A comparison of clustering techniques for short social text messages
The amount of social text messages authored each day is huge and the information contained within is potentially very valuable. Software that can cluster and thereby help analyze these messages would consequently be helpful. This thesis explores several ways of clustering social text messages. Two a...
| Main Author: | |
|---|---|
| Format: | Others |
| Language: | English |
| Published: |
KTH, Skolan för datavetenskap och kommunikation (CSC)
2016
|
| Subjects: | |
| Online Access: | http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-196735 |