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.
|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|
|Publication status||E-pub ahead of print - 4 Feb 2020|
|Name||Advances in Intelligent Systems and Computing|
- sequence mining
- network analysis