Using sequence constraints for modelling network interactions

Johannes De Smedt; Junichiro Mori; Masanao Ochi

doi:10.1007/978-3-030-39878-1_1

Using sequence constraints for modelling network interactions

Johannes De Smedt, Junichiro Mori, Masanao Ochi

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

Abstract

This is an extension from a selected paper from JSAI2019. The ubiquitous nature of networks has led to a vast number of works dedicated to the study of capturing their information. Various graph-based techniques exist that report on the characteristics of nodes and edges, e.g., author-citation networks, social interactions, and so on. A significant amount of information can be extracted by summarizing the surrounding network structure of nodes, e.g., by capturing motives, or walk patterns. In this work, we present a new way of capturing the interaction between nodes in a network by making use of the sequence in which they occur. (1) The objective of this paper is to make use of behavioural constraint patterns; a concise but detailed report of node's interactions can be constructed that can be used for various purposes. (2) It is shown how the constraint patterns can be mined form interaction data, and how they can be used for various applications. (3) A case study is presented which uses behavioural constraint patterns to profile user interactions in a communication network.

Original language	English
Title of host publication	Advances in Artificial Intelligence
Subtitle of host publication	Selected Papers from the Annual Conference of Japanese Society of Artificial Intelligence (JSAI 2019)
Editors	Y Ohsawa, K Yada, T Ito, Y Takama, E Sato-Shimokawara, A Abe, J Mori, N Matsumura
Publisher	Springer
Pages	3-13
ISBN (Electronic)	9783030398781
ISBN (Print)	9783030398774
DOIs	https://doi.org/10.1007/978-3-030-39878-1_1
Publication status	E-pub ahead of print - 4 Feb 2020

Publication series

Name	Advances in Intelligent Systems and Computing
Publisher	Springer
ISSN (Print)	2194-5357

Keywords / Materials (for Non-textual outputs)

sequence mining
network analysis

Access to Document

10.1007/978-3-030-39878-1_1

DeSmedtEtAl2020UsingSequenceConstraints
This is a post-peer-review, pre-copyedit version of an article published in Annual Conference of the Japanese Society for Artificial Intelligence JSAI 2019: Advances in Artificial Intelligence. The final authenticated version is available online at: https://link.springer.com/chapter/10.1007/978-3-030-39878-1_1
Accepted author manuscript, 273 KB

https://link.springer.com/chapter/10.1007/978-3-030-39878-1_1

Using sequence constraints for modelling network interactions
De Smedt, J., Mori, J. & Ochi, M., 1 Jun 2019, Proceedings of the Annual Conference of the Japanese Society for Artificial Intelligence. The Japanese Society for Artificial Intelligence
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Cite this

De Smedt, J., Mori, J., & Ochi, M. (2020). Using sequence constraints for modelling network interactions. In Y. Ohsawa, K. Yada, T. Ito, Y. Takama, E. Sato-Shimokawara, A. Abe, J. Mori, & N. Matsumura (Eds.), Advances in Artificial Intelligence: Selected Papers from the Annual Conference of Japanese Society of Artificial Intelligence (JSAI 2019) (pp. 3-13). (Advances in Intelligent Systems and Computing). Springer. Advance online publication. https://doi.org/10.1007/978-3-030-39878-1_1

De Smedt, Johannes ; Mori, Junichiro ; Ochi, Masanao. / Using sequence constraints for modelling network interactions. Advances in Artificial Intelligence: Selected Papers from the Annual Conference of Japanese Society of Artificial Intelligence (JSAI 2019). editor / Y Ohsawa ; K Yada ; T Ito ; Y Takama ; E Sato-Shimokawara ; A Abe ; J Mori ; N Matsumura. Springer, 2020. pp. 3-13 (Advances in Intelligent Systems and Computing).

