The document outlines a project that analyzes GPS data from 62 users collected over two years in China, totaling 3,497,750 GPS points. It describes algorithms for identifying user stay points based on distance and time thresholds, followed by relational algebra operations like bag union and intersection to extract meaningful patterns. The goal is to discover interesting places frequented by users through these stay point calculations.

1. Mining GPS data

2. THE GOAL
 Discover interesting places from GPS data of 62 users.
 The data collected with Microsoft Research Asia,
in two years, 4115 days in china for the users
 3،497،750 GPS point
 43،18،284 km squared

3. Notations
 GPS Users: We have GPS logs of n users U = (u1,u2,………..,un).
 GPS Log: GPS points of the ith user, Gi = (gi1,gi2,………,gin).
 GPS Point: (Longitude, Latitude, Altitude, Date, Time).
 Stay Point: stay point Si is a geographical location where an individual
spent a significant amount of time.

4. ALGORITHM METHODS
1) Determine every user stay point
with algorithm (1).
2) Apply relational algebra operations
(Bag Union & Bag Intersection).
3) Apply Mode of Stay Points.

5. ALGORITHM(1)
 Algorithm1:
StayPointCalculation( GPSPoints,
ThresDistance,
ThresTime)
 Input: GPS points G={g1, g2,…., gn} ,
a distance threshold ThresDistance
and time span threshold ThresTime
Output: A set of stay points StayPts={S}

6. RELATIONAL ALGEBRA OPERATIONS
 Bag Union:
SPUnion= {Su1} UB{Su2} UB…………………… UB {Sun}
{ S ui} = Stay Points of User ui.
UB = Bag Union
 Bag Intersection:
SPIntersect = {S u1} ПB{Su2} ПB…………………… ПB {Sun}
{ S ui} = Stay Points of User ui.
ПB = Bag Intersection
 Mode of Stay Points: with (ThresCount)
M1 = Mode({SPUnion})
M2 = Mode({SPUnion} {M1})
M3 = Mode({SPUnion} {M1,M2})
Mn = Mode({SPUnion} {M1,M2,M3,…..,Mn-1})
SPMode={M1 , M2 , M3 ,…………, Mn}

7. APPLY ON DATA SET
Bag union
result

8. Mode
operation
result