Dynamic N-Gram System Based on an Online Croatian Spellchecking Service. Gledec, G., Soic, R., & Dembitz, S. IEEE ACCESS, 7:149988–149995, 2019. Place: 445 HOES LANE, PISCATAWAY, NJ 08855-4141 USA Publisher: IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC Type: Article
doi  abstract   bibtex   
As an infrastructure able to accelerate the development of natural language processing applications, large-scale lexical n-gram databases are at present important data systems. However, deriving such systems for world minority languages as it was done in the Google n-gram project leads to many obstacles. This paper presents an innovative approach to large-scale n-gram system creation applied to the Croatian language. Instead of using the Web as the worlds largest text repository, our process of n-gram collection relies on the Croatian online academic spellchecker \textlessitalic\textgreaterHascheck\textless/italic\textgreater, a language service publicly available since 1993 and popular worldwide. Our n-gram filtering is based on dictionary criteria, contrary to the publicly available Google n-gram systems in which cutoff criteria were applied. After 12 years of collecting, the size of the Croatian n-gram system reached the size of the largest Google Version 1 n-gram systems. Due to reliance on a service in constant use, the Croatian n-gram system is a dynamic one. System dynamics allowed modeling of n-gram count behavior through Heaps law, which led to interesting results. Like many minority languages, the Croatian language suffers from a lack of sophisticated language processing systems in many application areas. The importance of a rich lexical n-gram infrastructure for rapid breakthroughs in new application areas is also exemplified in the paper.
@article{gledec_dynamic_2019,
	title = {Dynamic {N}-{Gram} {System} {Based} on an {Online} {Croatian} {Spellchecking} {Service}},
	volume = {7},
	issn = {2169-3536},
	doi = {10.1109/ACCESS.2019.2947898},
	abstract = {As an infrastructure able to accelerate the development of natural language processing applications, large-scale lexical n-gram databases are at present important data systems. However, deriving such systems for world minority languages as it was done in the Google n-gram project leads to many obstacles. This paper presents an innovative approach to large-scale n-gram system creation applied to the Croatian language. Instead of using the Web as the worlds largest text repository, our process of n-gram collection relies on the Croatian online academic spellchecker {\textless}italic{\textgreater}Hascheck{\textless}/italic{\textgreater}, a language service publicly available since 1993 and popular worldwide. Our n-gram filtering is based on dictionary criteria, contrary to the publicly available Google n-gram systems in which cutoff criteria were applied. After 12 years of collecting, the size of the Croatian n-gram system reached the size of the largest Google Version 1 n-gram systems. Due to reliance on a service in constant use, the Croatian n-gram system is a dynamic one. System dynamics allowed modeling of n-gram count behavior through Heaps law, which led to interesting results. Like many minority languages, the Croatian language suffers from a lack of sophisticated language processing systems in many application areas. The importance of a rich lexical n-gram infrastructure for rapid breakthroughs in new application areas is also exemplified in the paper.},
	language = {English},
	journal = {IEEE ACCESS},
	author = {Gledec, Gordan and Soic, Renato and Dembitz, Sandor},
	year = {2019},
	note = {Place: 445 HOES LANE, PISCATAWAY, NJ 08855-4141 USA
Publisher: IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Type: Article},
	keywords = {Biological system modeling, Croatian language, Dictionaries, Google, Heaps' law, Licenses, Linguistics, Natural language processing, Tools, language modeling, lexical n-gram, n-gram system comparison},
	pages = {149988--149995},
}

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