Statistical and Semantic Approaches for Tweet Contextualization-Reference-Cited by-同舟云学术

Statistical and Semantic Approaches for Tweet Contextualization

Published:2015 Issue: Volume:60 Page:498-507
ISSN:1877-0509
Container-title:Procedia Computer Science
language:en
Short-container-title:Procedia Computer Science

Author:

Zingla Meriem Amina,Chiraz Latiri,Slimani Yahya,Berrut Catherine

Publisher

Elsevier BV

Subject

General Engineering

Reference20 articles.

1. Leveraging social relevance: Using social networks to enhance literature access and microblog search;Ben-jabeur,2013

2. Lia@inex2012 : Combinaison de the‘mes latents pour la contextualisation de tweets;Morchid,2013

3. An automatic greedy summarization system at INEX 2013 tweet contextualization track;Linhares;In: Working Notes for CLEF 2013 Conference , Valencia, Spain, September 23-26, 2013.,2013

4. Three statistical summarizers at CLEF-INEX 2013 tweet contextualization track;Torres-Moreno,2014

5. Effective tweet contextualization with hashtags performance prediction and multi-document summarization;Deveaud,2013

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1. Classification of Topics Using Bi-LSTM and CNN with the Feature Expansion on Twitter;2023 IEEE International Conference on Communication, Networks and Satellite (COMNETSAT);2023-11-23

2. Topic Classification Using the Long Short-Term Memory (LSTM) Method with FastText Feature Expansion on Twitter;2023 International Conference on Data Science and Its Applications (ICoDSA);2023-08-09

3. Using a Rich Context Model for Real-Time Big Data Analytics in Twitter;2016 IEEE 4th International Conference on Future Internet of Things and Cloud Workshops (FiCloudW);2016-08