Online abuse detection: the value of preprocessing and neural attention models
Proceedings of the Tenth Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis
We propose an attention-based neural network approach to detect abusive speech in online social networks. Our approach enables more effective modeling of context and the semantic relationships between words. We also empirically evaluate the value of text pre-processing techniques in addressing the challenge of out-of-vocabulary words in toxic content. Finally, we conduct extensive experiments on the Wikipedia Talk page datasets, showing improved predictive power over the previous state-of-the-art.
Annotation of Rhetorical Moves in Biochemistry Articles
Robert E. Mercer
Proceedings of the 6th Workshop on Argument Mining
This paper focuses on the real world application of scientific writing and on determining rhetorical moves, an important step in establishing the argument structure of biomedical articles. Using the observation that the structure of scholarly writing in laboratory-based experimental sciences closely follows laboratory procedures, we examine most closely the Methods section of the texts and adopt an approach of identifying rhetorical moves that are procedure-oriented. We also propose a verb-centric frame semantics with an effective set of semantic roles in order to support the analysis. These components are designed to support a computational model that extends a promising proposal of appropriate rhetorical moves for this domain, but one which is merely descriptive. Our work also contributes to the understanding of argument-related annotation schemes. In particular, we conduct a detailed study with human annotators to confirm that our selection of semantic roles is effective in determining the underlying rhetorical structure of existing biomedical articles in an extensive dataset. The annotated dataset that we produce provides the important knowledge needed for our ultimate goal of analyzing biochemistry articles.
Mixed-initiative translation of Web pages
Proceedings of the Fourth Conference of the Association for Machine Translation in the Americas: Technical Papers
A mixed-initiative system is one which allows more interactivity between the system and user, as the system is reasoning. We present some observations on the task of translating Web pages for users and suggest that a more interactive approach to this problem may be desirable. The aim is to interact with the user who is requesting the translation and the challenge is to determine the circumstances under which the user should be able to take the initiative to direct the processing or the system should be able to take the initiative to solicit further input from the user. In fact, we envision a need to support interactive translation of Web pages as the World Wide Web becomes more accessible to people with varying needs and abilities throughout the world.
Resolving Plan Ambiguity for Response Generation
Peter van Beek
Proceedings of the Fifth International Workshop on Natural Language Generation
On the Relationship Between User Models and Discourse Models
Computational Linguistics, Volume 14, Number 3, September 1988
Book Reviews: Reasoning and Discourse Processes
Computational Linguistics, Volume 14, Number 4, December 1988, LFP: A Logic for Linguistic Descriptions and an Analysis of its Complexity
Analyzing the Structure of Argumentative Discourse
Computational Linguistics, Formerly the American Journal of Computational Linguistics, Volume 13, Numbers 1-2, January-June 1987
A Computational Theory of the Function of Clue Words in Argument Understanding
10th International Conference on Computational Linguistics and 22nd Annual Meeting of the Association for Computational Linguistics
Investigation of Processing Strategies for the Structural Analysis of Arguments
19th Annual Meeting of the Association for Computational Linguistics