Techniques for automatically correcting words in text
ACM Computing Surveys (CSUR)
Foundations of statistical natural language processing
Foundations of statistical natural language processing
Using Natural-Language Processing to Produce Weather Forecasts
IEEE Expert: Intelligent Systems and Their Applications
The mathematics of statistical machine translation: parameter estimation
Computational Linguistics - Special issue on using large corpora: II
Spelling and grammar correction for danish in SCARRIE
ANLC '00 Proceedings of the sixth conference on Applied natural language processing
Generation that exploits corpus-based statistical knowledge
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 1
From detection/correction to computer aided writing
COLING '92 Proceedings of the 14th conference on Computational linguistics - Volume 3
GramCheck: a grammar and style checker
COLING '96 Proceedings of the 16th conference on Computational linguistics - Volume 1
COLING '02 Proceedings of the 19th international conference on Computational linguistics - Volume 1
Generating basic skills reports for low-skilled readers*
Natural Language Engineering
Intelligent computer assisted blog writing system
Expert Systems with Applications: An International Journal
Using Wikipedia concepts and frequency in language to extract key terms from support documents
Expert Systems with Applications: An International Journal
ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part V
Hi-index | 12.05 |
In this paper, we designed and implemented a computer assisted writing system and the application domain is love letter. The system includes text generation module, synonym substitution module and simile expression module. A text generation model is proposed based on keyword generation model and sentence generation model. The keyword generation model extracts important keywords from the corpus and they will become the backbone of the template. Meanwhile, the sentences between keywords will construct the content of the template and candidate sentences are retrieved from the corpus based on statistical analysis. Synonym substitution and simile expression are two modules that could enrich the content of the text. Synonym terms are retrieved from the Internet and a simile expressions discovery mechanism is proposed to collect related simile expressions. The prototype system has shown that it could work well on love letter application domain and the concept of this research could be extended to another domain with minor modification.