We built "topic-label" database over the last two data sets by our OLLDA algorithm.
for CONF, we trained OLLDA over the data from CIKM2013 to obtain probability distributions with labels as test queries, and trained OLLDA over the remaining data as "topic-label" database; for TW, to increase the number of points with same labels in a probability vector set, we split the dataset into 12 pieces according to the time order, and trained separately OLLDA over the 1 th ∼ 11 th pieces as "topic-label" database, and over the 12 th piece as test queries.