Paper: Multi-Way Relation Classification: Application To Protein-Protein Interactions

ACL ID H05-1092
Title Multi-Way Relation Classification: Application To Protein-Protein Interactions
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2005
Authors

We address the problem of multi-way re- lation classification, applied to identifica- tion of the interactions between proteins in bioscience text. A major impediment to such work is the acquisition of appro- priately labeled training data; for our ex- periments we have identified a database that serves as a proxy for training data. We use two graphical models and a neu- ral net for the classification of the inter- actions, achieving an accuracy of 64% for a 10-way distinction between relation types. We also provide evidence that the exploitation of the sentences surrounding a citation to a paper can yield higher accu- racy than other sentences.