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title = "Using sequence constraints for modelling network interactions",

abstract = "This is an extension from a selected paper from JSAI2019. The ubiquitous nature of networks has led to a vast number of works dedicated to the study of capturing their information. Various graph-based techniques exist that report on the characteristics of nodes and edges, e.g., author-citation networks, social interactions, and so on. A significant amount of information can be extracted by summarizing the surrounding network structure of nodes, e.g., by capturing motives, or walk patterns. In this work, we present a new way of capturing the interaction between nodes in a network by making use of the sequence in which they occur. (1) The objective of this paper is to make use of behavioural constraint patterns; a concise but detailed report of node's interactions can be constructed that can be used for various purposes. (2) It is shown how the constraint patterns can be mined form interaction data, and how they can be used for various applications. (3) A case study is presented which uses behavioural constraint patterns to profile user interactions in a communication network.",

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De Smedt, J, Mori, J & Ochi, M 2020, Using sequence constraints for modelling network interactions. in Y Ohsawa, K Yada, T Ito, Y Takama, E Sato-Shimokawara, A Abe, J Mori & N Matsumura (eds), Advances in Artificial Intelligence: Selected Papers from the Annual Conference of Japanese Society of Artificial Intelligence (JSAI 2019). Advances in Intelligent Systems and Computing, Springer, pp. 3-13. https://doi.org/10.1007/978-3-030-39878-1_1

Using sequence constraints for modelling network interactions. / De Smedt, Johannes; Mori, Junichiro; Ochi, Masanao.
Advances in Artificial Intelligence: Selected Papers from the Annual Conference of Japanese Society of Artificial Intelligence (JSAI 2019). ed. / Y Ohsawa; K Yada; T Ito; Y Takama; E Sato-Shimokawara; A Abe; J Mori; N Matsumura. Springer, 2020. p. 3-13 (Advances in Intelligent Systems and Computing).

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

TY - GEN

T1 - Using sequence constraints for modelling network interactions

AU - De Smedt, Johannes

AU - Mori, Junichiro

AU - Ochi, Masanao

PY - 2020/2/4

Y1 - 2020/2/4

N2 - This is an extension from a selected paper from JSAI2019. The ubiquitous nature of networks has led to a vast number of works dedicated to the study of capturing their information. Various graph-based techniques exist that report on the characteristics of nodes and edges, e.g., author-citation networks, social interactions, and so on. A significant amount of information can be extracted by summarizing the surrounding network structure of nodes, e.g., by capturing motives, or walk patterns. In this work, we present a new way of capturing the interaction between nodes in a network by making use of the sequence in which they occur. (1) The objective of this paper is to make use of behavioural constraint patterns; a concise but detailed report of node's interactions can be constructed that can be used for various purposes. (2) It is shown how the constraint patterns can be mined form interaction data, and how they can be used for various applications. (3) A case study is presented which uses behavioural constraint patterns to profile user interactions in a communication network.

AB - This is an extension from a selected paper from JSAI2019. The ubiquitous nature of networks has led to a vast number of works dedicated to the study of capturing their information. Various graph-based techniques exist that report on the characteristics of nodes and edges, e.g., author-citation networks, social interactions, and so on. A significant amount of information can be extracted by summarizing the surrounding network structure of nodes, e.g., by capturing motives, or walk patterns. In this work, we present a new way of capturing the interaction between nodes in a network by making use of the sequence in which they occur. (1) The objective of this paper is to make use of behavioural constraint patterns; a concise but detailed report of node's interactions can be constructed that can be used for various purposes. (2) It is shown how the constraint patterns can be mined form interaction data, and how they can be used for various applications. (3) A case study is presented which uses behavioural constraint patterns to profile user interactions in a communication network.

KW - sequence mining

KW - network analysis

U2 - 10.1007/978-3-030-39878-1_1

DO - 10.1007/978-3-030-39878-1_1

M3 - Conference contribution

SN - 9783030398774

T3 - Advances in Intelligent Systems and Computing

SP - 3

EP - 13

BT - Advances in Artificial Intelligence

A2 - Ohsawa, Y

A2 - Yada, K

A2 - Ito, T

A2 - Takama, Y

A2 - Sato-Shimokawara, E

A2 - Abe, A

A2 - Mori, J

A2 - Matsumura, N

PB - Springer

ER -

De Smedt J, Mori J, Ochi M. Using sequence constraints for modelling network interactions. In Ohsawa Y, Yada K, Ito T, Takama Y, Sato-Shimokawara E, Abe A, Mori J, Matsumura N, editors, Advances in Artificial Intelligence: Selected Papers from the Annual Conference of Japanese Society of Artificial Intelligence (JSAI 2019). Springer. 2020. p. 3-13. (Advances in Intelligent Systems and Computing). Epub 2020 Feb 4. doi: 10.1007/978-3-030-39878-1_1

Using sequence constraints for modelling network interactions

Abstract

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Keywords / Materials (for Non-textual outputs)

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Research output

Using sequence constraints for modelling network interactions

Cite this