Applied Natural Language Processing

Philip M. McCarthy and Scott A. Crossley

The Applied Natural Language Processing track is a forum for researchers working in natural language processing (NLP), computational linguistics (CL), applied linguistics (AL) and related areas. The rapid pace of development in natural language processing in textual studies, speech recognition, speech production, and data mining has led to a revived interest in tools able to understand, organize and extract information from natural language sources. These include the analysis of online materials, most of them in textual form or text combined with other media (visual, audio), the use of innovative human-computer interfaces, such as interactive agents, which benefit from language understanding, and the use of computational tools to facilitate intelligent tutoring systems and instructional methodology. In addition, natural language processing can facilitate human-computer interaction for people with special needs, assist in the organization of classification systems, and coordinate text segmentation. While papers and contributions on traditional issues were welcome, the 2008 special track will emphasize applications by the NLP/CL community, particularly in areas such as multilingual processing, learning environments, multimodal communication, bioNLP, spam filtering, language acquisition, textual assessment, language varieties, materials development, generic classification, and educational applications etc. We also encourage papers in information retrieval, speech processing and machine learning that present actual applications that can benefit from or have an impact on NLP/CL. Typical papers of the track address issues such as the following: NL-based knowledge representations and systems; first and second language acquisition; English for specific purposes; textual assessment indices; syntax; semantics; coreference resolution; word sense disambiguation; text cohesion and coherence; dialogue management and systems; language generation; language models; machine learning applied to NL problems; multilingual processing; NL in learning environments; semantic web, ontologies, reasoning; and applications.

Submitted: Feb 21, 2008

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