@inproceedings{bdcf264f9a5948f8a6647ddf87fd7a1c,
title = "A modified approach to inferring animal social networks from spatiotemporal data streams",
abstract = "Animal social networks offer an important research mechanism for animal behaviour analysis. Inferring social network structures in ecological systems from spatiotemporal data streams [1] presents a procedure to build such networks based on animal{\textquoteright}s foraging process data which consists of time and location records. The method clusters the individuals into different gathering events and links up the individuals that appear in the same events, and subsequently filters coincident links. However, the original model does not perform well in many aspects, including time and space complexity and not-unique coincident link filtering threshold. To modify this method, fuzzy c-means is employed in this work to cluster all links into two groups, strong links or weak links. The work presented here also experimentally compares the performance of the proposed modification against the original method, demonstrating the efficacy of the modified version. {\textcopyright} 2018, Springer International Publishing AG",
keywords = "computational intelligence, robotics, neural networks, fuzzy systems",
author = "Pu Zhang and Qiang Shen",
year = "2017",
month = jul,
day = "10",
doi = "10.1007/978-3-319-66939-7_7",
language = "English",
isbn = "978-331966938-0",
series = "Advances in Intelligent Systems and Computing",
publisher = "Springer Nature",
pages = "75--87",
editor = "Fei Chao and Steven Schockaert and Qingfu Zhang",
booktitle = "Proceedings of the 17th UK Workshop on Computational Intelligence",
address = "Switzerland",
note = "17th Annual UK Workshop on Computational Intelligence, UKCI-2017 ; Conference date: 06-09-2017 Through 08-09-2017",
}