Article

Automated email activity management: an unsupervised learning approach

Authors:

Nicholas Kushmerick,

Tessa LauAuthors Info & Claims

IUI '05: Proceedings of the 10th international conference on Intelligent user interfaces

Pages 67 - 74

https://doi.org/10.1145/1040830.1040854

Published: 10 January 2005 Publication History

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Abstract

Many structured activities are managed by email. For instance, a consumer purchasing an item from an e-commerce vendor may receive a message confirming the order, a warning of a delay, and then a shipment notification. Existing email clients do not understand this structure, forcing users to manage their activities by sifting through lists of messages. As a first step to developing email applications that provide high-level support for structured activities, we consider the problem of automatically learning an activity's structure. We formalize activities as finite-state automata, where states correspond to the status of the process, and transitions represent messages sent between participants. We propose several unsupervised machine learning algorithms in this context, and evaluate them on a collection of e-commerce email.

References

[1]

V. Bellotti, B. Dalal, N. Good, P. Flynn, D. Bobrow, and N. Ducheneaut. What a to-do: studies of task management towards the design of a personal task list manager. In Proc. Conf. Human Factors in Computing Systems, 2004.

Digital Library

Google Scholar

[2]

V. Bellotti, N. Ducheneaut, M. Howard, and I. Smith. Taking email to task: The design and evaluation of a task management centered email tool. In Proc. Conf. Human Factors in Computing Systems, 2003.

Digital Library

Google Scholar

[3]

R. Carrasco. Accurate computation of the relative entropy between stochastic regular grammars. Theoretical Informatics and Applications, 31(5), 1997.

Google Scholar

[4]

N. Ducheneaut and V. Bellotti. Email as habitat: An exploration of embedded personal information management. ACM Interactions, 8(1), 2001.

Digital Library

Google Scholar

[5]

E. Gold. Grammar identification in the limit. Information and Control, 10(5), 1967.

Google Scholar

[6]

J. Gwizdka. Reinventing the inbox -- supporting the management of pending tasks in email. In Proc. Conf. Human Factors in Computing Systems, 2002.

Digital Library

Google Scholar

[7]

N. Kushmerick and A. Heß. Learning to attach semantic metadata to web services. In Proc. Int. Semantic Web Conf., 2003.

Google Scholar

[8]

P. Maes. Agents that reduce work and information overload. Communications of the ACM, 37(7), 1994.

Digital Library

Google Scholar

[9]

K. Mock. An experimental framework for email categorization and management. In Proc. Int. Conf. Research and Development in Information Retrieval, 2001.

Digital Library

Google Scholar

[10]

S. Rohall, D. Gruen, P. Moody, M. Wattenberg, M. Stern, B. Kerr, B. Stachel, D. Kushal, R. Armes, and E. Wilcox. Remail: A reinvented email prototype. In Proc. Conf. Human Factors in Computing Systems, 2004.

Digital Library

Google Scholar

[11]

M. Sahami, S. Dumais, D. Heckerman, and E. Horvitz. A Bayesian approach to filtering junk e-mail. In Proc. AAI-98 Workshop on Learning for Text Categorization, 1998.

Google Scholar

[12]

R. Segal and J. Kephart. Incremental learning in SwiftFile. In Proc. Int. Conf. Machine Learning, 2000.

Digital Library

Google Scholar

[13]

F. Thollard, P. Dupont, and C. de le Higuera. Probabilistic DFA inference using Kullback-Leibler divergence and minimality. In Proc. Int. Conf. Machine Learning, 2000.

Digital Library

Google Scholar

[14]

W. van der Aalst, B. van Dongen, J. Herbst, L. Maruster, G. Schimm, and A. Weijters. Workflow mining: A survey of issues and approaches. Data and Knowledge Engineering, 47(2):237--267, 2003.

Digital Library

Google Scholar

[15]

S. Whittaker and C. Sidner. Email overloading: Exploring personal information management of email. In Proc. Conf. Human Factors in Computing Systems, 1996.

Digital Library

Google Scholar

Cited By

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Elleuch MIsmaili OLaga NGaaloul W(2023)Process fragments discovery from emails: Functional, data and behavioral perspectives discoveryInformation Systems10.1016/j.is.2023.102229118(102229)Online publication date: Sep-2023
https://doi.org/10.1016/j.is.2023.102229
Elleuch MLaga NAlaoui Ismaili OGaaloul W(2021)Multi‐perspective business process discovery from messaging systems: State‐of‐the artConcurrency and Computation: Practice and Experience10.1002/cpe.664235:11Online publication date: 30-Sep-2021
https://doi.org/10.1002/cpe.6642
ELLEUCH MLAGA NALAOUI ISMAILI OGAALOUL W(2020)Discovering Business Processes And Activities From Messaging Systems: State-Of-The Art2020 IEEE 29th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE)10.1109/WETICE49692.2020.00035(137-142)Online publication date: Sep-2020
https://doi.org/10.1109/WETICE49692.2020.00035
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Index Terms

