Summarizing scientific articles: experiments with relevance and rhetorical status
Computational Linguistics - Summarization
Interface design for metadata creation
CHI '03 Extended Abstracts on Human Factors in Computing Systems
An efficient method for determining bilingual word classes
EACL '99 Proceedings of the ninth conference on European chapter of the Association for Computational Linguistics
Quantifying the accuracy of relational statements in Wikipedia: a methodology
Proceedings of the 6th ACM/IEEE-CS joint conference on Digital libraries
TANGO: bilingual collocational concordancer
ACLdemo '04 Proceedings of the ACL 2004 on Interactive poster and demonstration sessions
Bidirectional inference with the easiest-first strategy for tagging sequence data
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Improving "email speech acts" analysis via n-gram selection
ACTS '09 Proceedings of the HLT-NAACL 2006 Workshop on Analyzing Conversations in Text and Speech
| Hi-index | 0.00 |
Various writing assistance tools have been developed through efforts in the areas of natural language processing with different degrees of success of curriculum integration depending on their functional rigor and pedagogical designs. In this paper, we developed a system, WriteAhead, that provides six types of suggestions when non-native graduate students of English from different disciplines are composing journal abstracts, and assessed its effectiveness. The method involved automatically building domain-specific corpora of abstracts from the Web via domain names and related keywords as query expansions, and automatically extracting vocabulary and n-grams from the corpora in order to offer writing suggestions. At runtime, learners' input in the writing area of the system actively triggered a set of corresponding writing suggestions. This abstract writing assistant system facilitates interactions between learners and the system for writing abstracts in an effective and contextualized way, by providing suggestions such as collocations or transitional words. For assessment of WriteAhead, we compared the writing performance of two groups of students with or without using the system, and adopted student perception data. Findings show that the experiment group wrote better, and most students were satisfied with the system concerning most suggestion types, as they can effectively compose quality abstracts through provided language supports from WriteAhead.