@inbook {12400,
	title = {Collecting Semantic Similarity Ratings to Connect Concepts in Assistive Communication Tools},
	booktitle = {Modeling, Learning, and Processing of Text Technological Data StructuresModeling, Learning, and Processing of Text Technological Data Structures},
	series = {Studies in Computational Intelligence},
	volume = {370},
	year = {2012},
	month = {2012///},
	pages = {81 - 93},
	publisher = {Springer Berlin / Heidelberg},
	organization = {Springer Berlin / Heidelberg},
	abstract = {To compensate for the common inability of people with lexical production impairments to access and express intended concepts, we make use of models of human semantic memory that build on the notion of semantic similarity and relatedness. Such models, constructed on evidence gained from psycholinguistic experiments, form the basis of a large lexical database, WordNet . We augment WordNet with many additional links among words and concepts that are semantically related. Making this densely connected semantic network available to people with anomic aphasia through assistive technologies should enable them to navigate among related words and concepts and retrieve the words that they intend to express.},
	isbn = {978-3-642-22612-0},
	url = {http://dx.doi.org/10.1007/978-3-642-22613-7_5},
	author = {Nikolova,Sonya and Jordan Boyd-Graber and Fellbaum,Christiane},
	editor = {Mehler,Alexander and K{\"u}hnberger,Kai-Uwe and Lobin,Henning and L{\"u}ngen,Harald and Storrer,Angelika and Witt,Andreas}
}
