Build a basic text search application from python with Vespa: Part 2

Thiago Martins, a Vespa Data Scientist, provides a tutorial on using the pyvespa API to conduct search engine experiments in Python, building on a basic text search application established in a previous tutorial. The focus is on comparing two query models using different matching operators, OR and WeakAnd, to manage document retrieval and ranking efficiently. By feeding additional data and employing evaluation metrics such as MatchRatio, Recall, and Normalized Discounted Cumulative Gain (NDCG), the tutorial demonstrates that the WeakAnd operator can significantly reduce the number of documents matched without compromising recall and precision. The tutorial also explores optimizing the WeakAnd operator's hits parameter, revealing that a hits value greater than three maintains recall while further reducing the average number of matched documents. Overall, the tutorial aims to enable Vespa users to run search engine experiments efficiently from Python while offering insights into optimizing search query models.