IEICE TRANSACTIONS on Information
Workflow Extraction for Service Operation Using Multiple Unstructured Trouble Tickets
Summary :
In current large-scale IT systems, troubleshooting has become more complicated due to the diversification in the causes of failures, which has increased operational costs. Thus, clarifying the troubleshooting process also becomes important, though it is also time-consuming. We propose a method of automatically extracting a workflow, a graph indicating a troubleshooting process, using multiple trouble tickets. Our method extracts an operator's actions from free-format texts and aligns relative sentences between multiple trouble tickets. Our method uses a stochastic model to detect a resolution, a frequent action pattern that helps us understand how to solve a problem. We validated our method using real trouble-ticket data captured from a real network operation and showed that it can extract a workflow to identify the cause of a failure.
- Publication
- IEICE TRANSACTIONS on Information Vol.E101-D No.4 pp.1030-1041
- Publication Date
- 2018/04/01
- Publicized
- 2018/01/18
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.2017DAP0014
- Type of Manuscript
- Special Section PAPER (Special Section on Data Engineering and Information Management)
- Category
Authors
Akio WATANABE
NTT Corporation
Keisuke ISHIBASHI
NTT Corporation
Tsuyoshi TOYONO
NTT Corporation
Keishiro WATANABE
NTT Corporation
Tatsuaki KIMURA
NTT Corporation
Yoichi MATSUO
NTT Corporation
Kohei SHIOMOTO
Tokyo City University
Ryoichi KAWAHARA
NTT Corporation
Keyword
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Akio WATANABE, Keisuke ISHIBASHI, Tsuyoshi TOYONO, Keishiro WATANABE, Tatsuaki KIMURA, Yoichi MATSUO, Kohei SHIOMOTO, Ryoichi KAWAHARA, "Workflow Extraction for Service Operation Using Multiple Unstructured Trouble Tickets" in IEICE TRANSACTIONS on Information,
vol. E101-D, no. 4, pp. 1030-1041, April 2018, doi: 10.1587/transinf.2017DAP0014.
Abstract: In current large-scale IT systems, troubleshooting has become more complicated due to the diversification in the causes of failures, which has increased operational costs. Thus, clarifying the troubleshooting process also becomes important, though it is also time-consuming. We propose a method of automatically extracting a workflow, a graph indicating a troubleshooting process, using multiple trouble tickets. Our method extracts an operator's actions from free-format texts and aligns relative sentences between multiple trouble tickets. Our method uses a stochastic model to detect a resolution, a frequent action pattern that helps us understand how to solve a problem. We validated our method using real trouble-ticket data captured from a real network operation and showed that it can extract a workflow to identify the cause of a failure.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2017DAP0014/_p
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@ARTICLE{e101-d_4_1030,
author={Akio WATANABE, Keisuke ISHIBASHI, Tsuyoshi TOYONO, Keishiro WATANABE, Tatsuaki KIMURA, Yoichi MATSUO, Kohei SHIOMOTO, Ryoichi KAWAHARA, },
journal={IEICE TRANSACTIONS on Information},
title={Workflow Extraction for Service Operation Using Multiple Unstructured Trouble Tickets},
year={2018},
volume={E101-D},
number={4},
pages={1030-1041},
abstract={In current large-scale IT systems, troubleshooting has become more complicated due to the diversification in the causes of failures, which has increased operational costs. Thus, clarifying the troubleshooting process also becomes important, though it is also time-consuming. We propose a method of automatically extracting a workflow, a graph indicating a troubleshooting process, using multiple trouble tickets. Our method extracts an operator's actions from free-format texts and aligns relative sentences between multiple trouble tickets. Our method uses a stochastic model to detect a resolution, a frequent action pattern that helps us understand how to solve a problem. We validated our method using real trouble-ticket data captured from a real network operation and showed that it can extract a workflow to identify the cause of a failure.},
keywords={},
doi={10.1587/transinf.2017DAP0014},
ISSN={1745-1361},
month={April},}
Copy
TY - JOUR
TI - Workflow Extraction for Service Operation Using Multiple Unstructured Trouble Tickets
T2 - IEICE TRANSACTIONS on Information
SP - 1030
EP - 1041
AU - Akio WATANABE
AU - Keisuke ISHIBASHI
AU - Tsuyoshi TOYONO
AU - Keishiro WATANABE
AU - Tatsuaki KIMURA
AU - Yoichi MATSUO
AU - Kohei SHIOMOTO
AU - Ryoichi KAWAHARA
PY - 2018
DO - 10.1587/transinf.2017DAP0014
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E101-D
IS - 4
JA - IEICE TRANSACTIONS on Information
Y1 - April 2018
AB - In current large-scale IT systems, troubleshooting has become more complicated due to the diversification in the causes of failures, which has increased operational costs. Thus, clarifying the troubleshooting process also becomes important, though it is also time-consuming. We propose a method of automatically extracting a workflow, a graph indicating a troubleshooting process, using multiple trouble tickets. Our method extracts an operator's actions from free-format texts and aligns relative sentences between multiple trouble tickets. Our method uses a stochastic model to detect a resolution, a frequent action pattern that helps us understand how to solve a problem. We validated our method using real trouble-ticket data captured from a real network operation and showed that it can extract a workflow to identify the cause of a failure.
ER -
English
