Discovery of effective infrequent sequences based on maximum probability path

Figures & data

Figure 1. Process model mined by FHM algorithm.

Figure 2. Process model mined by iDHM algorithm.

Table 1. 1000 logs containing noise activity x and the meaning of the activity.

Id	Trace	Number	Id	Trace	Number
1	〈AFGH〉	$\times 7$	18	〈AIMNOPD〉	$\times 1$
2	〈AXFGH〉	$\times 1$	19	〈AIMNOPH〉	$\times 41$
3	〈AFXGH〉	$\times 1$	20	〈AIMNOQ〉	$\times 8$
4	〈AFGXH〉	$\times 1$	21	〈AIMXNOQ〉	$\times 1$
5	〈AFGHX〉	$\times 1$	22	〈ABCD〉	$\times 121$
6	〈AFKLXD〉	$\times 9$	23	〈ABED〉	$\times 150$
7	〈AFKLH〉	$\times 1$	24	〈AFGD〉	$\times 172$
8	〈AFKNOPXD〉	$\times 1$	25	〈AFXGD〉	$\times 9$
9	〈AFKNOPH〉	$\times 100$	26	〈AIJGD〉	$\times 149$
10	〈AFXKNOPH〉	$\times 2$	27	〈AIJGXD〉	$\times 2$
11	〈AFKNOPXH〉	$\times 1$	28	〈AIXJGD〉	$\times 5$
12	〈AFKNOQ〉	$\times 5$	29	〈AIJGH〉	$\times 4$
13	〈AIJKLXD〉	$\times 1$	30	〈AIJGXH〉	$\times 1$
14	〈AIJKLH〉	$\times 7$	31	〈AXIJGH〉	$\times 2$
15	〈AIJKNOPXD〉	$\times 1$	32	〈AXIMLD〉	$\times 1$
16	〈AIJKNOPH〉	$\times 61$	33	〈AIMLH〉	$\times 121$
17	〈AIJKNOQ〉	$\times 12$

Figure 3. Screenshot of the program running interface.

Figure 4. The entropy of activities under different threshold settings.

Figure 5. The change of entropy of noise activity in different thresholds.

Figure 6. IM mines the model quality of manual logs under the threshold (${\delta }_L-{\delta }_N-{\delta }_S$).

Figure 7. HM mines the model quality of manual logs under the threshold (${\delta }_L-{\delta }_N-{\delta }_S$).

Figure 8. DFG mines the model quality of manual logs under the threshold (${\delta }_L-{\delta }_N-{\delta }_S$).

Figure 9. Partial results of DFG mining synthetic logs.

Table 2. Model quality metrics under different threshold settings.

