Vebran Web Services for Corpus Query Expansion

Stanković, Ranka; Utvić, Miloš

doi:10.18485/infotheca.2019.19.2.5

Cited by 1 publication

(2 citation statements)

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“…The existing work in Serbian language corpus can be found in the Literature [2,3,4,5,6,7,8]. Annotation process of contemporary Serbian is described in [2].…”

Section: Related Workmentioning

confidence: 99%

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N-Gram-Based Serbian Text Classification

Prvulović,

Radosavljević,

Vujošević

et al. 2023

Machine Learning Techniques and NLP

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Natural language processing is an active area of research which finds many applications in variety of fields. Low-resource languages are a challenge as they lack curated datasets, stemmers and other elements used in text processing. Statistical approach is an alternative which can be used to bypass lack of rule-based implementations. The paper presents a model for classification of unstructured text in Serbian language. The model uses n-gram-based stemming to create document attributes vectors. Vectors are created on 3-, 4- and 5-grams. Vector reduction is tested on two criteria: n-gram entropy and number of occurrences, and two lengths: 1000 and 2000 n-grams. The support vector machine is used to classify documents. The model is trained and tested on a dataset collected from a Serbian news portal. Classification accuracy of over 80% is achieved. The presented model provides a good basis for range of applications in business decision automation for low-resource languages.

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“…The existing work in Serbian language corpus can be found in the Literature [2,3,4,5,6,7,8]. Annotation process of contemporary Serbian is described in [2].…”

Section: Related Workmentioning

confidence: 99%

“…The existing work in Serbian language corpus can be found in the Literature [2,3,4,5,6,7,8]. Annotation process of contemporary Serbian is described in [2]. The corpus words contain lemma, derivational stem and prefixes, infixes and suffixes.…”

Section: Related Workmentioning

confidence: 99%