Recent News

Attending 2018 SW StarLab Future SW Technology Forum

News Seminars Published August 24, 2018

All members of NLP*CL lab attended the 2018 SW StarLab Future SW Technology Forum held in Seoul National University, Seoul, Korea on August 24, 2018. Prof. Park gave a presentation for our StarLab project titled "How much do I trust what you say? What evidence do I need?".


 

2018 NLP*CL Homecoming Day

News Etc Published June 02, 2018

The NLP*CL Lab held its "2018 Homecoming Day" on 2nd of June.
Professor, alumni and current students gathered together to have a good time.


 

Our lab has been selected as SW Star Lab.

News Projects Published May 01, 2018

The Korean Ministry of Science and ICT and IITP selected our lab as a SW Star Lab of intelligent software on April 20, 2018.혻The selected lab will receive project funding of up to 300 million won per year for up to eight years and is encouraged to develop a world-class research agenda through open software.


Our lab will work on the development of software for automatically predicting the credibility distribution of given documents and dialogues, consisting of five modules: data collection, automatic collection of evidence, credibility enhancement, credibility distribution prediction, and linguistic analysis.


This year, a total of five laboratories have been selected in four universities: Seoul National University, POSTECH, Chung Ang University, and KAIST. There are two laboratories in the field of intelligent software including our lab.


 

Two new students joined our lab

News Announcements Published February 26, 2018

Seungwon and ChaeHun joined our lab as master's students starting from this semester. Welcome!



Attending HCI Korea 2018, Jeongseon, Korea

News Conferences Published January 31, 2018

Huije and Hoyun attended the HCI (Human-Computer Interaction) Korea 2018 held in Jeongseon, Korea on January 31-February 2, 2018. Huije gave an oral presentation for the paper titled "Detection of Non-Standard Meaning Usage with Word Embedding".


 

Attending KSC 2017, Busan, Korea

News Conferences Published December 20, 2017

Jung-Ho, Wonsuk, Hoyun and Huije attended the Korea Software Congress 2017 held in Busan, Korea on December 20-22, 2017. Hoyun gave an oral presentation for the paper titled "Predicting Symptoms of Depression for Social Media Users via Linguistic Patterns" and Jung-Ho, Youngjin (CGV Lab.), and Wonsuk attended SW/Demo Contest as a team named 'NLPCL * CGV' and won the best (理쒖슦닔) demo award. Congratulations!


 

Attending IJCNLP 2017, Taipei, Taiwan

News Conferences Published November 27, 2017

Jinseon, Jin-Woo, and Prof. Park attended the 8th International Joint Conference on Natural Language Processing (IJCNLP 2017) held in Taipei, Taiwan, on November 27밆ecember 1, 2017. Jinseon gave an oral presentation for the long paper titled "Extraction of Gene-Environment Interaction from the Biomedical Literature".


 

Jin-Woo won the NAVER PhD fellowship award

News Etc Published September 30, 2017

Jin-Woo won the NAVER PhD fellowship award given by NAVER Corporation. Congratulation!

NAVER PhD fellowship award is given to PhD students in computer science혻who have published top-tier conference papers and journal articles.혻Jin-Woo has done work on spatial information extraction from text and presented research results to IJCAI this year.



A paper accepted at IJCNLP 2017

News Publications Published September 01, 2017

Our paper "Extraction of Gene-Environment Interaction from the Biomedical Literature" (authored by Jinseon You, Jin-Woo Chung, Wonsuk Yang, and Prof. Park) has been accepted as a long paper at the 8th International Joint Conference on Natural Language Processing (IJCNLP 2017).


 

Attending IJCAI-17, Melbourne, Australia

News Conferences Published August 19, 2017

Jin-Woo, Wonsuk, and Prof. Park attended the 26th International Joint Conference on Artificial Intelligence (IJCAI-17) held in Melbourne, Australia on August 19-25, 2017. Jin-Woo gave an oral presentation for the main track paper titled "Inferring Implicit Event Locations from Context with Distributional Similarities".