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Collabot: Personalized Group Chat Summarization

Authors:

Lior LeibaAuthors Info & Claims

WSDM '18: Proceedings of the Eleventh ACM International Conference on Web Search and Data Mining

Pages 771 - 774

https://doi.org/10.1145/3159652.3160588

Published: 02 February 2018 Publication History

Abstract

In recent years, enterprise group chat collaboration tools, such as Slack, IBM»s Watson Workspace and Microsoft Teams, have presented unprecedented growth. With all the potential benefits of these tools - productivity increase and improved group communication - come significant challenges. Specifically, the 'always on' feature that makes it hard for users to cope with the load of conversational content and get up to speed after logging off for a while. In this demo, we present Collabot - a chat assistant service that implicitly learns users interests and social ties within a chat group and provides a personalized digest of missed content. Collabot assists users in coping with chat information overload by helping them understand the main topics discussed, collaborators, links and resources. This demo has two main contributions. First, we present a novel personalized group chat summarization algorithm; second the demonstration depicts a working implementation applied on different chat groups from different domains within IBM. A video, describing the demo can be found at https://www.youtube.com/watch?v=6cVsstiJ9vk.

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Cited By

Ogunleye BLancho Barrantes BZakariyyah K(2025)Topic modelling through the bibliometrics lens and its techniqueArtificial Intelligence Review10.1007/s10462-024-11011-x58:3Online publication date: 6-Jan-2025
https://doi.org/10.1007/s10462-024-11011-x
Ogunleye BMaswera THirsch LGaudoin JBrunsdon T(2023)Comparison of Topic Modelling Approaches in the Banking ContextApplied Sciences10.3390/app1302079713:2(797)Online publication date: 6-Jan-2023
https://doi.org/10.3390/app13020797
Jia QLiu YRen SZhu K(2023)Taxonomy of Abstractive Dialogue Summarization: Scenarios, Approaches, and Future DirectionsACM Computing Surveys10.1145/362293356:3(1-38)Online publication date: 5-Oct-2023
https://dl.acm.org/doi/10.1145/3622933
Show More Cited By

Index Terms

Collabot: Personalized Group Chat Summarization
1. Information systems
  1. Information retrieval
    1. Retrieval tasks and goals
      1. Summarization
  2. World Wide Web
    1. Web searching and information discovery
      1. Personalization

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Published In

cover image ACM Conferences

WSDM '18: Proceedings of the Eleventh ACM International Conference on Web Search and Data Mining

February 2018

821 pages

ISBN:9781450355810

DOI:10.1145/3159652

General Chairs:
Yi Chang
Jilin University, Huawei Inc.
,
Chengxiang Zhai
University of Illinois Urbana-Champaign
,
Program Chairs:
Yan Liu
University of Southern California
,
Yoelle Maarek
Amazon

Copyright © 2018 ACM.

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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Publication History

Published: 02 February 2018

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WSDM 2018: The Eleventh ACM International Conference on Web Search and Data Mining

February 5 - 9, 2018

CA, Marina Del Rey, USA

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WSDM '18 Paper Acceptance Rate 81 of 514 submissions, 16%;

Overall Acceptance Rate 498 of 2,863 submissions, 17%

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Cited By

Ogunleye BLancho Barrantes BZakariyyah K(2025)Topic modelling through the bibliometrics lens and its techniqueArtificial Intelligence Review10.1007/s10462-024-11011-x58:3Online publication date: 6-Jan-2025
https://doi.org/10.1007/s10462-024-11011-x
Ogunleye BMaswera THirsch LGaudoin JBrunsdon T(2023)Comparison of Topic Modelling Approaches in the Banking ContextApplied Sciences10.3390/app1302079713:2(797)Online publication date: 6-Jan-2023
https://doi.org/10.3390/app13020797
Jia QLiu YRen SZhu K(2023)Taxonomy of Abstractive Dialogue Summarization: Scenarios, Approaches, and Future DirectionsACM Computing Surveys10.1145/362293356:3(1-38)Online publication date: 5-Oct-2023
https://dl.acm.org/doi/10.1145/3622933
Chatterjee PDamevski KKraft NPollock L(2021)Automatically Identifying the Quality of Developer Chats for Post Hoc UseACM Transactions on Software Engineering and Methodology10.1145/345050330:4(1-28)Online publication date: 23-Jul-2021
https://dl.acm.org/doi/10.1145/3450503
Yang MCui HCao SWang YLi XHuang JChang YCheng XKamps JMurdock VWen JLiu Y(2020)ServiceGroup: A Human-Machine Cooperation Solution for Group Chat Customer ServiceProceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3397271.3401414(2189-2192)Online publication date: 25-Jul-2020
https://dl.acm.org/doi/10.1145/3397271.3401414
Lee SSong JKo EPark SKim JKim JBernhaupt RMueller FVerweij DAndres JMcGrenere JCockburn AAvellino IGoguey ABjørn PZhao SSamson BKocielnik R(2020)SolutionChat: Real-time Moderator Support for Chat-based Structured DiscussionProceedings of the 2020 CHI Conference on Human Factors in Computing Systems10.1145/3313831.3376609(1-12)Online publication date: 21-Apr-2020
https://dl.acm.org/doi/10.1145/3313831.3376609
Hashavit ATepper NRonen ILeiba LCohen AMitrovic TZhang JChen LChin D(2018)Implicit User Modeling in Group ChatAdjunct Publication of the 26th Conference on User Modeling, Adaptation and Personalization10.1145/3213586.3225236(275-280)Online publication date: 2-Jul-2018
https://dl.acm.org/doi/10.1145/3213586.3225236

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