Domain Knowledge

The SCISOR. system is a computer program designed to scan naturally occurring texts in constrained do- mains, extract information, and answer questions about that information. The system currently reads newspapers …...

A significant problem when translating Japanese dialogues into Ger- man is the missing information on number and definiteness in the Japanese analysis output. The integration of the search for such …...

In this paper wc discuss the use of discourse con- text in spoken dialogue systems and argue that the knowledge of the domain, modelled with the help of dialogue topics …...

In this paper, we describe the creation of Chinese zero anaphora resolution rules by performing experiments. The rules were constructed based on the centering model. In the experiments, we selected …...

One major bottleneck in conversational sys- tems is their incapability in interpreting un- expected user language inputs such as out-of- vocabulary words. To overcome this problem, conversational systems must be …...

AbstractWith the growing interest in opinion mining from web data, more works are focused on mining in English and Chinese reviews. Probing into the problem of product opinion mining, this …...

The ALTA shared tasks are programming competitions where all participants attempt to solve the same problem, and the winner is the system with the best results. The 2011 ALTA shared …...

AbstractGiven a controversial issue, argument mining from natural language texts (news papers, and any form of text on the Internet) is extremely challenging: domain knowledge is often required together with …...

AbstractOur ability to understand language often relies on common-sense knowledge ― background information the speaker can assume is known by the reader. Similarly, our comprehension of the language used in …...

AbstractThis paper investigates how to improve performance on information extraction tasks by constraining and sequencing CRF-based approaches. We consider two different relation extraction tasks, both from the medical literature: dependence …...

Topic modeling is an unsupervised method for revealing the hidden semantic structure of a corpus. It has been increasingly widely adopted as a tool in the social sciences, in- cluding …...

AbstractRecently, there has been significant progress in studying neural networks for translating text descriptions into SQL queries under the zero-shot cross-domain setting. Despite achieving good performance on some public benchmarks, …...

The recent advancement of pre-trained Trans- former models has propelled the development of effective text mining models across various biomedical tasks. However, these models are primarily learned on the textual …...

AbstractTo ease the difficulty of argument stance classification, the task of same side stance classification (S3C) has been proposed. In contrast to actual stance classification, which requires a substantial amount …...

AbstractAutomatic summarization methods are efficient but can suffer from low quality. In comparison, manual summarization is expensive but produces higher quality. Can humans and AI collaborate to improve summarization performance? …...

AbstractSpurious correlations are a threat to the trustworthiness of natural language processing systems, motivating research into methods for identifying and eliminating them. However, addressing the problem of spurious correlations requires …...

AbstractIn this paper, we study the effect of commonsense and domain knowledge while generating responses in counseling conversations using retrieval and generative methods for knowledge integration. We propose a pipeline …...

AbstractOptimizing the phrasing of argumentative text is crucial in higher education and professional development. However, assessing whether and how the different claims in a text should be revised is a …...