Transcription of CS 6501: Text Mining
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CS 6501: Text Mining
cs 6501 : Text MiningHongning Wang of Computer ScienceUniversity of Virginia1 Course OverviewGiven the dominance of text information over the Internet, Mining high-quality information fromtext becomes increasingly critical. The actionable knowledge extracted from text data facilitatesour life in a broad spectrum of areas, including business intelligence, information acquisition,social behavior analysis and decision making. In this course, we will cover important topics intext Mining including: basic natural language processing techniques, document representation,text categorization and clustering, document summarization, sentiment analysis , social networkand social media analysis , probabilistic topic models and text addition, as we are in the era of Big Data, we will provide you opportunities to gainhands-on experience of handling large-scale data set, , Big Data. Modern data processingarchitecture, , Apache Hadoop1, Apache Spark2and GraphLab3, will be incorporated inhomework PrerequisitesIt is recommended that you have taken CS 2150 (or equivalent courses in data structure, algo-rithm) and have a good working familiarity with at least one programming language (Java isrecommended, while Python is also ok).
text mining including: basic natural language processing techniques, document representation, text categorization and clustering, document summarization, sentiment analysis, social network and social media analysis, probabilistic topic models and text visualization.
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