Question Similarity

15 papers with code • 1 benchmarks • 1 datasets

This is the problem of detecting duplicate questions in forums, which is an important step towards automating the process of answering new questions

Datasets


Latest papers with no code

Sieg at MEDIQA 2019: Multi-task Neural Ensemble for Biomedical Inference and Entailment

no code yet • WS 2019

This paper presents a multi-task learning approach to natural language inference (NLI) and question entailment (RQE) in the biomedical domain.

MappSent at IJCNLP-2017 Task 5: A Textual Similarity Approach Applied to Multi-choice Question Answering in Examinations

no code yet • IJCNLP 2017

In this paper we present MappSent, a textual similarity approach that we applied to the multi-choice question answering in exams shared task.

An Exploration of Data Augmentation and RNN Architectures for Question Ranking in Community Question Answering

no code yet • IJCNLP 2017

The automation of tasks in community question answering (cQA) is dominated by machine learning approaches, whose performance is often limited by the number of training examples.

MappSent: a Textual Mapping Approach for Question-to-Question Similarity

no code yet • RANLP 2017

Since the advent of word embedding methods, the representation of longer pieces of texts such as sentences and paragraphs is gaining more and more interest, especially for textual similarity tasks.

Beihang-MSRA at SemEval-2017 Task 3: A Ranking System with Neural Matching Features for Community Question Answering

no code yet • SEMEVAL 2017

This paper presents the system in SemEval-2017 Task 3, Community Question Answering (CQA).

EICA Team at SemEval-2017 Task 3: Semantic and Metadata-based Features for Community Question Answering

no code yet • SEMEVAL 2017

In the main Subtask C, our primary submission was ranked fourth, with a MAP of 13. 48 and accuracy of 97. 08.

FA3L at SemEval-2017 Task 3: A ThRee Embeddings Recurrent Neural Network for Question Answering

no code yet • SEMEVAL 2017

In this paper we present ThReeNN, a model for Community Question Answering, Task 3, of SemEval-2017.