Aspect-based sentiment analysis (ABSA) means to identify fine-grained aspects, opinions,
and sentiment polarities. Recent ABSA research focuses on utilizing multi-task learning …

In bridge health monitoring (BHM), crack identification and width measurement are two of
the most important indices for evaluating the functionality of bridges. In order to reduce the …

Part-of-speech information is a pre-requisite in many NLP algorithms. However, Twitter text
is difficult to part-of-speech tag: it is noisy, with linguistic errors and idiosyncratic style. We …

The lack of Chinese sentiment corpora limits the research progress on Chinese sentiment
classification. However, there are many freely available English sentiment corpora on the …

We present a simple, but surprisingly effective, method of self-training a twophase parser-
reranker system using readily available unlabeled data. We show that this type of …

Conditional random fields (Lafferty et al., 2001) are quite effective at sequence labeling
tasks like shallow parsing (Sha and Pereira, 2003) and namedentity extraction (McCallum …

This paper investigates the application of cotraining and self-training to word sense
disambiguation. Optimal and empirical parameter selection methods for co-training and self …

We evaluate the character-level translation method for neural semantic parsing on a large
corpus of sentences annotated with Abstract Meaning Representations (AMRs). Using a …

A conventional approach to learning object detectors uses fully supervised learning
techniques which assumes that a training image set with manual annotation of object …

Computational syntactic processing is a fundamental technique in natural language
processing. It normally serves as a pre-processing method to transform natural language …