A Systematic Mapping Study of Language Features Identification from Large Text Collection

Diellza Nagavci Mati; Jaumin Ajdari; Bujar Raufi; Mentor Hamiti; Besnik Selimi

doi:10.1109/MECO.2019.8760042

A Systematic Mapping Study of Language Features Identification from Large Text Collection

Diellza Nagavci Mati, Jaumin Ajdari, Bujar Raufi, Mentor Hamiti, Besnik Selimi

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Natural Language Processing¹¹Henceforth: NLP is an emerging research area in today's era. The NLP resources are quite useful when it comes to building a machine capable of translating between linguistic pairs - a solution that strives to resolve the language barrier problems. Based on this premise, we are focusing our research on feature identification from large text collections of Albanian language. 'Rule-based' or statistical Part-of-Speech²²Henceforth: POS (POS) taggers are sought to be utilized that would either need considerable time for rule development or a sufficient amount of manually labelled data. In light of this, the impact of this research is based on exploring numerous cases that are conducive to progress and further development of this field. One of the goals of this paper is to conduct a systematic review study; to explore and analyze existing research that seek to target low resources language such as is the case of the Albanian language. According to prior observation of published research conducted since 2015, we are focusing our research on studies that have been published in areas that are relevant to Natural Language Processing. Based on considerable load of related research on this field, it is essential to conduct a review and provide an outline of the research situation as well as current developments in this specific but important field of research.

Original language	English
Title of host publication	2019 8th Mediterranean Conference on Embedded Computing, MECO 2019 - Proceedings
Editors	Radovan Stojanovic, Lech Jozwiak, Budimir Lutovac, Drazen Jurisic
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781728117393
DOIs	https://doi.org/10.1109/MECO.2019.8760042
Publication status	Published - Jun 2019
Externally published	Yes
Event	8th Mediterranean Conference on Embedded Computing, MECO 2019 - Budva, Montenegro Duration: 10 Jun 2019 → 14 Jun 2019

Publication series

Name	2019 8th Mediterranean Conference on Embedded Computing, MECO 2019 - Proceedings

Conference

Conference	8th Mediterranean Conference on Embedded Computing, MECO 2019
Country/Territory	Montenegro
City	Budva
Period	10/06/19 → 14/06/19

Keywords

Algorithms
Chinese Whispers
Clustering
component
Machine Learning
Natural Language Processing
Part-of-Speech

Access to Document

10.1109/MECO.2019.8760042

Cite this

Mati, D. N., Ajdari, J., Raufi, B., Hamiti, M., & Selimi, B. (2019). A Systematic Mapping Study of Language Features Identification from Large Text Collection. In R. Stojanovic, L. Jozwiak, B. Lutovac, & D. Jurisic (Eds.), 2019 8th Mediterranean Conference on Embedded Computing, MECO 2019 - Proceedings Article 8760042 (2019 8th Mediterranean Conference on Embedded Computing, MECO 2019 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/MECO.2019.8760042

Mati, Diellza Nagavci ; Ajdari, Jaumin ; Raufi, Bujar et al. / A Systematic Mapping Study of Language Features Identification from Large Text Collection. 2019 8th Mediterranean Conference on Embedded Computing, MECO 2019 - Proceedings. editor / Radovan Stojanovic ; Lech Jozwiak ; Budimir Lutovac ; Drazen Jurisic. Institute of Electrical and Electronics Engineers Inc., 2019. (2019 8th Mediterranean Conference on Embedded Computing, MECO 2019 - Proceedings).

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title = "A Systematic Mapping Study of Language Features Identification from Large Text Collection",

abstract = "Natural Language Processing11Henceforth: NLP is an emerging research area in today's era. The NLP resources are quite useful when it comes to building a machine capable of translating between linguistic pairs - a solution that strives to resolve the language barrier problems. Based on this premise, we are focusing our research on feature identification from large text collections of Albanian language. 'Rule-based' or statistical Part-of-Speech22Henceforth: POS (POS) taggers are sought to be utilized that would either need considerable time for rule development or a sufficient amount of manually labelled data. In light of this, the impact of this research is based on exploring numerous cases that are conducive to progress and further development of this field. One of the goals of this paper is to conduct a systematic review study; to explore and analyze existing research that seek to target low resources language such as is the case of the Albanian language. According to prior observation of published research conducted since 2015, we are focusing our research on studies that have been published in areas that are relevant to Natural Language Processing. Based on considerable load of related research on this field, it is essential to conduct a review and provide an outline of the research situation as well as current developments in this specific but important field of research.",

