Design of a POS Tagger using Conditional Random Fields for Malayalam

被引：0

作者：

Krishnapriya, V ^{[1
]}

Sreesha, P. ^{[1
]}

Harithalakshmi, T. R. ^{[1
]}

Archana, T. C. ^{[1
]}

Vettath, Jayasree N. ^{[1
]}

机构：

[1] Sreepathy Inst Management & Technol, Dept Comp Sci & Engn, Palakkad, Kerala, India

来源：

2014 First International Conference on Computational Systems and Communications (ICCSC) | 2014年

关键词：

POS tagging; Hidden Markov Model; Stochastic process; CRF; Malayalam;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Parts of Speech tagging, is a process of marking the words in a text as corresponding to a particular part of speech, based on its definition and context. POS tagger plays an important role in Natural language applications like speech recognition, natural language parsing, information retrieval and extraction. This paper discusses architecture for designing a Part-Of-Speech (POS tagger for Malayalam language using Conditional Random Field (CRF). The experiments presented in this paper use an annotated corpus of 1028 sentences (11,315 words) and tagset consists of 100 tags. A trigram based tagging scheme is involved in the experiments. The proposed system is based on an empirical approach that models the human POS tagging processing more realistically than the existing systems, without compromising the efficiency and accuracy.

引用

页码：370 / 373

页数：4

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