CSE 261Advanced Data-Driven Text Mining
Unsupervised, weakly supervised, and distantly supervised methods for text mining problems, including information retrieval, open-domain information extraction, text summarization (both extractive and generative), and knowledge graph construction. Bootstrapping, comparative analysis, learning from seed words and existing knowledge bases will be the key methodologies. Students may not receive credit for both CSE 261 and DSC 253. Knowledge about machine learning and data mining, statistics, coding with Python, C/C++, and/or Java.
Prerequisites
None listed in the catalog.