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Combined Machine-Learning Approach to PoS-Tagging of Middle English Corpora

Raoul Karimov, Chelyabinsk State University
2018 Crossroads A Journal of English Studies  
Whereas PoS-tagging in general is now considered a solved problem for Modern English and is mainly achieved via hidden Markov models (HMM) and matrix-based word-to-vector conversions with every word in  ...  As such, we believe that Middle English could be better handled by a morphographemic encoding and instance-based machine learning algorithms like SVM, random forests, kNN, etc.  ...  With that in mind, we decided to find a way to automate the process of PoS-tagging by applying existing machine learning methodology.  ... 
doi:10.15290/cr.2018.21.2.04 fatcat:3wxatuco7bf5zl3hnwaajm2lcm

Part of speech tagging: a systematic review of deep learning and machine learning approaches

Alebachew Chiche, Betselot Yitagesu
2022 Journal of Big Data  
Recently, Deep learning (DL) and Machine learning (ML)-based POS taggers are being implemented as potential solutions to efficiently identify words in a given sentence across a paragraph.  ...  A comprehensive review of the latest POS tagging articles is provided by discussing the weakness and strengths of the proposed approaches.  ...  Keyword Rule based A rule-based approach for POS tagging uses hand-crafted rules to assign tags to words in a sentence.  ... 
doi:10.1186/s40537-022-00561-y fatcat:fpmxdnm76benxms6wckwiqykpy

Machine Learning Approaches for Amharic Parts-of-speech Tagging [article]

Ibrahim Gashaw, H L. Shashirekha
2020 arXiv   pre-print
The aim of this work is to improve POS tagging performance for the Amharic language, which was never above 91%.  ...  retrieval, information processing, parsing, question answering, and machine translation.  ...  Statistical/Machine Learning approaches: These approaches use frequency or probability to tag words in a text.  ... 
arXiv:2001.03324v1 fatcat:bp7xuo444jdkhoc26w47n2fgv4

Entity Extraction from Social Media Text Indian Languages (ESM-IL)

Chintak Mandalia, Memon Mohammed Rahil, Manthan Raval, Sandip Modha
2015 Forum for Information Retrieval Evaluation  
NER in Hindi by aggregating approaches such as Rule based CRF suite and for tagging RDRpostagger and geniatagger.  ...  NER is the process to detect Named Entities (NEs) in a document and to categorize them into certain Named entity classes such as the name of organization, person, location, sport, river, city, country,  ...  We have used Machine learning based approach to perform NER task for given data, because it is more efficient than rule-based approach and it is more frequently used.  ... 
dblp:conf/fire/MandaliaRRM15 fatcat:kggo5dlbyffujodzrs5onz2ojm

Development of Part of Speech Tagger using Deep Learning

2019 International Journal of Engineering and Advanced Technology  
In this paper we have shown the development of POS tagging using neural approach.  ...  POS Tagging is sequence labelling task in which we assign Part-of-speech to every word (Wi) which is sequence in sentence and tag (Ti) to corresponding word as label such as (Wi/Ti.... Wn/Tn).  ...  Gupta et al. [30] developed a POS tagger for Urdu using machine learning approach.  ... 
doi:10.35940/ijeat.a1531.109119 fatcat:d2n3vj47hzbqlb2soll43t7mxy

An Experimental Study on Vietnamese POS Tagging

Oanh Thi Tran, Cuong Anh Le, Thuy Quang Ha, Quynh Hoang Le
2009 2009 International Conference on Asian Language Processing  
To verify the effectiveness of these features, we use three powerful machine learning techniques -MEM, CRF and SVM.  ...  In this paper, we present an experimental study on Vietnamese POS tagging.  ...  Many machine learning methods have been applied for POS tagging. Ratnaparkhi [9] proposed Maximum entropy model for English POS tagger.  ... 
doi:10.1109/ialp.2009.14 dblp:conf/ialp/TranLHL09 fatcat:zakmjjezsre6vcwydxrstjml2q

Analysis of users' Sentiments from Kannada Web Documents

K. M. Anil Kumar, N. Rajasimha, Manovikas Reddy, A. Rajanarayana, Kewal Nadgir
2015 Procedia Computer Science  
We found the average accuracy of machine learning approaches to be better than the average accuracy of semantic learning approaches for Kannada data set.  ...  We have explored the usefulness of semantic approaches and machine learning approaches, used predominately on English language data set, from Kannada web documents.  ...  Evaluation results of (a) Semantic approaches; (b) Machine learning approaches. training and testing dataset, which we used to split our dataset into two equal halves, one for training and the other for  ... 
doi:10.1016/j.procs.2015.06.029 fatcat:7pnqpb2i3fcuxlsts6boyv3rcq

Part of Speech Tagging in Urdu: Comparison of Machine and Deep Learning Approaches

