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Automatic Twitter ResponseGenerator
KTH, School of Computer Science and Communication (CSC).
KTH, School of Computer Science and Communication (CSC).
2013 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

Since the beginning of chatbots, the most common techniques used for simulating conversation

has been different pattern matching-techniques. This is a study of possible alternative methods

and an attempt of implementation. As the research of natural language processing is rapidly

progressing, the aim of this report is to clarify current techniques and what could possibly be

achieved by adapting recent findings on the area.

A combination of part-of-speech tagging, methods for information retrieval and known methods

for generating language are covered and described of how it could be of use. An implementation

is reviewed and compared to traditional programs. The final conclusion states that the

implementation is not as satisfying as chatbots using elaborated pattern matching-techniques.

However, it is concluded that the new methods covered are more likely to be part of future

chatbots considering the progress of natural language processing.

Place, publisher, year, edition, pages
Kandidatexjobb CSC, K13008
National Category
Computer Science
URN: urn:nbn:se:kth:diva-134835OAI: diva2:668274
Educational program
Master of Science in Engineering - Computer Science and Technology
Available from: 2013-12-13 Created: 2013-11-29 Last updated: 2013-12-13Bibliographically approved

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Automatic Twitter Response(248 kB)51 downloads
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