2015/11/19 by James Cross, Cross, James, Bing Xiang +3
Computer Science · #Advanced Text Analysis Techniques #Computation and Language (cs.CL) #FOS: Computer and information sciences #Natural Language Processing Techniques #Topic Modeling
paper · pdf · doi:10.48550/arxiv.1511.06312
openalex publication_date 2015/11/19 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
We propose two methods of learning vector representations of words and phrases that each combine sentence context with structural features extracted from dependency trees. Using several variations of neural network classifier, we show that these combined methods lead to improved performance when used as input features for supervised term-matching.