Taxonomy Extraction for Customer Service Knowledge Base Construction

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Abstract

Customer service agents play an important role in bridging the gap between customers’ vocabulary and business terms. In a scenario where organisations are moving into semi-automatic customer service, semantic technologies with capacity to bridge this gap become a necessity. In this paper we explore the use of automatic taxonomy extraction from text as a means to reconstruct a customer-agent taxonomic vocabulary. We evaluate our proposed solution in an industry use case scenario in the financial domain and show that our approaches for automated term extraction and using in-domain training for taxonomy construction can improve the quality of automatically constructed taxonomic knowledge bases.

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APA

Pereira, B., Robin, C., Daudert, T., McCrae, J. P., Mohanty, P., & Buitelaar, P. (2019). Taxonomy Extraction for Customer Service Knowledge Base Construction. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11702 LNCS, pp. 175–190). Springer. https://doi.org/10.1007/978-3-030-33220-4_13

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