Helping the Ineloquent Farmers: Finding Experts for Questions With Limited Text in Agricultural Q&A Communities

Helping the Ineloquent Farmers: Finding Experts for Questions With Limited Text in Agricultural Q&A Communities

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Nowadays, hundreds of thousands of farmers in walter hagenah me 262 China seek online in agricultural Q&A communities, such as Farm-Doctor, for agricultural advice.As in many other Q&A communities, the key design issue is to find experts to provide timely and suitable answers.State-of-the-art approaches often rely on extracting topics from the question texts, however, the major challenge here is that questions in agricultural Q&A communities often contain limited textual information.

To solve this problem, in this article, we conduct an extensive measurement on Farm-Doctor, which consists of over 690 thousand questions and over 3 million answers, and we model Farm-Doctor as a heterogeneous information network that incorporates rich side information.We propose a novel approach based on graph neural network to accurately recommend for each question the users that are highly likely to answer it.With an average income of fewer than kuiper belt whiskey 6 dollars a day, our method helps these less eloquent farmers with their cultivation and hopefully provides a way to improve their lives.