CHENG-YUAN LIOULiou, D.-R.D.-R.LiouSimak, A.A.A.A.SimakHuang, B.-S.B.-S.Huang2018-09-102018-09-10201303029743http://www.scopus.com/inward/record.url?eid=2-s2.0-84892884612&partnerID=MN8TOARShttp://scholars.lib.ntu.edu.tw/handle/123456789/379132https://www.scopus.com/inward/record.uri?eid=2-s2.0-84892884612&doi=10.1007%2f978-3-642-42057-3_3&partnerID=40&md5=c2f7038b9cf9f2e9103e52059961c29aThis work uses L-system to model the text sequence. The sequence complexity is obtained by calculating the complexity of its modeling system. It can sense certain quasi-regular structures and serves as a measure of regularity of the sequence. The outliers and statistics of the complexity values can be applied to the anomaly detection of symbol sequences. © 2013 Springer-Verlag Berlin Heidelberg.L-system; measure of regularity; quasi-regular structure; rewriting rule; text complexityBig data; L-systems; measure of regularity; Regular structure; Rewriting rules; text complexity; Anomaly detectionconference paper10.1007/978-3-642-42057-3-32-s2.0-84892884612