  In this work, we focus on effectively leveraging and integrating information
from concept-level as well as word-level via projecting concepts and words into
a lower dimensional space while retaining most critical semantics. In a broad
context of opinion understanding system, we investigate the use of the fused
embedding for several core NLP tasks: named entity detection and
classification, automatic speech recognition reranking, and targeted sentiment
analysis.
