TY - GEN
T1 - NLP-KG
T2 - 62nd Annual Meeting of the Association for Computational Linguistics, ACL 2024
AU - Schopf, Tim
AU - Matthes, Florian
N1 - Publisher Copyright:
© 2024 Association for Computational Linguistics.
PY - 2024
Y1 - 2024
N2 - Scientific literature searches are often exploratory, whereby users are not yet familiar with a particular field or concept but are interested in learning more about it. However, existing systems for scientific literature search are typically tailored to keyword-based lookup searches, limiting the possibilities for exploration. We propose NLP-KG, a feature-rich system designed to support the exploration of research literature in unfamiliar natural language processing (NLP) fields. In addition to a semantic search, NLP-KG allows users to easily find survey papers that provide a quick introduction to a field of interest. Further, a Fields of Study hierarchy graph enables users to familiarize themselves with a field and its related areas. Finally, a chat interface allows users to ask questions about unfamiliar concepts or specific articles in NLP and obtain answers grounded in knowledge retrieved from scientific publications. Our system provides users with comprehensive exploration possibilities, supporting them in investigating the relationships between different fields, understanding unfamiliar concepts in NLP, and finding relevant research literature. Demo, video, and code are available at: https://github.com/NLPKnowledge-Graph/NLP-KG-WebApp.
AB - Scientific literature searches are often exploratory, whereby users are not yet familiar with a particular field or concept but are interested in learning more about it. However, existing systems for scientific literature search are typically tailored to keyword-based lookup searches, limiting the possibilities for exploration. We propose NLP-KG, a feature-rich system designed to support the exploration of research literature in unfamiliar natural language processing (NLP) fields. In addition to a semantic search, NLP-KG allows users to easily find survey papers that provide a quick introduction to a field of interest. Further, a Fields of Study hierarchy graph enables users to familiarize themselves with a field and its related areas. Finally, a chat interface allows users to ask questions about unfamiliar concepts or specific articles in NLP and obtain answers grounded in knowledge retrieved from scientific publications. Our system provides users with comprehensive exploration possibilities, supporting them in investigating the relationships between different fields, understanding unfamiliar concepts in NLP, and finding relevant research literature. Demo, video, and code are available at: https://github.com/NLPKnowledge-Graph/NLP-KG-WebApp.
UR - http://www.scopus.com/inward/record.url?scp=85203796352&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85203796352
T3 - Proceedings of the Annual Meeting of the Association for Computational Linguistics
SP - 127
EP - 135
BT - System Demonstrations
A2 - Cao, Yixin
A2 - Feng, Yang
A2 - Xiong, Deyi
PB - Association for Computational Linguistics (ACL)
Y2 - 11 August 2024 through 16 August 2024
ER -