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Text Mining - Period 4
概述
CEA CAPA 合作伙伴机构: Vrije Universiteit Amsterdam
地点: Amsterdam, 荷兰
Primary Subject Area: 计算机科学
指令: 英语
课程代码: L_PABAALG002
记录来源: 合作伙伴机构
课程详细信息: 300级
Recommended Semester Credits: 3
联系时间: 84
描述
It is estimated that about 80% of knowledge is captured in language: think of news, 维基百科, social media and handbooks. Searching for information is also largely done through language. The amount of information is too large for humans to oversee, which is why technologies are developed to access and use this information more efficiently.
Text Mining is a promising research domain whose goal it is to extract structured information from unstructured natural language. This is a big challenge as human language is a rich and complex medium that is to be understood in the context of social human interaction. Therefore, language technology analyses language on different levels: the grammatical level (e.g. word types and syntax), and the semantic level (e.g. entities, events, opinions). During the course you will learn how this information is coded in text and how you can extract and present it using computers.
Vrije Universiteit Amsterdam (VU Amsterdam) awards credits based on the ECTS system. 联系 hours listed under a course description may vary due to the combination of lecture-based and independent work required for each course therefore, CEA's recommended credits are based on the ECTS credits assigned by VU Amsterdam. 1 ECTS equals 28 contact hours assigned by VU Amsterdam.
Text Mining is a promising research domain whose goal it is to extract structured information from unstructured natural language. This is a big challenge as human language is a rich and complex medium that is to be understood in the context of social human interaction. Therefore, language technology analyses language on different levels: the grammatical level (e.g. word types and syntax), and the semantic level (e.g. entities, events, opinions). During the course you will learn how this information is coded in text and how you can extract and present it using computers.
Vrije Universiteit Amsterdam (VU Amsterdam) awards credits based on the ECTS system. 联系 hours listed under a course description may vary due to the combination of lecture-based and independent work required for each course therefore, CEA's recommended credits are based on the ECTS credits assigned by VU Amsterdam. 1 ECTS equals 28 contact hours assigned by VU Amsterdam.
