Design and Implementation of an Optimal Travel Route Recommender System on Big Data for Tourists in Jeju
Abstract
:1. Introduction
2. Related Work
3. Proposed Optimal Travel Route Recommender System Architecture
3.1. Association Rule Mining Based Travel Route Recommendation
Pseudo Code for Apriori (T, MS) |
Input (T, MS) Output: Begin: ← {T} for k← 2 to do { ← //cartesian product of Lk−1 × Lk−1 and eliminating any k − 1 infrequent size items set for each t in T do { ← od } od } Return |
- For each frequent route set R, find all nonempty subset of R.
- For each non-empty subset S of R, write the strong route S → (R-S) if support count of R/support count of S ≥ minimum confidence.
3.2. Genetic Algorithm Based Travel Route Optimization
4. Dataset and Experiment
5. Implementation Details
6. Use Case Study: Mobile Tourist
7. Comparison and Significance
8. Conclusions and Future Direction
Author Contributions
Funding
Conflicts of Interest
References
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Min Supp | Min Conf | No. Cycles | No. Best Rules | Average Run Time |
---|---|---|---|---|
0.03 | 0.9 | 8 | 125 | 9.674 s |
0.04 | 0.9 | 7 | 125 | 5.860 s |
0.05 | 0.9 | 7 | 61 | 5.336 s |
0.06 | 0.9 | 7 | 61 | 5.036 s |
0.07 | 0.9 | 5 | 61 | 4.272 s |
0.08 | 0.9 | 5 | 29 | 2.420 s |
0.09 | 0.9 | 5 | 26 | 2.264 s |
0.1 | 0.9 | 5 | 29 | 2.073 s |
Season | Min Supp | Min Conf | No. Cycles | No. Best Rules | Average Run Time |
---|---|---|---|---|---|
Spring | 0.07 | 0.9 | 4 | 61 | 1.102 s |
Summer | 0.07 | 0.9 | 5 | 29 | 0.581 s |
Autumn | 0.07 | 0.9 | 6 | 125 | 4.313 s |
Winter | 0.07 | 0.9 | 5 | 13 | 0.453 s |
Season | Id | Moving Path |
---|---|---|
Spring | 1 | Jeongbang Falls, Chilshimni Food Street, Seobok Exhibition Hall, Jungmun Tourist Complex |
2 | Seobok Exhibition Hall, Jeongbang Falls, Chilshimni Food Street, Jungmun Tourist Complex | |
3 | Chishimni Food Street, Jeongbang Falls, Seobok Exhibition Hall, Jungmun Tourist Complex | |
Summer | 1 | Play K-Pop Jeju, Teddy Bear Museum, Pacific Land, Cheonjeyeon Falls |
2 | Teddy Bear Museum, Cheonjeyeon Falls, Pacific Land, Play K-Pop Jeju | |
3 | Cheonjeyeon Falls, Pacific Land, Play K-Pop Jeju, Teddy Bear Museum |
No | No. Places | Population Size | Max Generation | Mutation Rate |
---|---|---|---|---|
1 | 10 | 100 | 1000 | 1.5% |
2 | 25 | 100 | 1000 | 1.5% |
3 | 40 | 100 | 1000 | 1.5% |
5 | 55 | 100 | 1000 | 1.5% |
No | No. Places | Best Result | Average Result | Optimum |
---|---|---|---|---|
1 | 10 | 789 | 801 | 740 |
2 | 25 | 1550 | 1620 | 1475 |
3 | 40 | 3460 | 3505 | 3250 |
4 | 55 | 7620 | 7720 | 7420 |
Component | Characterization |
---|---|
Operating System | Windows 7 Ultimate 64 bits |
CPU | Intel(R) Core i3-3220 |
Memory | 12 GB |
IDE | Eclipse Luna (4.4.2) |
Library and Framework | opencsv |
Programming Language | Java |
Component | Characterization |
---|---|
Model Name | Galaxy S4 SHV-E300K |
Operating System | Android 4.2.2 |
CPU | Octa-core (4 × 1.6 GHz Cortex-A15 & 4 × 1.2 GHz Cortex-A7) |
Memory | 2 GB |
IDE | Android Studio 3.1.2 |
DBMS | SQlite3 |
Library and Framework | Daum Map API, kma API, YouTube Data API |
Programming Language | Java, XML |
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Hang, L.; Kang, S.-H.; Jin, W.; Kim, D.-H. Design and Implementation of an Optimal Travel Route Recommender System on Big Data for Tourists in Jeju. Processes 2018, 6, 133. https://doi.org/10.3390/pr6080133
Hang L, Kang S-H, Jin W, Kim D-H. Design and Implementation of an Optimal Travel Route Recommender System on Big Data for Tourists in Jeju. Processes. 2018; 6(8):133. https://doi.org/10.3390/pr6080133
Chicago/Turabian StyleHang, Lei, Sang-Hun Kang, Wenquan Jin, and Do-Hyeun Kim. 2018. "Design and Implementation of an Optimal Travel Route Recommender System on Big Data for Tourists in Jeju" Processes 6, no. 8: 133. https://doi.org/10.3390/pr6080133
APA StyleHang, L., Kang, S.-H., Jin, W., & Kim, D.-H. (2018). Design and Implementation of an Optimal Travel Route Recommender System on Big Data for Tourists in Jeju. Processes, 6(8), 133. https://doi.org/10.3390/pr6080133