INFORMATION ENRICHMENT USING GLOBAL STRUCTURE LEARNING

摘要

Methods, systems and computer program products implementing data enrichment using global structure learning are disclosed. An information enrichment system predicts a likely canonical name from a transaction record in which names may be shortened, or extra token(s) inserted. In a training phase, the information enrichment system determines tag patterns based on labeled and unlabeled training transaction records. The tag patterns include co-occurrence probability and sequential order of co-occurrence of tags. In a testing phase, the information enrichment system receives a test transaction record. The information enrichment system predicts a likely tag sequence from the test transaction record based on the tag patterns. The information enrichment system predicts a canonical name based on likely tag values and token composition. The information enrichment system can then enrich the test transaction record with the predicted canonical name.