All-In-1 at IJCNLP-2017 Task 4: Short Text Classification with One Model for All Languages

2017-12-01 · IJCNLP 2017 12 · Barbara Plank

We present All-In-1, a simple model for multilingual text classification that does not require any parallel data. It is based on a traditional Support Vector Machine classifier exploiting multilingual word embeddings and character n-grams. Our model is simple, easily extendable yet very effective, overall ranking 1st (out of 12 teams) in the IJCNLP 2017 shared task on customer feedback analysis in four languages: English, French, Japanese and Spanish.

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AllGeneral ClassificationMultilingual text classificationMultilingual Word Embeddingstext-classification Text ClassificationWord Embeddings

ALL-IN-1: Short Text Classification with One Model for All Languages

2017-10-26 · Barbara Plank

We present ALL-IN-1, a simple model for multilingual text classification that does not require any parallel data. It is based on a traditional Support Vector Machine classifier exploiting multilingual word embeddings and…

All General Classification Multilingual text classification Multilingual Word Embeddings+3

Bingo at IJCNLP-2017 Task 4: Augmenting Data using Machine Translation for Cross-linguistic Customer Feedback Classification

2017-12-01 · IJCNLP 2017 12 · Heba Elfardy, Manisha Srivastava, Wei Xiao, Jared Kramer 외

The ability to automatically and accurately process customer feedback is a necessity in the private sector. Unfortunately, customer feedback can be one of the most difficult types of data to work with due to the sheer vo…

Feature Engineering General Classification Machine Translation Sentiment Analysis+3

IJCNLP-2017 Task 4: Customer Feedback Analysis

2017-12-01 · IJCNLP 2017 12 · Chao-Hong Liu, Yasufumi Moriya, Alberto Poncelas, Declan Groves

This document introduces the IJCNLP 2017 Shared Task on Customer Feedback Analysis. In this shared task we have prepared corpora of customer feedback in four languages, i.e. English, French, Spanish and Japanese. They we…

Machine Translation Prediction

NITMZ-JU at IJCNLP-2017 Task 4: Customer Feedback Analysis

2017-12-01 · IJCNLP 2017 12 · Somnath Banerjee, Partha Pakray, Riyanka Manna, Dipankar Das 외

In this paper, we describe a deep learning framework for analyzing the customer feedback as part of our participation in the shared task on Customer Feedback Analysis at the 8th International Joint Conference on Natural …

Text Classification

YNU-HPCC at IJCNLP-2017 Task 4: Attention-based Bi-directional GRU Model for Customer Feedback Analysis Task of English

2017-12-01 · IJCNLP 2017 12 · Nan Wang, Jin Wang, Xue-jie Zhang

This paper describes our submission to IJCNLP 2017 shared task 4, for predicting the tags of unseen customer feedback sentences, such as comments, complaints, bugs, requests, and meaningless and undetermined statements. …

Classification General Classification Question Answering Representation Learning+3