Research on Precision Marketing Model of Tourism Industry Based on User’s Mobile Behavior Trajectory

Algorithm 3

	Input parameters: user movement behavior trajectory Q, minimum speed S, minimum time T, and maximum disturbance threshold MT.
	Output parameters: collection of popular scenic spots HR.
	Step 1: for (i = 2, i ≤ |Q|, i++) /∗  represents the number of location information points∗/
	Step 2: D [i − 1] · T = cal T (pi − 1, pi);
	Step 3: D [i − 1] · S = cal D (pi − 1, pi)/D [i − 1] · T;
	Step 4: HR = {}; C = {}; CO = false;
	Step 5: for (j = 2, j ≤ , j++) /∗cycle search indoor attractions area HRI∗/
	Step 6: if (D [j − 1] · T > T and D [i − 1] · S < n ∗ S) then
	Step 7: C = {pj − 1, pj}; /∗record location information point stay area∗/
	Step 8: if (not CO) then CO = true;
	Step 9: else C = Update {pj − 1, pj}; /∗merge the location information points closer to the collection HR∗/
	Step 10: else if (CO) then
	Step 11: HR = {C}; CO = false; C = {} /∗search outdoor attractions area HRII∗/
	Step 12: if (D [j − 1] · S ≤ S) then /∗determine activity intensive areas∗/
	Step 13: C = {pj};
	Step 14: if (not CO) then CO = true;
	Step 15: else if (CO) then
	Step 16: last Index = look Ahead (MT, S);
	Step 17: if (last Index ≤ j + MT) then
	Step 18: for k = last Index downto j do
	Step 19: C = {pk};
	Step 20: j = last Index;
	Step 21: else if (time (C) > T) then
	Step 22: HÈ = {C}; C = {}; CO = false;
	Step 23: return HR;