Answering complex queries in knowledge graphs with bidirectional sequence encoders useable to support decision making and having medical use applications

Abstract

A method for encoding a query graph into a sequence representation includes receiving m×n path queries representing a query graph having m root nodes and n leaf nodes, each path query beginning with a root node and ending with a leaf node, and encoding positions of each node and each edge between nodes within each path query independently, wherein the encoded positions include a positional order within each path query. The positional encodings may include no positional ordering between different path queries. The query graph may include one or more missing entities and each missing entity may be masked to produce a masked sequential query, which may be fed to a transformer encoder. The invention can be used for, but is not limited to, medical uses, such as for predicting protein-drug interactions or medical conditions, as well as other applications, and significantly outperforms the optimized model.