keywords = "Algorithms, Chinese Whispers, Clustering, component, Machine Learning, Natural Language Processing, Part-of-Speech",

author = "Mati, {Diellza Nagavci} and Jaumin Ajdari and Bujar Raufi and Mentor Hamiti and Besnik Selimi",

note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 8th Mediterranean Conference on Embedded Computing, MECO 2019 ; Conference date: 10-06-2019 Through 14-06-2019",

year = "2019",

month = jun,

doi = "10.1109/MECO.2019.8760042",

language = "English",

series = "2019 8th Mediterranean Conference on Embedded Computing, MECO 2019 - Proceedings",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

editor = "Radovan Stojanovic and Lech Jozwiak and Budimir Lutovac and Drazen Jurisic",

booktitle = "2019 8th Mediterranean Conference on Embedded Computing, MECO 2019 - Proceedings",

address = "United States",

}

Mati, DN, Ajdari, J, Raufi, B, Hamiti, M & Selimi, B 2019, A Systematic Mapping Study of Language Features Identification from Large Text Collection. in R Stojanovic, L Jozwiak, B Lutovac & D Jurisic (eds), 2019 8th Mediterranean Conference on Embedded Computing, MECO 2019 - Proceedings., 8760042, 2019 8th Mediterranean Conference on Embedded Computing, MECO 2019 - Proceedings, Institute of Electrical and Electronics Engineers Inc., 8th Mediterranean Conference on Embedded Computing, MECO 2019, Budva, Montenegro, 10/06/19. https://doi.org/10.1109/MECO.2019.8760042

A Systematic Mapping Study of Language Features Identification from Large Text Collection. / Mati, Diellza Nagavci; Ajdari, Jaumin; Raufi, Bujar et al.
2019 8th Mediterranean Conference on Embedded Computing, MECO 2019 - Proceedings. ed. / Radovan Stojanovic; Lech Jozwiak; Budimir Lutovac; Drazen Jurisic. Institute of Electrical and Electronics Engineers Inc., 2019. 8760042 (2019 8th Mediterranean Conference on Embedded Computing, MECO 2019 - Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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T1 - A Systematic Mapping Study of Language Features Identification from Large Text Collection

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AU - Ajdari, Jaumin

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AU - Hamiti, Mentor

AU - Selimi, Besnik

PY - 2019/6

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AB - Natural Language Processing11Henceforth: NLP is an emerging research area in today's era. The NLP resources are quite useful when it comes to building a machine capable of translating between linguistic pairs - a solution that strives to resolve the language barrier problems. Based on this premise, we are focusing our research on feature identification from large text collections of Albanian language. 'Rule-based' or statistical Part-of-Speech22Henceforth: POS (POS) taggers are sought to be utilized that would either need considerable time for rule development or a sufficient amount of manually labelled data. In light of this, the impact of this research is based on exploring numerous cases that are conducive to progress and further development of this field. One of the goals of this paper is to conduct a systematic review study; to explore and analyze existing research that seek to target low resources language such as is the case of the Albanian language. According to prior observation of published research conducted since 2015, we are focusing our research on studies that have been published in areas that are relevant to Natural Language Processing. Based on considerable load of related research on this field, it is essential to conduct a review and provide an outline of the research situation as well as current developments in this specific but important field of research.

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KW - Chinese Whispers

KW - Clustering

KW - component

KW - Machine Learning

KW - Natural Language Processing

KW - Part-of-Speech

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DO - 10.1109/MECO.2019.8760042

M3 - Conference contribution

AN - SCOPUS:85073914656

T3 - 2019 8th Mediterranean Conference on Embedded Computing, MECO 2019 - Proceedings

BT - 2019 8th Mediterranean Conference on Embedded Computing, MECO 2019 - Proceedings

A2 - Stojanovic, Radovan

A2 - Jozwiak, Lech

A2 - Lutovac, Budimir

A2 - Jurisic, Drazen

PB - Institute of Electrical and Electronics Engineers Inc.

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Mati DN, Ajdari J, Raufi B, Hamiti M, Selimi B. A Systematic Mapping Study of Language Features Identification from Large Text Collection. In Stojanovic R, Jozwiak L, Lutovac B, Jurisic D, editors, 2019 8th Mediterranean Conference on Embedded Computing, MECO 2019 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2019. 8760042. (2019 8th Mediterranean Conference on Embedded Computing, MECO 2019 - Proceedings). doi: 10.1109/MECO.2019.8760042

A Systematic Mapping Study of Language Features Identification from Large Text Collection

Abstract

Publication series

Conference

Keywords

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