Standard
Extraction of Typical Client Requests from Bank Chat Logs. / Pronoza, Ekaterina ; Pronoza, Anton ; Yagunova, Elena .
Advances in Computational Intelligence: 17th Mexican International Conference on Artificial Intelligence, MICAI 2018, Guadalajara, Mexico, October 22-27, 2018, Proceedings, Part II. Switzerland : Springer Nature, 2018. p. 156-164 (Lecture Notes in Artificial Intelligence; Vol. 11289).
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review
Harvard
Pronoza, E, Pronoza, A
& Yagunova, E 2018,
Extraction of Typical Client Requests from Bank Chat Logs. in
Advances in Computational Intelligence: 17th Mexican International Conference on Artificial Intelligence, MICAI 2018, Guadalajara, Mexico, October 22-27, 2018, Proceedings, Part II. Lecture Notes in Artificial Intelligence, vol. 11289, Springer Nature, Switzerland, pp. 156-164, 17th Mexican International Conference on Artificial Intelligence MICAI'2018, Гвадалахара, Mexico,
22/10/18.
APA
Pronoza, E., Pronoza, A.
, & Yagunova, E. (2018).
Extraction of Typical Client Requests from Bank Chat Logs. In
Advances in Computational Intelligence: 17th Mexican International Conference on Artificial Intelligence, MICAI 2018, Guadalajara, Mexico, October 22-27, 2018, Proceedings, Part II (pp. 156-164). (Lecture Notes in Artificial Intelligence; Vol. 11289). Springer Nature.
Vancouver
Author
Pronoza, Ekaterina ; Pronoza, Anton
; Yagunova, Elena . /
Extraction of Typical Client Requests from Bank Chat Logs. Advances in Computational Intelligence: 17th Mexican International Conference on Artificial Intelligence, MICAI 2018, Guadalajara, Mexico, October 22-27, 2018, Proceedings, Part II. Switzerland : Springer Nature, 2018. pp. 156-164 (Lecture Notes in Artificial Intelligence).
BibTeX
@inproceedings{a591b5b1273148ebad44b6a69350f88a,
title = "Extraction of Typical Client Requests from Bank Chat Logs",
abstract = "In this paper we propose a simple but powerful method of extracting key client requests from bank chat logs. Many companies nowadays are interested in building a chat bot to optimize their business, and are ready to provide chat bot developers with large amounts of data, but such data often need special preparation to be successfully used for a chat bot system. We propose a method of data preparation which includes not only data cleaning but also data mining: we extract key notions from chat logs and retrieve typical client requests in generalized form. The method uses simple metrics as well as word embeddings and additional semantic resources to extract typical client requests from client-manager chat logs.",
keywords = "chat logs, chat bot, keywords, collocations, client requests",
author = "Ekaterina Pronoza and Anton Pronoza and Elena Yagunova",
note = "Pronoza E., Pronoza A., Yagunova E. (2018) Extraction of Typical Client Requests from Bank Chat Logs. In: Batyrshin I., Mart{\'i}nez-Villase{\~n}or M., Ponce Espinosa H. (eds) Advances in Computational Intelligence. MICAI 2018. Lecture Notes in Computer Science, vol 11289. Springer, Cham. https://doi.org/10.1007/978-3-030-04497-8_13; null ; Conference date: 22-10-2018 Through 27-01-2019",
year = "2018",
language = "English",
isbn = "978-3-030-04496-1",
series = "Lecture Notes in Artificial Intelligence",
publisher = "Springer Nature",
pages = "156--164",
booktitle = "Advances in Computational Intelligence",
address = "Germany",
url = "http://www.micai.org/2018/",
}
RIS
TY - GEN
T1 - Extraction of Typical Client Requests from Bank Chat Logs
AU - Pronoza, Ekaterina
AU - Pronoza, Anton
AU - Yagunova, Elena
N1 - Conference code: 17
PY - 2018
Y1 - 2018
N2 - In this paper we propose a simple but powerful method of extracting key client requests from bank chat logs. Many companies nowadays are interested in building a chat bot to optimize their business, and are ready to provide chat bot developers with large amounts of data, but such data often need special preparation to be successfully used for a chat bot system. We propose a method of data preparation which includes not only data cleaning but also data mining: we extract key notions from chat logs and retrieve typical client requests in generalized form. The method uses simple metrics as well as word embeddings and additional semantic resources to extract typical client requests from client-manager chat logs.
AB - In this paper we propose a simple but powerful method of extracting key client requests from bank chat logs. Many companies nowadays are interested in building a chat bot to optimize their business, and are ready to provide chat bot developers with large amounts of data, but such data often need special preparation to be successfully used for a chat bot system. We propose a method of data preparation which includes not only data cleaning but also data mining: we extract key notions from chat logs and retrieve typical client requests in generalized form. The method uses simple metrics as well as word embeddings and additional semantic resources to extract typical client requests from client-manager chat logs.
KW - chat logs
KW - chat bot
KW - keywords
KW - collocations
KW - client requests
UR - https://link.springer.com/chapter/10.1007/978-3-030-04497-8_13
M3 - Conference contribution
SN - 978-3-030-04496-1
T3 - Lecture Notes in Artificial Intelligence
SP - 156
EP - 164
BT - Advances in Computational Intelligence
PB - Springer Nature
CY - Switzerland
Y2 - 22 October 2018 through 27 January 2019
ER -
