This paper describes in detail the combination of NLP methods applied to the treatment of logic forms in the topic processing and statistical methods applied to the search engine ...
We propose an online topic model for sequentially analyzing the time evolution of topics in document collections. Topics naturally evolve with multiple timescales. For example, so...
Unsupervised word representations are very useful in NLP tasks both as inputs to learning algorithms and as extra word features in NLP systems. However, most of these models are b...
Eric H. Huang, Richard Socher, Christopher D. Mann...
Word importance discrimination is a task deserving attention when one treats a topic from TREC where a topic is quite long. The goal of the process is to estimate importance of wo...