Wahab Khan, Ali Daud, Khairullah Khan, Jamal Abdul Nasir, Mohammed Basheri, Naif Aljohani, Fahd S. Alotaibi
2019 IEEE Access  
However, in the current study, we offer: 1) the implementation of both machine and deep learning models for Urdu POS tagging task with well-balanced language-independent feature set and 2) to highlight  ...  In this research, we demonstrated the effectiveness of machine learning and deep learning models for Urdu POS task.  ...  The ongoing paramount method for covering POS task is supervised machine learning approach.  ... 
doi:10.1109/access.2019.2897327 fatcat:ebxykydphfgqpksolb2gwppbpu

POS Tagging of Hindi-English Code Mixed Text from Social Media: Some Machine Learning Experiments

Royal Sequiera, Monojit Choudhury, Kalika Bali
2015 International Conference on Natural Language Processing  
We propose extensions to the existing approaches, we also present a new feature set which addresses the transliteration problem inherent in social media.  ...  We show that the context and joint modeling of language detection and POS tag layers do not help in POS tagging.  ...  We are also grateful to Rafiya Begum, MSR India for her help with reviewing the annotations.  ... 
dblp:conf/icon-nlp/SequieraCB15 fatcat:mjhc5z2jqff6beqsvu43w364qm

POS Tagging in Amazighe Using Support Vector Machines and Conditional Random Fields [chapter]

Mohamed Outahajala, Yassine Benajiba, Paolo Rosso, Lahbib Zenkouar
2011 Lecture Notes in Computer Science  
We have used state-of-art supervised machine learning approaches to build our POS-tagging models.  ...  The aim of this paper is to present the first Amazighe POS tagger.  ...  We would like to thank all IRCAM researchers for their valuable assistance.  ... 
doi:10.1007/978-3-642-22327-3_28 fatcat:qazruempt5hinlgyaddkjhd7gu

Joint Part-of-Speech Tagging and Named Entity Recognition Using Factor Graphs [chapter]

György Móra, Veronika Vincze
2012 Lecture Notes in Computer Science  
We present a machine learning-based method for jointly labeling POS tags and named entities. This joint labeling is performed by utilizing factor graphs.  ...  Using the feature sets of SZTENER and the POS-tagger magyarlanc, we built a model that is able to outperform both of the original taggers.  ...  Joint Labeling Approaches Different labeling tasks (such as POS tagging, chunking, NER) are usually performed in sequential steps and are defined as separate machine learning problems.  ... 
doi:10.1007/978-3-642-32790-2_28 fatcat:yriil7cqqjarndye4bsqmv7ryq

Part of Speech Tagging of Marathi Text Using Trigram Method

Jyoti Singh, Nisheeth Joshi, Iti Mathur
2013 International Journal of Advanced Information Technology  
The main concept of trigram is to explore the most likely POS for a token based on given information of previous two tags by calculating probabilities to determine which is the best sequence of a tag.  ...  The general approach used for development of tagger is statistical using trigram Method.  ...  In this paper they described a machine learning algorithm for Gujarati Part of Speech Tagging.This paper shows a machine learning algorithm for Gujarati Part of Speech Tagging.  ... 
doi:10.5121/ijait.2013.3203 fatcat:36seszs5m5btpedaj6k3ntolui

Natural Language Processing Tools for Tamil Grammar Learning and Teaching

V Dhanalakshmi, S Rajendran
2010 International Journal of Computer Applications  
Interlinking the computer to the language through Natural language Processing (NLP) paves a way to solve this problem.  ...  The innovative NLP applications are used to generate language learning and teaching tools which enhance the teaching and learning of Grammar.  ...  The capability for a tool to automatically POS tag and chunk a sentence is very essential for further analysis in many approaches to the field of NLP.  ... 
doi:10.5120/1314-1790 fatcat:oupplfz5ubc65fuilgqr2bnmo4

Analysis of implemented part of speech tagger approaches: The case of Ethiopian languages

Wubetu Barud Demilie, Department of Information Technology, Wachemo University, Hossana, Ethiopia, P.O. Box 667
2020 Indian Journal of Science and Technology  
The cycle takes a word or a sentence as information allocates a POS tag to the word or each word in the sentence and creates the labeled content as yield (3) (4) .  ...  Part of Speech (POS) tagging POS tagging means assigning labeling implies appointing linguistic classes for example suitable POS labels to each word in normal language messages and sentences.  ...  Acknowledgment The author wants to acknowledge all researchers of the area who have been contributed a lot regardless of POS tagging research work for Ethiopian languages.  ... 
doi:10.17485/ijst/v13i48.1876 fatcat:hpsvixt5tnamplkuk2niyfn2lu

Yunshan Cup 2020: Overview of the Part-of-Speech Tagging Task for Low-resourced Languages [article]

Yingwen Fu and Jinyi Chen and Nankai Lin and Xixuan Huang and Xinying Qiu and Shengyi Jiang
2022 arXiv   pre-print
The methods of participants ranged from feature-based to neural networks using either classical machine learning techniques or ensemble methods.  ...  There were two tasks for this track: (1) POS tagging for the Indonesian language, and (2) POS tagging for the Lao tagging.  ...  POS tagging is the process of assigning a particular POS to a word based on both its definition and its context.  ... 
arXiv:2204.02658v1 fatcat:gny3dfxkdfdilobdptdvlha6v4
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