Automated email activity management: an unsupervised learning approach
1. Human-centered computing
2. Information systems
  1. World Wide Web
    1. Web applications
      1. Internet communications tools
        Email

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Reviews

Reviewer: Caroline Merriam Eastman

Have you ever spent time sorting or searching through your email in an attempt to find earlier messages related to your current task__?__ If so, you are well aware of the problem Kushmerick and Lau address in this paper. A task, such as an e-commerce purchase or online course, often generates a series of emails, both incoming and outgoing. Can these email messages be usefully organized by tasks and subtasks__?__ The project described here automatically classifies messages and constructs finite-state automata representing task structures using unsupervised machine learning techniques. The algorithms developed produced very good results on a small corpus of 111 messages, relating to 39 transactions with six online retailers. The research provides a sound foundation for further work, which might include a broader range of different tasks and investigation of the scalability and usability of a more complete system. The paper is well written, and should be of interest to researchers and developers working with email systems. Online Computing Reviews Service

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Information & Contributors

Information

Published In

IUI '05: Proceedings of the 10th international conference on Intelligent user interfaces

January 2005

344 pages

ISBN:1581138946

DOI:10.1145/1040830

General Chair:
Rob St. Amant
North Carolina State University, USA
,
Program Chairs:
John Riedl
University of Minnesota, USA
,
Anthony Jameson
DFKI and International University in Germany

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 10 January 2005

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IUI05

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IUI05: Tenth International Conference on Intelligent User Interfaces

January 10 - 13, 2005

California, San Diego, USA

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Overall Acceptance Rate 746 of 2,811 submissions, 27%

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IUI '25

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March 24 - 27, 2025

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Cited By

View all

Elleuch MIsmaili OLaga NGaaloul W(2023)Process fragments discovery from emails: Functional, data and behavioral perspectives discoveryInformation Systems10.1016/j.is.2023.102229118(102229)Online publication date: Sep-2023
https://doi.org/10.1016/j.is.2023.102229
Elleuch MLaga NAlaoui Ismaili OGaaloul W(2021)Multi‐perspective business process discovery from messaging systems: State‐of‐the artConcurrency and Computation: Practice and Experience10.1002/cpe.664235:11Online publication date: 30-Sep-2021
https://doi.org/10.1002/cpe.6642
ELLEUCH MLAGA NALAOUI ISMAILI OGAALOUL W(2020)Discovering Business Processes And Activities From Messaging Systems: State-Of-The Art2020 IEEE 29th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE)10.1109/WETICE49692.2020.00035(137-142)Online publication date: Sep-2020
https://doi.org/10.1109/WETICE49692.2020.00035
ELLEUCH MASSY NLAGA NGAALOUL WALAOUI ISMAILI OBenatallah B(2020)A Meta Model for Mining Processes from Email Data2020 IEEE International Conference on Services Computing (SCC)10.1109/SCC49832.2020.00028(152-161)Online publication date: Nov-2020
https://doi.org/10.1109/SCC49832.2020.00028
Elleuch MAlaoui Ismaili OLaga NAssy NGaaloul W(2020)Discovery of Activities’ Actor Perspective from Emails based on Speech Acts Detection2020 2nd International Conference on Process Mining (ICPM)10.1109/ICPM49681.2020.00021(73-80)Online publication date: Oct-2020
https://doi.org/10.1109/ICPM49681.2020.00021
Trippas JSpina DScholer FAwadallah ABailey PBennett PWhite RLiono JRen YSalim FSanderson MAzzopardi LHalvey MRuthven IJoho HMurdock VQvarfordt P(2019)Learning About Work Tasks to Inform Intelligent Assistant DesignProceedings of the 2019 Conference on Human Information Interaction and Retrieval10.1145/3295750.3298934(5-14)Online publication date: 8-Mar-2019
https://dl.acm.org/doi/10.1145/3295750.3298934
Bota HBennett PAwadallah ADumais SNordlie RPharo NFreund LLarsen BRussel D(2017)Self-EsProceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval10.1145/3020165.3020189(205-214)Online publication date: 7-Mar-2017
https://dl.acm.org/doi/10.1145/3020165.3020189
Haraty MWang ZWang HIqbal STeevan J(2017)Design and in-situ evaluation of a mixed-initiative approach to information organizationJournal of the Association for Information Science and Technology10.1002/asi.2382368:9(2211-2224)Online publication date: 1-Sep-2017
https://dl.acm.org/doi/10.1002/asi.23823
Stamm KDengel A(2014)Mapping Multichannel Documents to Attentive Tasks: Ensuring Information Gain and Detecting FailureAgents and Artificial Intelligence10.1007/978-3-662-44440-5_13(211-227)Online publication date: 31-Oct-2014
https://doi.org/10.1007/978-3-662-44440-5_13
Gil YRatnakar VChklovski TGroth PVrandecic D(2012)Capturing Common Knowledge about TasksACM Transactions on Interactive Intelligent Systems10.1145/2362394.23623972:3(1-35)Online publication date: 1-Sep-2012
https://dl.acm.org/doi/10.1145/2362394.2362397
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