42 citations · 79 across the 5 of their papers we have counts for
11 papers
Knowing What, How and Why: A Near Complete Solution for Aspect-based Sentiment Analysis
Haiyun Peng, Lu Xu, Lidong Bing +3
Target-based sentiment analysis or aspect-based sentiment analysis (ABSA) refers to addressing various sentiment analysis tasks at a fine-grained level, which includes but is not l…
Aligning Cross-Lingual Entities with Multi-Aspect Information
Hsiu-Wei Yang, Yanyan Zou, Peng Shi +3
Multilingual knowledge graphs (KGs), such as YAGO and DBpedia, represent entities in different languages. The task of cross-lingual entity alignment is to match entities in a sourc…
Text2Math: End-to-end Parsing Text into Math Expressions
Yanyan Zou, Wei Lu
We propose Text2Math, a model for semantically parsing text into math expressions. The model can be used to solve different math related problems including arithmetic word problems…
Dependency-Guided LSTM-CRF for Named Entity Recognition
Zhanming Jie, Wei Lu
Dependency tree structures capture long-distance and syntactic relationships between words in a sentence. The syntactic relations (e.g., nominal subject, object) can potentially in…
Learning Explicit and Implicit Structures for Targeted Sentiment Analysis
Hao Li, Wei Lu
Targeted sentiment analysis is the task of jointly predicting target entities and their associated sentiment information. Existing research efforts mostly regard this joint task as…
Densely Connected Graph Convolutional Networks for Graph-to-Sequence Learning
Zhijiang Guo, Yan Zhang, Zhiyang Teng +1
We focus on graph-to-sequence learning, which can be framed as transducing graph structures to sequences for text generation. To capture structural information associated with grap…