2 papers
cs.LG2016
Sentence Level Recurrent Topic Model: Letting Topics Speak for Themselves
Fei Tian, Bin Gao, Di He +1
We propose Sentence Level Recurrent Topic Model (SLRTM), a new topic model that assumes the generation of each word within a sentence to depend on both the topic of the sentence an…
cs.CL2015
Learning Better Word Embedding by Asymmetric Low-Rank Projection of Knowledge Graph
Fei Tian, Bin Gao, Enhong Chen +1
Word embedding, which refers to low-dimensional dense vector representations of natural words, has demonstrated its power in many natural language processing tasks. However, it may…