# Learning to Rank Questions for Community Question Answering with Ranking SVM

Source: [Learning to Rank Questions for Community Question Answering with Ranking SVM](<https://www.sota2.com/research/paper/68fa62bf1e209131ce9fb23f>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-25T20:26:18.516Z

Authors: Minh-Tien Nguyen, Viet-Anh Phan, Truong-Son Nguyen, Minh-Le Nguyen

Published: 2016-08-15T06:16:18.000Z

## Abstract

This paper presents our method to retrieve relevant queries given a new question in the context of Discovery Challenge: Learning to Re-Ranking Questions for Community Question Answering competition. In order to do that, a set of learning to rank methods was investigated to select an appropriate method. The selected method was optimized on training data by using a search strategy. After optimizing, the method was applied to development and test set. Results from the competition indicate that the performance of our method outperforms almost participants and show that Ranking SVM is efficient for retrieving relevant queries in community question answering.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/1608.04185>)

[PDF](<https://arxiv.org/pdf/1608.04185.pdf>)