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Character cluster based Thai information retrieval

Authors:

Thanaruk Theeramunkong,

Virach Sornlertlamvanich,

Thanasan Tanhermhong,

Wirat ChinnanAuthors Info & Claims

IRAL '00: Proceedings of the fifth international workshop on on Information retrieval with Asian languages

Pages 75 - 80

https://doi.org/10.1145/355214.355225

Published: 01 November 2000 Publication History

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Abstract

Some languages including Thai, Japanese and Chinese do not have explicit word boundary. This causes the problem of word boundary ambiguity that results in decreasing the accuracy of information retrieval. This paper proposes a new technique so-called character clustering to reduce the ambiguity of word boundary in Thai documents and hence improve searching efficiency. To investigate the efficiency, a set of experiments using Thai newspapers is conducted in both non-indexing and indexing searching approaches. The experimental results show our method outperform the traditional methods in both non-indexing and indexing approaches in all measures.

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Cited By

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Chay-intr TKamigaito HOkumura M(2023)Character-Based Thai Word Segmentation with Multiple AttentionsJournal of Natural Language Processing10.5715/jnlp.30.37230:2(372-400)Online publication date: 2023
https://doi.org/10.5715/jnlp.30.372
Stoilos GPapasarantopoulos NVougiouklis PBansky PZhang ARangwala H(2022)Type Linking for Query Understanding and Semantic SearchProceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining10.1145/3534678.3539067(3931-3940)Online publication date: 14-Aug-2022
https://dl.acm.org/doi/10.1145/3534678.3539067
Sornlertlamvanich VYuenyong S(2022)Thai Named Entity Recognition Using BiLSTM-CNN-CRF Enhanced by TCCIEEE Access10.1109/ACCESS.2022.317520110(53043-53052)Online publication date: 2022
https://doi.org/10.1109/ACCESS.2022.3175201
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Character cluster based Thai information retrieval
1. Information systems
  1. Information retrieval

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Information & Contributors

Information

Published In

IRAL '00: Proceedings of the fifth international workshop on on Information retrieval with Asian languages

November 2000

220 pages

ISBN:1581133006

DOI:10.1145/355214

Chairmen:
Kam-Fai Wong
Chinese Univ. of Hong Kong, Hong Kong, China
,
Dik L. Lee
Hong Kong Univ. of Science and Technology, Hong Kong, China
,
Jong-Hyeok Lee
Pohang Univ. of Science and Technology, Korea

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 November 2000

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IRAL00

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SIGWEB
ACM Hong Kong Chapter
SIGIR
SIGLINK

IRAL00: 5th International Workshop on Information Retrieval with Asia Languages

September 30 - October 1, 2000

Hong Kong, China

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Chay-intr TKamigaito HOkumura M(2023)Character-Based Thai Word Segmentation with Multiple AttentionsJournal of Natural Language Processing10.5715/jnlp.30.37230:2(372-400)Online publication date: 2023
https://doi.org/10.5715/jnlp.30.372
Stoilos GPapasarantopoulos NVougiouklis PBansky PZhang ARangwala H(2022)Type Linking for Query Understanding and Semantic SearchProceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining10.1145/3534678.3539067(3931-3940)Online publication date: 14-Aug-2022
https://dl.acm.org/doi/10.1145/3534678.3539067
Sornlertlamvanich VYuenyong S(2022)Thai Named Entity Recognition Using BiLSTM-CNN-CRF Enhanced by TCCIEEE Access10.1109/ACCESS.2022.317520110(53043-53052)Online publication date: 2022
https://doi.org/10.1109/ACCESS.2022.3175201
Marukatat S(2021)Text generation by probabilistic suffix tree language model2021 16th International Joint Symposium on Artificial Intelligence and Natural Language Processing (iSAI-NLP)10.1109/iSAI-NLP54397.2021.9678167(1-4)Online publication date: 21-Dec-2021
https://doi.org/10.1109/iSAI-NLP54397.2021.9678167
Pasupa KSeneewong Na Ayutthaya T(2021)Hybrid Deep Learning Models for Thai Sentiment AnalysisCognitive Computation10.1007/s12559-020-09770-014:1(167-193)Online publication date: 4-Mar-2021
https://doi.org/10.1007/s12559-020-09770-0
Kedtiwerasak RAdsawinnawanawa EJirakunkanok PKongkachandra R(2019)Thai Keyword Extraction using TextRank Algorithm2019 14th International Joint Symposium on Artificial Intelligence and Natural Language Processing (iSAI-NLP)10.1109/iSAI-NLP48611.2019.9045523(1-6)Online publication date: Oct-2019
https://doi.org/10.1109/iSAI-NLP48611.2019.9045523
NARARATWONG RKERTKEIDKACHORN NCOOHAROJANANONE NOKADA H(2018)Improving Thai Word and Sentence Segmentation Using Linguistic KnowledgeIEICE Transactions on Information and Systems10.1587/transinf.2018EDP7016E101.D:12(3218-3225)Online publication date: 1-Dec-2018
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Lapjaturapit TViriyayudhakom KTheeramunkong T(2018)Multi-Candidate Word Segmentation using Bi-directional LSTM Neural Networks2018 International Conference on Embedded Systems and Intelligent Technology & International Conference on Information and Communication Technology for Embedded Systems (ICESIT-ICICTES)10.1109/ICESIT-ICICTES.2018.8442053(1-6)Online publication date: May-2018
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Phyu MHashimoto K(2017)Burmese word segmentation with Character Clustering and CRFs2017 14th International Joint Conference on Computer Science and Software Engineering (JCSSE)10.1109/JCSSE.2017.8025934(1-6)Online publication date: Jul-2017
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Kongyoung SRugchatjaroen AKosawat K(2017)TLex+: A Hybrid Method Using Conditional Random Fields and Dictionaries for Thai Word SegmentationRecent Advances and Future Prospects in Knowledge, Information and Creativity Support Systems10.1007/978-3-319-70019-9_10(112-125)Online publication date: 2-Dec-2017
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