All Outputs (2)

Problem classification for tailored help desk auto replies (2022)
Conference Proceeding
Nicholls, R., Fellows, R., Battle, S., & Ihshaish, H. (2022). Problem classification for tailored help desk auto replies. In E. Pimenidis, P. Angelov, C. Jayne, A. Papaleonidas, & M. Aydin (Eds.), Artificial Neural Networks and Machine Learning – ICANN 2022 (445-454). https://doi.org/10.1007/978-3-031-15937-4_37

IT helpdesks are charged with the task of responding quickly to user queries. To give the user confidence that their query matters, the helpdesk will auto-reply to the user with confirmation that their query has been received and logged. This auto-re... Read More about Problem classification for tailored help desk auto replies.

Task-oriented dialogue systems: Performance vs. quality-optima, a review (2022)
Conference Proceeding
Fellows, R., Ihshaish, H., Battle, S., Haines, C., Mayhew, P., & Deza, J. I. (2022). Task-oriented dialogue systems: Performance vs. quality-optima, a review. In David C. Wyld et al. (Eds): SIPP, NLPCL, BIGML, SOEN, AISC, NCWMC, CCSIT - 2022 pp. 69-87, 2022. CS & IT - CSCP 2022 (69-87). https://doi.org/10.5121/csit.2022.121306

Task-oriented dialogue systems (TODS) are continuing to rise in popularity as various industries find ways to effectively harness their capabilities, saving both time and money. However, even state-of-the-art TODS are not yet reaching their full pote... Read More about Task-oriented dialogue systems: Performance vs. quality-optima, a review.