Very interesting is the tag “folksonomy” page and the related links proposed by Bibsonomy: you can find hundreds of bookmarks (whether web sites or articles) over topics such as social tagging and information architecture.
A number of resources have been compiled within the context of the MuchMore project. These include: a bilingual, parallel medical corpus; corresponding queries and relevance assessments; evaluation sets of disambiguated terms for GermaNet and UMLS; an evaluation list for morphological decomposition of medical terms.
MALLET is an integrated collection of Java code useful for statistical natural language processing, document classification, clustering, information extraction, and other machine learning applications to text.
I'm interested in machine learning techniques (graphical models, kernel methods) applied to text understanding (entity and relation extraction, coreference resolution, document classification and clustering, confidence prediction, social network analysis, data mining).
D. Schlör, J. Pfister, and A. Hotho. 2023 the 7th International Conference on Medical and Health Informatics (ICMHI), page 136–141. New York, NY, USA, Association for Computing Machinery, (2023)
A. Dulny, A. Hotho, and A. Krause. Machine Learning and Knowledge Discovery in Databases: Research Track, page 438--455. Cham, Springer Nature Switzerland, (2023)
D. Wangsadirdja, J. Pfister, K. Kobs, and A. Hotho. Proceedings of the The 17th International Workshop on Semantic Evaluation (SemEval-2023), page 1090--1095. Toronto, Canada, Association for Computational Linguistics, (July 2023)