Name
Abstract | ||
|---|---|---|
It is challenging to search a dictionary consisting of thousands of entries in order to select appropriate words for building written communication. This is true both for people trying to communicate in a foreign language who have not developed a full vocabulary, for school children learning to write, for authors who wish to be more precise and expressive, and especially for people with lexical access disorders. We make vocabulary navigation and word finding easier by augmenting a basic vocabulary with links between words based on human judgments of semantic similarity. In this paper, we report the results from a user study evaluating how our system named ViVA performs compared to a widely used assistive vocabulary in which words are organized hierarchically into common categories. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1145/1719970.1720031 | IUI |
Keywords | Field | DocType |
semantic similarity,semantic network,semantic networks,foreign language | Semantic similarity,World Wide Web,Lexical access,Computer science,Semantic network,Visual vocabularies,Artificial intelligence,Natural language processing,Vocabulary,Foreign language | Conference |
Citations | PageRank | References |
6 | 0.78 | 3 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sonya S. Nikolova | 1 | 80 | 8.84 |
| Xiaojuan Ma | 2 | 325 | 49.27 |
| Marilyn Tremaine | 3 | 387 | 64.54 |
| Perry R. Cook | 4 | 2102 | 222.10 |