Papers by Matthias Lee

2 papers
Recent Developments for the Linguistic Linked Open Data Infrastructure (2020.lrec-1)

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Challenge: Language data is rarely 'ready-to-use' and language technology specialists spend over 80% of their time cleaning, organizing and collecting language datasets.
Approach: They propose a methodology for building data value chains based around language resources and language technologies that can be integrated by means of semantic technologies.
Outcome: The proposed methodology is based on language resources and language technologies that can be integrated by means of semantic technologies.
Predicting Customer Satisfaction with Soft Labels for Ordinal Classification (2023.acl-industry)

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Challenge: a typical call center only responds to 8% of customers with a customer satisfaction survey . a predictive algorithm that infers CSAT on the 1-5 scale is needed to minimize this data sparsity and response bias.
Approach: They propose an algorithm that infers CSAT on 1-5 scale on inbound calls to the call center . they reframe the problem into a binary class and map it back to five classes .
Outcome: The proposed model is able to support keycustomer workflows with high accuracy overmillions of calls a month.

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