EMCODIST: A Context-based Search Tool for Email Archives

Santhilata  Kuppili Venkata; Stephanie Decker; David Kirsch; Adam Nix

doi:10.1109/BigData52589.2021.9671832

EMCODIST: A Context-based Search Tool for Email Archives

Santhilata Kuppili Venkata, Stephanie Decker, David Kirsch, Adam Nix

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Preservation of emails poses particular challenges to future discovery as alternative historical sources. Emails represent communications between individuals and contain a wealth of information when viewed as an organisation-wide collection. Existing search tools can extract named entities and keyword searches but are less effective when it comes to extracting patterns and contextual information across multiple custodians. To address this, we present EMCODIST, a discovery tool for searching the contextual information across emails using attention-based models of Natural Language Processing (NLP). The EMCODIST aims to steer end-users to personalise their searches towards a concept. In this paper, we explain the definition of the ‘context’ for emails which is also suitable for object-oriented computational modelling. The tool is evaluated based on the relevancy of the emails extracted.

Original language	English
Title of host publication	2021 IEEE International Conference on Big Data (Big Data)
Editors	Yixin Chen, Heiko Ludwig, Yicheng Tu, Usama Fayyad, Xingquan Zhu, Xiaohua Hu, Suren Byna, Xiong Liu, Jianping Zhang, Shirui Pan, Vagelis Papalexakis, Jianwu Wang, Alfredo Cuzzocrea, Carlos Ordonez
Publisher	IEEE
Pages	2281-2290
Number of pages	10
ISBN (Electronic)	9781665439022
ISBN (Print)	9781665445993 (PoD)
DOIs	https://doi.org/10.1109/BigData52589.2021.9671832
Publication status	Published - 13 Jan 2022

Publication series

Name	IEEE International Conference on Big Data
Publisher	IEEE
ISSN (Print)	2639-1589
ISSN (Electronic)	2573-2978

Keywords

Contextualisation
Email archives processing
Content analysis
Natural Language Processing

Access to Document

10.1109/BigData52589.2021.9671832

Funded Project: Contextualising Email Archives’ (CEA), Full title: “Historicising the dot.com bubble and contextualising email archives”
Stephanie Decker (Contributor), Adam Nix (Contributor), David A. Kirsch (Contributor) & Santhilata Kuppili Venkata (Contributor)
2020 → 2022
Activity: Other

Cite this

Kuppili Venkata, S., Decker, S., Kirsch, D., & Nix, A. (2022). EMCODIST: A Context-based Search Tool for Email Archives. In Y. Chen, H. Ludwig, Y. Tu, U. Fayyad, X. Zhu, X. Hu, S. Byna, X. Liu, J. Zhang, S. Pan, V. Papalexakis, J. Wang, A. Cuzzocrea, & C. Ordonez (Eds.), 2021 IEEE International Conference on Big Data (Big Data) (pp. 2281-2290). (IEEE International Conference on Big Data). IEEE. https://doi.org/10.1109/BigData52589.2021.9671832

Kuppili Venkata, Santhilata ; Decker, Stephanie ; Kirsch, David et al. / EMCODIST : A Context-based Search Tool for Email Archives. 2021 IEEE International Conference on Big Data (Big Data). editor / Yixin Chen ; Heiko Ludwig ; Yicheng Tu ; Usama Fayyad ; Xingquan Zhu ; Xiaohua Hu ; Suren Byna ; Xiong Liu ; Jianping Zhang ; Shirui Pan ; Vagelis Papalexakis ; Jianwu Wang ; Alfredo Cuzzocrea ; Carlos Ordonez. IEEE, 2022. pp. 2281-2290 (IEEE International Conference on Big Data).

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title = "EMCODIST: A Context-based Search Tool for Email Archives",

abstract = "Preservation of emails poses particular challenges to future discovery as alternative historical sources. Emails represent communications between individuals and contain a wealth of information when viewed as an organisation-wide collection. Existing search tools can extract named entities and keyword searches but are less effective when it comes to extracting patterns and contextual information across multiple custodians. To address this, we present EMCODIST, a discovery tool for searching the contextual information across emails using attention-based models of Natural Language Processing (NLP). The EMCODIST aims to steer end-users to personalise their searches towards a concept. In this paper, we explain the definition of the {\textquoteleft}context{\textquoteright} for emails which is also suitable for object-oriented computational modelling. The tool is evaluated based on the relevancy of the emails extracted.",

keywords = "Contextualisation, Email archives processing, Content analysis, Natural Language Processing",

author = "{Kuppili Venkata}, Santhilata and Stephanie Decker and David Kirsch and Adam Nix",

year = "2022",

month = jan,

day = "13",

doi = "10.1109/BigData52589.2021.9671832",

language = "English",

isbn = "9781665445993 (PoD)",

series = "IEEE International Conference on Big Data",

publisher = "IEEE",

pages = "2281--2290",

editor = "Yixin Chen and Heiko Ludwig and Yicheng Tu and Usama Fayyad and Xingquan Zhu and Xiaohua Hu and Suren Byna and Xiong Liu and Jianping Zhang and Shirui Pan and Vagelis Papalexakis and Jianwu Wang and Alfredo Cuzzocrea and Carlos Ordonez",

