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 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 drosselklappe stellantrieb 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 6 9x11 pergola dollars a day, our method helps these less eloquent farmers with their cultivation and hopefully provides a way to improve their lives.