Streamlining Knowledge Map Construction for an Online Auction House Using Automatic Term Filtering

Abstract

Organizations are building automated technical support software that can help both consumers and field support engineers with problem resolution. The goal of the automated technical support system is reducing operational cost and increasing customer satisfaction. This paper examines the set of challenges that knowledge engineers face in building automated technical support software. This paper uses a technical services engagement with a major online auction house with tens of millions of users to highlight the challenges and present an automated knowledge map generation technique. The objective of this automated technique was to improve the quality of expressions extracted from documents, which would reduce the burden on knowledge engineers to construct knowledge maps. The technique was run on large corpora of documents in the online auction house and found a significant increase in the quality of the knowledge map. Further experimentation showed that the technique works well for other domains as well.