Electronic Resource

Article - n bot we trust: A new methodology of chatbot performance measures Volume: 62 Halaman: 785–797

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Chatbots are used frequently in business to facilitate various processes,
particularly those related to customer service and personalization. In this article,
we propose novel methods of tracking human-chatbot interactions and measuring
chatbot performance that take into consideration ethical concerns, particularly
trust. Our proposed methodology links neuroscientific methods, text mining, and

machine learning. We argue that trust is the focal point of successful human-
chatbot interaction and assess how trust as a relevant category is being redefined

with the advent of deep learning supported chatbots. We propose a novel method

of analyzing the content of messages produced in human-chatbot interactions, us-
ing the Condor Tribefinder system we developed for text mining that is based on a

machine learning classification engine. Our results will help build better social bots
for interaction in business or commercial environments.
a 2019 Kelley School of Business, Indiana University. Published by Elsevier Inc. All
rights reserved.

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Ketersediaan

Informasi Detail

Judul Seri

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No. Panggil

658.812 PRZ i

Penerbit

: Elsevier Academic Press., 2019

Deskripsi Fisik

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Bahasa

English

ISBN/ISSN

0007-6813

Klasifikasi

658.812 PRZ i

Tipe Isi

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Tipe Media

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Tipe Pembawa

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Edisi

Volume: 62 Halaman: 785–797

Subjek

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Info Detail Spesifik

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Pernyataan Tanggungjawab

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