Communications of the ACM
Proceedings of the 20th annual international ACM SIGIR conference on Research and development in information retrieval
An algorithm for suffix stripping
Readings in information retrieval
Mapping semantic information in virtual space: dimensions, variance and individual differences
International Journal of Human-Computer Studies - Empirical evaluation of information visualizations
Using part-of-speech patterns to reduce query ambiguity
SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
SETN '02 Proceedings of the Second Hellenic Conference on AI: Methods and Applications of Artificial Intelligence
Compansion: From research prototype to practical integration
Natural Language Engineering
Automatic evaluation of summaries using N-gram co-occurrence statistics
NAACL '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - Volume 1
Semantic knowledge in word completion
Proceedings of the 7th international ACM SIGACCESS conference on Computers and accessibility
Topic modeling in fringe word prediction for AAC
Proceedings of the 11th international conference on Intelligent user interfaces
Semantic term matching in axiomatic approaches to information retrieval
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Predicting sentences using N-gram language models
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
s-grams: Defining generalized n-grams for information retrieval
Information Processing and Management: an International Journal
Unsupervised Multilingual Sentence Boundary Detection
Computational Linguistics
Corpus studies in word prediction
Proceedings of the 9th international ACM SIGACCESS conference on Computers and accessibility
Positional language models for information retrieval
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Exploiting long distance collocational relations in predictive typing
TextEntry '03 Proceedings of the 2003 EACL Workshop on Language Modeling for Text Entry Methods
Natural Language Processing with Python
Natural Language Processing with Python
Semantic-based grouping of search engine results using WordNet
APWeb/WAIM'07 Proceedings of the joint 9th Asia-Pacific web and 8th international conference on web-age information management conference on Advances in data and web management
Click on bake to get cookies: guiding word-finding with semantic associations
Proceedings of the 12th international ACM SIGACCESS conference on Computers and accessibility
n-Gram Statistics for Natural Language Understanding and Text Processing
IEEE Transactions on Pattern Analysis and Machine Intelligence
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
SymbolPath: a continuous motion overlay module for icon-based assistive communication
Proceedings of the 14th international ACM SIGACCESS conference on Computers and accessibility
Semantic disambiguation of non-syntactic and continuous motion text entry for AAC
ACM SIGACCESS Accessibility and Computing
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Most icon-based augmentative and alternative communication (AAC) devices require users to formulate messages in syntactic order in order to produce syntactic utterances. Reliance on syntactic ordering, however, may not be appropriate for individuals with limited or emerging literacy skills. Some of these users may benefit from unordered message formulation accompanied by automatic message expansion to generate syntactically correct messages. Facilitating communication via unordered message formulation, however, requires new methods of prediction. This paper describes a novel approach to word prediction using semantic grams, or "sem-grams," which provide relational information about message components regardless of word order. Performance of four word-level prediction algorithms, two based on sem-grams and two based on n-grams, were compared on a corpus of informal blogs. Results showed that sem-grams yield accurate word prediction, but lack prediction coverage. Hybrid methods that combine n-gram and sem-gram approaches may be viable for unordered prediction in AAC.