2.1 Question Search
art techniques usually fail to achieve desired results
due to short questions and information need texts.
Burke et al. (1997) combined a lexical metric and a
simple semantic knowledge-based (WordNet) simi-
In order to measure the similarity between short
texts, we make use of three kinds of text similari-
larity method to retrieve semantically similar ques-
tions from frequently asked question (FAQ) data.
ty measures: TFIDF based, Knowledge based and
Latent Dirichlet Allocation (LDA) based similarity
Jeon et al. (2005a) retrieved semantically similar
measures in this paper. We will compare their per-
questions from Korean CQA data by calculating the
formance for the task of question recommendation
similarity between their answers. The assumption
in the experiment section.
behind their research is that questions with very sim-
ilar answers tend to be semantically similar. Jeon
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