Delta	Fitness			Precision			Generalisation			Simplicity
(${\delta }_L-{\delta }_S$)	IM	HM	DFG	IM	HM	DFG	IM	HM	DFG	IM	HM	DFG
Before EIM	0.93	0.95	0.59	0.22	0.85	1.00	0.8	0.78	0.34	0.58	0.76	0.57
0.02–0.1	0.94	0.94	0.10	0.87	0.21	1.00	0.86	0.66	0.33	0.81	0.55	0.68
0.02–0.3	0.94	0.95	0.28	0.87	0.19	1.00	0.86	0.71	0.32	0.81	0.59	0.70
0.02–0.5	0.94	0.95	0.55	0.87	0.20	1.00	0.86	0.72	0.34	0.81	0.60	0.71
0.02–0.7	0.93	0.90	0.73	0.99	0.29	1.00	0.92	0.77	0.64	0.84	0.66	0.78
0.02–0.9	0.93	1.00	0.87	0.99	0.53	1.00	0.92	0.97	0.70	0.84	0.64	0.81
0.04–0.1	0.94	0.94	0.37	0.87	0.20	1.00	0.85	0.67	0.34	0.81	0.55	0.69
0.04–0.3	0.94	1.00	0.38	0.87	0.18	1.00	0.84	0.66	0.35	0.81	0.57	0.70
0.04–0.5	0.94	0.89	0.41	0.87	0.22	1.00	0.84	0.71	0.41	0.81	0.62	0.75
0.04–0.7	0.93	1.00	0.73	1.00	0.54	1.00	0.91	0.93	0.74	0.85	0.60	0.82
0.04–0.9	0.93	1.00	0.88	1.00	0.52	1.00	0.91	0.97	0.76	0.85	0.60	0.81
0.06–0.1	0.93	0.94	0.22	0.71	0.14	1.00	0.79	0.67	0.33	0.83	0.58	0.68
0.06–0.3	0.93	0.92	0.37	0.71	0.14	1.00	0.75	0.59	0.28	0.83	0.59	0.70
0.06–0.5	0.95	1.00	0.21	1.00	0.34	1.00	0.90	0.73	0.38	0.92	0.65	0.79
0.06–0.7	0.92	1.00	0.77	1.00	0.89	1.00	0.90	0.91	0.72	0.92	0.82	0.90
0.06–0.9	0.92	1.00	0.88	1.00	0.88	1.00	0.90	0.98	0.77	0.92	0.88	0.89
0.08–0.1	0.93	0.94	0.41	0.71	0.14	1.00	0.79	0.67	0.33	0.83	0.58	0.68
0.08–0.3	0.93	0.92	0.21	0.71	0.14	1.00	0.75	0.59	0.28	0.83	0.59	0.70
0.08–0.5	0.92	1.00	0.41	1.00	0.34	1.00	0.90	0.73	0.38	0.92	0.65	0.79
0.08–0.7	0.92	1.00	0.77	1.00	0.89	1.00	0.90	0.91	0.72	0.92	0.82	0.90
0.08–0.9	0.92	1.00	0.91	1.00	0.88	1.00	0.90	0.98	0.77	0.92	0.88	0.89
0.1–0.1	1.00	0.94	0.27	0.79	0.11	1.00	0.83	0.66	0.34	0.86	0.58	0.69
0.1–0.3	1.00	0.92	0.37	0.79	0.12	1.00	0.79	0.59	0.29	0.86	0.59	0.71
0.1–0.5	1.00	1.00	0.43	1.00	0.41	1.00	0.98	0.72	0.40	1.00	0.67	0.83
0.1–0.7	1.00	1.00	0.81	1.00	1.00	1.00	0.98	0.91	0.80	1.00	0.89	1.00
0.1-0.9	1.00	1.00	0.91	1.00	1.00	1.00	0.98	0.98	0.86	1.00	1.00	1.00
0.12–0.1	1.00	0.94	0.47	0.79	0.11	1.00	0.83	0.66	0.34	0.86	0.58	0.69
0.12–0.3	1.00	0.92	0.22	0.79	0.12	1.00	0.79	0.59	0.29	0.86	0.59	0.71
0.12–0.5	1.00	1.00	0.43	1.00	0.41	1.00	0.98	0.72	0.40	1.00	0.67	0.83
0.12–0.7	1.00	1.00	0.81	1.00	1.00	1.00	0.98	0.91	0.80	1.00	0.89	1.00
0.12–0.9	1.00	1.00	0.95	1.00	1.00	1.00	0.98	0.98	0.86	1.00	1.00	1.00
0.14–0.1	1.00	0.94	0.43	0.79	0.11	1.00	0.83	0.66	0.34	0.86	0.58	0.69
0.14–0.3	1.00	0.92	0.31	0.79	0.12	1.00	0.79	0.59	0.29	0.86	0.59	0.71
0.14–0.5	1.00	1.00	0.37	1.00	0.41	1.00	0.98	0.72	0.40	1.00	0.67	0.83
0.14–0.7	1.00	1.00	0.81	1.00	1.00	1.00	0.98	0.91	0.80	1.00	0.89	1.00
0.14–0.9	1.00	1.00	0.95	1.00	1.00	1.00	0.98	0.98	0.86	1.00	1.00	1.00
0.16–0.1	1.00	0.94	0.22	0.79	0.11	1.00	0.83	0.66	0.34	0.86	0.58	0.69
0.16–0.3	1.00	0.92	0.37	0.79	0.12	1.00	0.79	0.59	0.29	0.86	0.59	0.71
0.16–0.5	1.00	1.00	0.22	1.00	0.41	1.00	0.98	0.72	0.40	1.00	0.67	0.83
0.16–0.7	1.00	1.00	0.78	1.00	1.00	1.00	0.98	0.91	0.80	1.00	0.89	1.00
0.16–0.9	1.00	1.00	0.95	1.00	1.00	1.00	0.98	0.98	0.86	1.00	1.00	1.00
0.18–0.1	1.00	0.94	0.59	0.79	0.11	1.00	0.83	0.66	0.34	0.86	0.58	0.69
0.18–0.3	1.00	0.92	0.53	0.79	0.12	1.00	0.79	0.59	0.29	0.86	0.59	0.71
0.18–0.5	1.00	1.00	0.31	1.00	0.41	1.00	0.98	0.72	0.40	1.00	0.67	0.83
0.18–0.7	1.00	1.00	0.78	1.00	1.00	1.00	0.98	0.91	0.80	1.00	0.89	1.00
0.18–0.9	1.00	1.00	0.91	1.00	1.00	1.00	0.98	0.98	0.86	1.00	1.00	1.00