Claim up to $500 in flight credits!
Get up to $500 in flight credits or grants toward study or internship programs abroad when you apply by January 01, 2025. See our Official Rules for full details.
Text Mining - Period 4
Computer Science Program
Amsterdam, Netherlands
Dates: 2/1/24 - 6/1/24
Text Mining - Period 4
OVERVIEW
CEA CAPA Partner Institution: Vrije Universiteit Amsterdam
Location: Amsterdam, Netherlands
Primary Subject Area: Computer Sciences
Instruction in: English
Course Code: L_PABAALG002
Transcript Source: Partner Institution
Course Details: Level 300
Recommended Semester Credits: 3
Contact Hours: 84
DESCRIPTION
It is estimated that about 80% of knowledge is captured in language: think of news, wikis, 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. Contact 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. Contact 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.