short-paper

Hashtag Recommendation Based on Topic Enhanced Embedding, Tweet Entity Data and Learning to Rank

Authors:

Armineh Nourbakhsh,

Rui FangAuthors Info & Claims

CIKM '16: Proceedings of the 25th ACM International on Conference on Information and Knowledge Management

Pages 2085 - 2088

https://doi.org/10.1145/2983323.2983915

Published: 24 October 2016 Publication History

Abstract

In this paper, we present a new approach of recommending hashtags for tweets. It uses Learning to Rank algorithm to incorporate features built from topic enhanced word embeddings, tweet entity data, hashtag frequency, hashtag temporal data and tweet URL domain information. The experiments using millions of tweets and hashtags show that the proposed approach outperforms the three baseline methods -- the LDA topic, the tf.idf based and the general word embedding approaches.

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Cited By

Jafari Sadr MMirtaheri SGreco SBorna K(2023)Popular Tag Recommendation by Neural Network in Social MediaComputational Intelligence and Neuroscience10.1155/2023/43004082023(1-13)Online publication date: 29-May-2023
https://doi.org/10.1155/2023/4300408
Alsini AHuynh DDatta A(2021)Hashtag Recommendation Methods for Twitter and Sina Weibo: A ReviewFuture Internet10.3390/fi1305012913:5(129)Online publication date: 14-May-2021
https://doi.org/10.3390/fi13050129
Najafabadi MNair MMohamed A(2021)Tag recommendation model using feature learning via word embedding2021 IEEE 19th World Symposium on Applied Machine Intelligence and Informatics (SAMI)10.1109/SAMI50585.2021.9378621(000305-000310)Online publication date: 21-Jan-2021
https://doi.org/10.1109/SAMI50585.2021.9378621
Show More Cited By

Index Terms

Hashtag Recommendation Based on Topic Enhanced Embedding, Tweet Entity Data and Learning to Rank
1. Human-centered computing
  1. Collaborative and social computing
    1. Collaborative and social computing theory, concepts and paradigms
      1. Social recommendation
2. Information systems
  1. Information retrieval
    1. Retrieval tasks and goals
      1. Recommender systems
  2. World Wide Web
    1. Web searching and information discovery
      1. Social recommendation

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cover image ACM Conferences

CIKM '16: Proceedings of the 25th ACM International on Conference on Information and Knowledge Management

October 2016

2566 pages

ISBN:9781450340731

DOI:10.1145/2983323

General Chairs:
Snehasis Mukhopadhyay
Indiana University Purdue University Indianapolis, USA
,
ChengXiang Zhai
University of Illinois at Urbana-Champaign, USA
,
Program Chairs:
Elisa Bertino
Purdue University
,
Fabio Crestani
University of Lugano
,
Javed Mostafa
University of North Carolina
,
Jie Tang
Tsinghua University
,
Luo Si
Alibaba Group Inc & Purdue University
,
Xiaofang Zhou
University of Queensland
,
Yi Chang
Yahoo Research
,
Yunyao Li
IBM Research - Almaden
,
Parikshit Sondhi
WalmartLabs

Copyright © 2016 ACM.

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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Published: 24 October 2016

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CIKM'16

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CIKM'16: ACM Conference on Information and Knowledge Management

October 24 - 28, 2016

Indiana, Indianapolis, USA

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CIKM '16 Paper Acceptance Rate 160 of 701 submissions, 23%;

Overall Acceptance Rate 1,861 of 8,427 submissions, 22%

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Cited By

Jafari Sadr MMirtaheri SGreco SBorna K(2023)Popular Tag Recommendation by Neural Network in Social MediaComputational Intelligence and Neuroscience10.1155/2023/43004082023(1-13)Online publication date: 29-May-2023
https://doi.org/10.1155/2023/4300408
Alsini AHuynh DDatta A(2021)Hashtag Recommendation Methods for Twitter and Sina Weibo: A ReviewFuture Internet10.3390/fi1305012913:5(129)Online publication date: 14-May-2021
https://doi.org/10.3390/fi13050129
Najafabadi MNair MMohamed A(2021)Tag recommendation model using feature learning via word embedding2021 IEEE 19th World Symposium on Applied Machine Intelligence and Informatics (SAMI)10.1109/SAMI50585.2021.9378621(000305-000310)Online publication date: 21-Jan-2021
https://doi.org/10.1109/SAMI50585.2021.9378621
Amiri BKarimianghadim RYazdanjue NHossain L(2021)Research topics and trends of the hashtag recommendation domainScientometrics10.1007/s11192-021-03874-6126:4(2689-2735)Online publication date: 1-Apr-2021
https://dl.acm.org/doi/10.1007/s11192-021-03874-6
Hachaj TMiazga J(2020)Image Hashtag Recommendations Using a Voting Deep Neural Network and Associative Rules Mining ApproachEntropy10.3390/e2212135122:12(1351)Online publication date: 30-Nov-2020
https://doi.org/10.3390/e22121351
Yang QWu GLi YLi RGu XDeng HWu J(2020)AMNN: Attention-Based Multimodal Neural Network Model for Hashtag RecommendationIEEE Transactions on Computational Social Systems10.1109/TCSS.2020.29867787:3(768-779)Online publication date: Jun-2020
https://doi.org/10.1109/TCSS.2020.2986778
Little CMclean DCrockett KEdmonds B(2020)A Semantic and Syntactic Similarity Measure for Political TweetsIEEE Access10.1109/ACCESS.2020.30177978(154095-154113)Online publication date: 2020
https://doi.org/10.1109/ACCESS.2020.3017797
Gao JZhang CXu YLuo MNiu Z(2020)Hybrid microblog recommendation with heterogeneous features using deep neural networkExpert Systems with Applications10.1016/j.eswa.2020.114191(114191)Online publication date: Nov-2020
https://doi.org/10.1016/j.eswa.2020.114191
Zhu RYang DLi Y(2019)Learning Improved Semantic Representations with Tree-Structured LSTM for Hashtag Recommendation: An Experimental StudyInformation10.3390/info1004012710:4(127)Online publication date: 6-Apr-2019
https://doi.org/10.3390/info10040127
Wang YSohn SLiu SShen FWang LAtkinson EAmin SLiu H(2019)A clinical text classification paradigm using weak supervision and deep representationBMC Medical Informatics and Decision Making10.1186/s12911-018-0723-619:1Online publication date: 7-Jan-2019
https://doi.org/10.1186/s12911-018-0723-6
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