Auto-tagging Emails with User Stories Using Project Context

被引:0
|
作者
Sohan, S. M. [1 ]
Richter, Michael M. [1 ]
Maurer, Frank [1 ]
机构
[1] Univ Calgary, Dept Comp Sci, Calgary, AB T2L 2A7, Canada
关键词
Distributed Agile; Collaboration; Software Documentation; Agile Tool; SOFTWARE-DEVELOPMENT;
D O I
暂无
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
In distributed agile teams, people often use email as a knowledge sharing tool to clarify the project requirements (aka user stories). Knowledge about the project included in these emails is easily lost when recipients leave the project or delete emails for various reasons. However, the knowledge contained in the emails may be needed for useful purposes such as re-engineering software, changing vendor and so on. But, it is difficult to relate texts such as emails to certain topics because the relation is not explicit. In this paper, we present and evaluate a technique for automatically relating emails with user stories based on their text and context similarity. Agile project management tools can use this technique to automatically build a knowledge base that is otherwise costly to produce and maintain.
引用
收藏
页码:103 / 116
页数:14
相关论文
共 50 条
  • [21] Auto-tagging algorithm of 3D CAD models
    Li, L. (sweetsilence1019@mail.nwpu.edu.cn), 1600, CIMS (19):
  • [22] Music auto-tagging based on the unified latent semantic modeling
    Xi Shao
    Zhiyong Cheng
    Mohan S. Kankanhalli
    Multimedia Tools and Applications, 2019, 78 : 161 - 176
  • [23] Music auto-tagging based on the unified latent semantic modeling
    Shao, Xi
    Cheng, Zhiyong
    Kankanhalli, Mohan S.
    MULTIMEDIA TOOLS AND APPLICATIONS, 2019, 78 (01) : 161 - 176
  • [24] Music Auto-tagging with Variable Feature Sets and Probabilistic Annotation
    Yin, Jingjing
    Yan, Qin
    Lv, Yong
    Tao, Qiuyu
    2014 9TH INTERNATIONAL SYMPOSIUM ON COMMUNICATION SYSTEMS, NETWORKS & DIGITAL SIGNAL PROCESSING (CSNDSP), 2014, : 156 - 160
  • [25] Comparative Study on Different Approaches in Optimizing Threshold for Music Auto-Tagging
    Khanh Nguyen Cao Minh
    Thinh Dang An
    Vu Tran Quang
    Van Hoai Tran
    FUTURE DATA AND SECURITY ENGINEERING, FDSE 2018, 2018, 11251 : 237 - 250
  • [26] Music auto-tagging using scattering transform and convolutional neural network with self-attention
    Song, Guangxiao
    Wang, Zhijie
    Han, Fang
    Ding, Shenyi
    Gu, Xiaochun
    APPLIED SOFT COMPUTING, 2020, 96
  • [27] Tag Propagation and Cost-Sensitive Learning for Music Auto-Tagging
    Lin, Yi-Hsun
    Chen, Homer H.
    IEEE TRANSACTIONS ON MULTIMEDIA, 2021, 23 : 1605 - 1616
  • [28] Playlist-Based Tag Propagation for Improving Music Auto-Tagging
    Lin, Yi-Hsun
    Chung, Chia-Hao
    Chen, Homer H.
    2018 26TH EUROPEAN SIGNAL PROCESSING CONFERENCE (EUSIPCO), 2018, : 2270 - 2274
  • [29] Auto-Tagging for Massive Online Selection Tests: Machine Learning to the Rescue
    Krithivasan, S.
    Gupta, S.
    Shandilya, S.
    Arya, K.
    Lala, K.
    2016 IEEE 8TH INTERNATIONAL CONFERENCE ON TECHNOLOGY FOR EDUCATION (T4E 2016), 2016, : 204 - 207
  • [30] A Model for Auto-Tagging of Research Papers based on Keyphrase Extraction Methods
    Thushara, M. G.
    Krishnapriya, M. S.
    Nair, Sangeetha S.
    2017 INTERNATIONAL CONFERENCE ON ADVANCES IN COMPUTING, COMMUNICATIONS AND INFORMATICS (ICACCI), 2017, : 1695 - 1700