Machine learning approach to automated correction of LATEX documents
| Autor: | Kirill Chuvilin |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2016 |
| Předmět: | |
| Zdroj: | Proceedings of the XXth Conference of Open Innovations Association FRUCT, Vol 664, Iss 18, Pp 33-40 (2016) |
| Druh dokumentu: | article |
| ISSN: | 2305-7254 2343-0737 |
| DOI: | 10.1109/FRUCT-ISPIT.2016.7561505 |
| Popis: | The problem is the automatic synthesis of formal correcting rules for LATEX documents. Each document is represented as a syntax tree. Tree node mappings of initial documents to edited documents form the training set, which is used to generate the rules. Rules with a simple structure, which implement removal, insertion or replacing operations of single node and use linear sequence of nodes to select a position are synthesized primarily. The constructed rules are grouped based on the positions of applicability and quality. The rules that use tree-like structure of nodes to select the position are studied. The changes in the quality of the rules during the sequential increase of the training document set are analyzed. |
| Databáze: | Directory of Open Access Journals |
| Externí odkaz: |
|