (1) multimodal QA, (2) feedback processing functionality as well as (3) prototypical extensions of the partners’ product suites and use-case studies.

＊ Flagship (2016-) :
Emotional intelligence technology to infer human emotion and carry on dialogue accordingly.

＊ PACS (2016-) :
This project is to realize structured knowledge from multi-modal EMR data using artificial intelligence-based natural language processing technology and to integrate it with medical knowledge through learning of medical image and to acquire integrated medical knowledge.

＊ VTT (2017-) :
This project aims to develop human-level video understanding intelligence and verification technology and develops recognition and relationship inference for event situation from video data.

＊ Open Knowledge Base and Question Answering Hackathon (2014-) :
OKBQA Hackathon organized by SWRC on an annual basis aims at facilitating open collaboration for development of knowledge base and question-answering technology which will become the core of many intelligent systems. Naturally being interdisciplinary collaboration, the OKBQA Hackathon is based on cutting-edge technology of semantic web, natural language processing, machine learning, and so forth.