Name
Abstract | ||
|---|---|---|
Using queries to explore corpora is today routine practice not only among researchers in various fields with an empirical approach to discourse, but also among non-specialists who use search engines or con-cordancers for language learning purposes. While keyword-based queries are quite common , non-specialists are less likely to explore syntactic constructions. Syntax-based queries usually require the use of regular expressions with grammatical words combined with mor-phosyntactic tags, meaning that users need to master both the query language of the tool and the tagset of the annotated corpus. However , non-specialists such as language learners may prefer to focus on the output rather than spend time and efforts mastering a query language. To address this shortcoming, we propose a methodology including a syntactic parser and using common similarity measures to compare sequences of automatically produced morphosyntactic tags. |
Year | Venue | Field |
|---|---|---|
2016 | PACLIC | Regular expression,RDF query language,Query language,Data control language,Computer science,Language acquisition,Corpus linguistics,Natural language processing,Artificial intelligence,Parsing,Syntax |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ilaine Wang | 1 | 0 | 0.68 |
| Sylvain Kahane | 2 | 113 | 30.77 |
| isabelle tellier | 3 | 84 | 20.31 |