Path: Top -> Journal -> Jurnal Internasional -> King Saud University -> 2021 -> Volume 33, Issue 4, May
Development of Sindhi text corpus
Oleh : Mazhar Ali Dootio, Asim Imdad Wagan, King Saud University
Dibuat : 2022-02-12, dengan 0 file
Keyword : Text corpus, NLP, Sindhi, DTM, TF-IDF
Url : http://www.sciencedirect.com/science/article/pii/S1319157818311649
Sumber pengambilan dokumen : web
Sindhi language is a rich language with plenty of literary and general texts. There are number of books, newspapers, magazines and internet material available to develop Sindhi text corpus but yet proper and useful text corpus could not be developed and presented online for research, language features analysis, linguistics analysis and information retrieval systems. The lack of resources for research on computational linguistics and NLP applications for Sindhi language are challenging tasks at this stage. However, we have developed Sindhi text corpora in order to provide text resources to computational linguists, Natural Languages process (NLP) experts and researchers. Online books, newspapers, magazines, blogs and social websites are utilized to build Sindhi text corpus. Sindhi sentiment based text corpus is developed and analyzed with Document Term Matrix and TF-IDF models using 2-gram technique of n-gram model. The corpus may be useful for research on language variation analysis, sentiment analysis, aspect based sentiment analysis, semantic analysis, machine translation, information retrieval, Word2Vec, topic modeling and cluster analysis.
Deskripsi Alternatif :Sindhi language is a rich language with plenty of literary and general texts. There are number of books, newspapers, magazines and internet material available to develop Sindhi text corpus but yet proper and useful text corpus could not be developed and presented online for research, language features analysis, linguistics analysis and information retrieval systems. The lack of resources for research on computational linguistics and NLP applications for Sindhi language are challenging tasks at this stage. However, we have developed Sindhi text corpora in order to provide text resources to computational linguists, Natural Languages process (NLP) experts and researchers. Online books, newspapers, magazines, blogs and social websites are utilized to build Sindhi text corpus. Sindhi sentiment based text corpus is developed and analyzed with Document Term Matrix and TF-IDF models using 2-gram technique of n-gram model. The corpus may be useful for research on language variation analysis, sentiment analysis, aspect based sentiment analysis, semantic analysis, machine translation, information retrieval, Word2Vec, topic modeling and cluster analysis.
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