booktitle = "2021 IEEE International Conference on Big Data (Big Data)",

}

Kuppili Venkata, S, Decker, S, Kirsch, D & Nix, A 2022, EMCODIST: A Context-based Search Tool for Email Archives. in Y Chen, H Ludwig, Y Tu, U Fayyad, X Zhu, X Hu, S Byna, X Liu, J Zhang, S Pan, V Papalexakis, J Wang, A Cuzzocrea & C Ordonez (eds), 2021 IEEE International Conference on Big Data (Big Data). IEEE International Conference on Big Data, IEEE, pp. 2281-2290. https://doi.org/10.1109/BigData52589.2021.9671832

EMCODIST: A Context-based Search Tool for Email Archives. / Kuppili Venkata, Santhilata; Decker, Stephanie; Kirsch, David et al.
2021 IEEE International Conference on Big Data (Big Data). ed. / Yixin Chen; Heiko Ludwig; Yicheng Tu; Usama Fayyad; Xingquan Zhu; Xiaohua Hu; Suren Byna; Xiong Liu; Jianping Zhang; Shirui Pan; Vagelis Papalexakis; Jianwu Wang; Alfredo Cuzzocrea; Carlos Ordonez. IEEE, 2022. p. 2281-2290 (IEEE International Conference on Big Data).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - EMCODIST

T2 - A Context-based Search Tool for Email Archives

AU - Kuppili Venkata, Santhilata

AU - Decker, Stephanie

AU - Kirsch, David

AU - Nix, Adam

PY - 2022/1/13

Y1 - 2022/1/13

N2 - Preservation of emails poses particular challenges to future discovery as alternative historical sources. Emails represent communications between individuals and contain a wealth of information when viewed as an organisation-wide collection. Existing search tools can extract named entities and keyword searches but are less effective when it comes to extracting patterns and contextual information across multiple custodians. To address this, we present EMCODIST, a discovery tool for searching the contextual information across emails using attention-based models of Natural Language Processing (NLP). The EMCODIST aims to steer end-users to personalise their searches towards a concept. In this paper, we explain the definition of the ‘context’ for emails which is also suitable for object-oriented computational modelling. The tool is evaluated based on the relevancy of the emails extracted.

AB - Preservation of emails poses particular challenges to future discovery as alternative historical sources. Emails represent communications between individuals and contain a wealth of information when viewed as an organisation-wide collection. Existing search tools can extract named entities and keyword searches but are less effective when it comes to extracting patterns and contextual information across multiple custodians. To address this, we present EMCODIST, a discovery tool for searching the contextual information across emails using attention-based models of Natural Language Processing (NLP). The EMCODIST aims to steer end-users to personalise their searches towards a concept. In this paper, we explain the definition of the ‘context’ for emails which is also suitable for object-oriented computational modelling. The tool is evaluated based on the relevancy of the emails extracted.

KW - Contextualisation

KW - Email archives processing

KW - Content analysis

KW - Natural Language Processing

UR - https://ieeexplore.ieee.org/abstract/document/9671832

U2 - 10.1109/BigData52589.2021.9671832

DO - 10.1109/BigData52589.2021.9671832

M3 - Conference contribution

SN - 9781665445993 (PoD)

T3 - IEEE International Conference on Big Data

SP - 2281

EP - 2290

BT - 2021 IEEE International Conference on Big Data (Big Data)

A2 - Chen, Yixin

A2 - Ludwig, Heiko

A2 - Tu, Yicheng

A2 - Fayyad, Usama

A2 - Zhu, Xingquan

A2 - Hu, Xiaohua

A2 - Byna, Suren

A2 - Liu, Xiong

A2 - Zhang, Jianping

A2 - Pan, Shirui

A2 - Papalexakis, Vagelis

A2 - Wang, Jianwu

A2 - Cuzzocrea, Alfredo

A2 - Ordonez, Carlos

PB - IEEE

ER -

Kuppili Venkata S, Decker S, Kirsch D, Nix A. EMCODIST: A Context-based Search Tool for Email Archives. In Chen Y, Ludwig H, Tu Y, Fayyad U, Zhu X, Hu X, Byna S, Liu X, Zhang J, Pan S, Papalexakis V, Wang J, Cuzzocrea A, Ordonez C, editors, 2021 IEEE International Conference on Big Data (Big Data). IEEE. 2022. p. 2281-2290. (IEEE International Conference on Big Data). doi: 10.1109/BigData52589.2021.9671832

EMCODIST: A Context-based Search Tool for Email Archives

Abstract

Publication series

Keywords

Access to Document

Fingerprint

Activities

Funded Project: Contextualising Email Archives’ (CEA), Full title: “Historicising the dot.com bubble and contextualising email archives”

Cite this