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Combining Local and Global Word Embeddings for Microblog Stemming

Published: 06 November 2017 Publication History

Abstract

Stemming is a vital step employed to improve retrieval performance through efficient unification of morphological variants of a word. We propose an unsupervised, context-specific stemming algorithm for microblogs, based on both local and global word embeddings, which is capable of handling the informal, noisy vocabulary of microblogs. Experiments on two standard microblog data collections (TREC 2016 and FIRE 2016) show that, the proposed stemmer enables significantly better retrieval performance than several state-of-the-art stemming algorithms, for the same queries.

References

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Moumita Basu, Anurag Roy, Kripabandhu Ghosh, Somprakash Bandyopadhyay, and Saptarshi Ghosh. 2017. A Novel Word Embedding Based Stemming Approach for Microblog Retrieval During Disasters. In Proc. ECIR.
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Saptarshi Ghosh and Kripabandhu Ghosh. 2016. Overview of the FIRE 2016 Mi- croblog track: Information Extraction from Microblogs Posted during Disasters. In Proc. FIRE 2016.
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Prasenjit Majumder, Mandar Mitra, Swapan K. Parui, Gobinda Kole, Pabitra Mi- tra, and Kalyankumar Datta. 2007. YASS: Yet another suffix stripper. ACM Trans. Inf. Syst. 25, 4, Article 18 (Oct. 2007).
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Jiaul H. Paik, Mandar Mitra, Swapan K. Parui, and Kalervo Järvelin. 2011. GRAS: An effective and efficient stemming algorithm for information retrieval. ACM Trans. Inf. Syst. 29, 4 (Dec. 2011), 19:1--19:24.
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Jiaul H. Paik, Dipasree Pal, and Swapan K. Parui. 2011. A novel corpus-based stemming algorithm using co-occurrence statistics. In Proc. ACM SIGIR.
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M. F. Porter. 1980. An algorithm for suffix stripping. Program 14, 3 (1980), 130--137.
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Cited By

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  • (2023)A selective approach to stemming for minimizing the risk of failure in information retrieval systemsPeerJ Computer Science10.7717/peerj-cs.11759(e1175)Online publication date: 10-Jan-2023
  • (2023)Microblog Retrieval Based on Concept-Enhanced Pre-Training ModelACM Transactions on Knowledge Discovery from Data10.1145/355231117:3(1-32)Online publication date: 22-Feb-2023
  • (2023)An Analytical Analysis of Text Stemming Methodologies in Information Retrieval and Natural Language Processing SystemsIEEE Access10.1109/ACCESS.2023.333271011(133681-133702)Online publication date: 2023
  • Show More Cited By

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  1. Combining Local and Global Word Embeddings for Microblog Stemming

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    cover image ACM Conferences
    CIKM '17: Proceedings of the 2017 ACM on Conference on Information and Knowledge Management
    November 2017
    2604 pages
    ISBN:9781450349185
    DOI:10.1145/3132847
    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 the author(s) 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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    Published: 06 November 2017

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    Author Tags

    1. glove
    2. microblog
    3. stemming
    4. word embedding
    5. word2vec

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    CIKM '17 Paper Acceptance Rate 171 of 855 submissions, 20%;
    Overall Acceptance Rate 1,861 of 8,427 submissions, 22%

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    Cited By

    View all
    • (2023)A selective approach to stemming for minimizing the risk of failure in information retrieval systemsPeerJ Computer Science10.7717/peerj-cs.11759(e1175)Online publication date: 10-Jan-2023
    • (2023)Microblog Retrieval Based on Concept-Enhanced Pre-Training ModelACM Transactions on Knowledge Discovery from Data10.1145/355231117:3(1-32)Online publication date: 22-Feb-2023
    • (2023)An Analytical Analysis of Text Stemming Methodologies in Information Retrieval and Natural Language Processing SystemsIEEE Access10.1109/ACCESS.2023.333271011(133681-133702)Online publication date: 2023
    • (2023)The Impact of Nostalgia on Brand Resurrection and Iconness: The Importance of Being LocalJournal of Global Marketing10.1080/08911762.2023.224847236:5(396-416)Online publication date: 19-Oct-2023
    • (2022)Neural Network Guided Fast and Efficient Query-Based Stemming by Predicting Term Co-occurrence StatisticsSN Computer Science10.1007/s42979-022-01081-53:3Online publication date: 24-Mar-2022
    • (2021)An Unsupervised Normalization Algorithm for Noisy Text: A Case Study for Information Retrieval and Stance DetectionJournal of Data and Information Quality10.1145/341803613:3(1-25)Online publication date: 27-Apr-2021
    • (2021)Query Expansion With Local Conceptual Word Embeddings in Microblog RetrievalIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2019.294576433:4(1737-1749)Online publication date: 1-Apr-2021
    • (2020)EmHash: Hashtag Recommendation using Neural Network based on BERT Embedding2020 6th International Conference on Web Research (ICWR)10.1109/ICWR49608.2020.9122275(113-118)Online publication date: Apr-2020
    • (2019)Learning Chinese Word Embeddings from Stroke, Structure and Pinyin of CharactersProceedings of the 28th ACM International Conference on Information and Knowledge Management10.1145/3357384.3358005(1011-1020)Online publication date: 3-Nov-2019
    • (2018)A Text Classification Approach using Parallel Naive Bayes in Big Data ContextProceedings of the 12th International Conference on Intelligent Systems: Theories and Applications10.1145/3289402.3289536(1-6)Online publication date: 24-Oct-2018
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