Discovering Context: Classifying Tweets Through a Semantic Transform based on Wikipedia
Authors | Yegin Genc Yasuaki Sakamoto Jeffrey V. Nickerson |
|---|---|
Publication date | 2011 |
DOI | 10.1007/978-3-642-21852-1_55 |
Links | Original |
Discovering Context: Classifying Tweets Through a Semantic Transform based on Wikipedia - scientific work related to Wikipedia quality published in 2011, written by Yegin Genc, Yasuaki Sakamoto and Jeffrey V. Nickerson.
Overview
By mapping messages into a large context, authors can compute the distances between them, and then classify them. Authors test this conjecture on Twitter messages: Messages are mapped onto their most similar Wikipedia pages, and the distances between pages are used as a proxy for the distances between messages. This technique yields more accurate classification of a set of Twitter messages than alternative techniques using string edit distance and latent semantic analysis.
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Wikipedia Quality
Genc, Yegin; Sakamoto, Yasuaki; Nickerson, Jeffrey V.. (2011). "[[Discovering Context: Classifying Tweets Through a Semantic Transform based on Wikipedia]]". Springer, Berlin, Heidelberg. DOI: 10.1007/978-3-642-21852-1_55.
English Wikipedia
{{cite journal |last1=Genc |first1=Yegin |last2=Sakamoto |first2=Yasuaki |last3=Nickerson |first3=Jeffrey V. |title=Discovering Context: Classifying Tweets Through a Semantic Transform based on Wikipedia |date=2011 |doi=10.1007/978-3-642-21852-1_55 |url=https://wikipediaquality.com/wiki/Discovering_Context:_Classifying_Tweets_Through_a_Semantic_Transform_based_on_Wikipedia |journal=Springer, Berlin, Heidelberg}}
HTML
Genc, Yegin; Sakamoto, Yasuaki; Nickerson, Jeffrey V.. (2011). "<a href="https://wikipediaquality.com/wiki/Discovering_Context:_Classifying_Tweets_Through_a_Semantic_Transform_based_on_Wikipedia">Discovering Context: Classifying Tweets Through a Semantic Transform based on Wikipedia</a>". Springer, Berlin, Heidelberg. DOI: 10.1007/978-3-642-21852-1_55.
