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Large-Scale Pattern-Based Information Extraction from the World Wide Web

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Large-Scale Pattern-Based Information Extraction from the World Wide Web


Suppose you want to stay up-to-date with all relevant facts about a product on the market or quickly generate a list of interesting events at your next travel destination? This data is probably nowhere covered broader and up-to-date than on the Web. Wouldn’t it be convenient to simply aggregate the required facts from the Web?

Extracting information from text is the task of obtaining structured, machine-processable facts from information that is mentioned in an unstructured manner. It thus allows systems to automatically aggregate information for further analysis, efficient retrieval, automatic validation, or appropriate visualization. Information Extraction systems require a model that describes how to identify relevant target information in texts. These models need to be adapted to the exact nature of the target information and to the nature of the textual input, which is typically accomplished by means of Machine Learning techniques that generate such models based on examples.

The talk presents studies on using textual patterns for extracting information from the World Wide Web. We explore both fundamental design choices and practical applications.

The talk will be given in German language.

(Sebastian Blohm)

Start: 18. November 2009 um 15:45
Ende: 18. November 2009 um 16:45

Im Gebäude 11.40, Raum: 231

Veranstaltung vormerken: (iCal)

Veranstalter: Forschungsgruppe(n) Wissensmanagement
Information: Media:Blohm.pdf