Text Processing Application for Indonesian Documents

Prihatini, Putu Manik; Suryawan, I Ketut Dedy

doi:10.1166/asl.2017.10598

Cited by 1 publication

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“…Filtering is a process to remove stop words such as prepositions, conjunctions, and words that are not meaningful. At the previous research, had been produced a list of 906 stop words that used in this research [24].…”

Section: Pre-processing Of Datamentioning

confidence: 99%

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Fuzzy-Gibbs latent Dirichlet allocation model for feature extraction on Indonesian documents

Prihatini¹,

Putra²,

Giriantari³

et al. 2017

ces

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Latent Dirichlet Allocation is a topic-based feature extraction method that uses reasoning to find semantic relationship in corpus. Although Latent Dirichlet Allocation is very powerful in handling very large data sets, but it has a very high complexity along with increasing number of document to reach convergence. Latent Dirichlet Allocation generates probability for all topics in a document, which it contains uncertainty, so its relationship with number of iterations needs to be analyzed. In this paper, Latent Dirichlet Allocation modified by adding fuzzy logic in Gibbs sampling inference algorithm. Its purpose is to analyze the effect of fuzzy logic in handling uncertainty of the occurrence all topics in a document that affect number of iteration in reasoning. Fuzzy-Gibbs Latent Dirichlet Allocation algorithm is implemented on text data of Indonesian documents. Testing performed on three different sizes of data to determine the effect of the number of document to the number of iteration. The algorithm performance was also measured using Perplexity, Precision, Recall and F-Measure.

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Section: Pre-processing Of Datamentioning

confidence: 99%

“…This process requires a dictionary of basic word and rules for prefixes-suffixes. At the previous research, had been produced a list of 30.342 basic words and five rules of prefixes and suffixes that used in this research [24].…”

Section: Pre-processing Of Datamentioning

confidence: 99%