Další formáty:
BibTeX
LaTeX
RIS
@inproceedings{1364281, author = {Měchura, Michal}, address = {Brno}, booktitle = {Proceedings of Recent Advances in Slavonic Natural Language Processing, RASLAN 2016}, editor = {Aleš Horák, Pavel Rychlý, Adam Rambousek}, keywords = {e-lexicography; dictionary writing systems; placement of multi-word items in dictionaries; bilingual dictionary reversal}, howpublished = {tištěná verze "print"}, language = {eng}, location = {Brno}, isbn = {978-80-263-1095-2}, pages = {97-104}, publisher = {Tribun EU}, title = {Data Structures in Lexicography: from Trees to Graphs}, url = {http://nlp.fi.muni.cz/raslan/2016/paper04-Mechura.pdf}, year = {2016} }
TY - JOUR ID - 1364281 AU - Měchura, Michal PY - 2016 TI - Data Structures in Lexicography: from Trees to Graphs PB - Tribun EU CY - Brno SN - 9788026310952 KW - e-lexicography KW - dictionary writing systems KW - placement of multi-word items in dictionaries KW - bilingual dictionary reversal UR - http://nlp.fi.muni.cz/raslan/2016/paper04-Mechura.pdf N2 - In lexicography, a dictionary entry is typically encoded in XML as a tree: a hierarchical data structure of parent-child relations where every element has at most one parent. This choice of data structure makes some aspects of the lexicographer’s work unnecessarily difficult, from deciding where to place multi-word items to reversing an entire bilingual dictionary. This paper proposes that these and other notorious areas of difficulty can be made easier by remodelling dictionaries as graphs rather than trees. However, unlike other authors who have proposed a radical departure from tree structures and whose proposals have remained largely unimplemented, this paper proposes a conservative compromise in which existing tree structures become augmented with specific types of inter-entry relations designed to solve specific problems. ER -
MĚCHURA, Michal. Data Structures in Lexicography: from Trees to Graphs. In Aleš Horák, Pavel Rychlý, Adam Rambousek. \textit{Proceedings of Recent Advances in Slavonic Natural Language Processing, RASLAN 2016}. Brno: Tribun EU, 2016, s.~97-104. ISBN~978-80-263-1095-2.
|