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Text_Mining_-_Hanmei_Fan_-_Fall_2006.ppt

Text_Mining_-_Hanmei_Fan_-_Fall_2006.ppt - Text Mining...

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Text Mining Presenter: Hanmei Fan
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Definition Text mining also is known as Text Data Mining (TDM) and Knowledge Discovery in Textual Database (KDT).[1] A process of identifying novel information from a collection of texts (also known as a corpus). [2]
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Data Mining vs. Text Mining Data Mining process directly Identify causal relationship Structured numeric transaction data residing in rational data warehouse Text Mining Linguistic processing or natural language processing (NLP) Discover heretofore unknown information[2] Applications deal with much more diverse and eclectic collections of systems and formats[4]
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Disputation Hearst: non-novel, novel. Text mining is not a simple extension of data mining applied to unstructured database. Text mining is the process of mining precious nuggets of ore from a mountain otherwise worthless rock. Kroeze: non-novel, semi-novel, and novel Non-novel: data/information retrieval Semi-novel: knowledge discovery (standard data- mining, metadata mining, and standard text mining) Novel: intelligent text mining
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Confusion Is text mining the same as information extraction? No! Information Extraction (IE) Extract facts about pre-specified entities, events or relationships from unrestricted text sources. No novelty : only information is already present is extracted.
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Two Foundations Information Retrieval (IR) Artificial Intelligence (AI)
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Information Retrieval The science of searching for Information in documents Documents themselves Metadata which describe documents Text, sound, images or data, within database: relational stand-alone database or hypertext networked databases such as the Internet or intranets.
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Information Retrieval Gerard Salton Functional overview of IR
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Application I Semi-novel Text clustering: group similar documents for further examination -> create thematic overviews of text collections Issues: Information needs is vague Even if a topic were available, the words used to describe it may not be known to the user The words used to describe a topic may not be those used to discuss the topic and may thus fail to appear in articles of interest.
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