- عشورنژاد، غدیر؛ عشورنژاد، انیس و تومانیان، آرا. (1396). ارائه روشهای جدید هرس کردن قوانین طبقهبندی انجمنی مورد کاوی: قوانین مرتبط با بهینگی مکان استقرار بانکهای شهر تهران. نشریه مهندسی نقشهبرداری و اطلاعات مکانی، ۸ (۲)، ۴۸-۳۹.
- Ashournejad, Q., Ashournejad, A., & Toomanian, A. (2017). New Methods of Pruning Associative Classification Rules (Case Study: Rules Related to the Optimality of Location of Banks in Tehran City). Geospatial Engineering Journal, 8(2), 39-48. [In Persian]
- Andriani, S. P., (2020). Sales Display Re-layout Based on Analysis of Item Sets Pattern Using Combination of Complete Linkage Hierarchical Clustering Method and Association-Rule Method with Apriori Algorithm.
- Angeline, D., (2013). Magdalene Delighta. "Association rule generation for student performance analysis using apriori algorithm. The SIJ Transactions on Computer Science Engineering & its Applications (CSEA), 1(1), 12-16. https://doi.org/10.9756/sijcsea/v1i1/01010252
- Appice, A. (2003). Discovery of spatial association rules in geo-referenced census data: A relational mining approach. Intelligent Data Analysis, 7(6), 541-566. https://doi.org/10.3233/ida-2003-7604
- Appice, A. (2005). Mining and filtering multi-level spatial association rules with ARES." International Symposium on Methodologies for Intelligent Systems. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11425274_36
- Bhatia, P. (2024). Machine Learning with Python. Cambridge: Cambridge University Press.
- Bin, R. (2014). Research on tourism service intelligent recommendation system based on apriori-MD algorithm." Applied Mechanics and Materials. Vol. 651. Trans Tech Publications Ltd. https://doi.org/10.4028/www.scientific.net/amm.651-653.1642
- Cox, D., Isham, V., & Northrop, P. (2000). Statistical Modeling and Analysis of Spatial Patterns. In U. Dieckmann, R. Law, & J. Metz (Eds.), The Geometry of Ecological Interactions: Simplifying Spatial Complexity (Cambridge Studies in Adaptive Dynamics, pp. 65-88). Cambridge: Cambridge University Press. https://doi.org/10.1017/cbo9780511525537.029
- Coyle, D., Meyer, O., & Staschen-Dielmann, S. (Eds.). (2023). A Deeper Learning Companion for CLIL: Putting Pluriliteracies into Practice. Cambridge: Cambridge University Press.
- Egidi, G. (2020). Towards local forms of sprawl: A brief reflection on mediterranean urbanization. Sustainability, 12(2), 582. https://doi.org/10.3390/su12020582
- Eick, Ch. F. (2008). Finding regional co-location patterns for sets of continuous variables in spatial datasets. Proceedings of the 16th ACM SIGSPATIAL international conference on Advances in geographic information systems. https://doi.org/10.1145/1463434.1463472
- El Naqa, I., & Martin J. M. (2015). What is machine learning?." machine learning in radiation oncology. Springer, Cham, 3-11. https://doi.org/10.1007/978-3-319-18305-3_1
-
- Fotheringham, A. S., & Chris, B. (1999). Local forms of spatial analysis. Geographical analysis, 31 (4), 340-358. https://doi.org/10.1111/j.1538-4632.1999.tb00989.x
- Fotheringham, A., Stewart, Chris B., & Martin Ch. (2000). Quantitative geography: perspectives on spatial data analysis. Sage.
- Goodchild, M. F. (2009). First law of geography. International encyclopedia of human geography. Elsevier Inc. 179-182. https://doi.org/10.1016/b978-008044910-4.00438-7
- Haining, R. (2003). Spatial Data Analysis: Theory and Practice. Cambridge: Cambridge University Press. doi:10.1017/CBO9780511754944
- Harun, Nur A. (2017). The application of apriori algorithm in predicting flood areas. management 17 (18. https://doi.org/10.18517/ijaseit.7.3.1463
- Hesse, M., & Jean-Paul, R. (2004). The transport geography of logistics and freight distribution. Journal of transport geography, 12(3), 171-184. https://doi.org/10.1016/j.jtrangeo.2003.12.004
- Hsieh, Po-Ch. et al. (2020). Combination of acupoints in treating patients with chronic obstructive pulmonary disease: an apriori algorithm-based association rule analysis. Evidence-Based Complementary and Alternative Medicine. https://doi.org/10.1155/2020/8165296
- Huang, Y., Shashi, Sh., & Hui, X. (2004). Discovering colocation patterns from spatial data sets: a general approach. IEEE Transactions on Knowledge and data engineering 16(12), 1472-1485. https://doi.org/10.1109/tkde.2004.90
- Jafarzadeh, A. A., Mahdavi, A., & Jafarzadeh, H. (2017). Evaluation of forest fire risk using the Apriori algorithm and fuzzy c-means clustering. Journal of forest Science, 63(80, 370-380. https://doi.org/10.17221/7/2017-jfs
- Jordan, Michael I., & Tom M. M. (2015). Machine learning: Trends, perspectives, and prospects. Science, 349(6245), 255-260. https://doi.org/10.1126/science.aaa8415
- Kavitha, M., & Subbaiah, S. (2020). Association rule mining using apriori algorithm for extracting product sales patterns in groceries. Int. J. Eng. Res. Technol, 8(03, 1-4.
- Li, H. (2011). An improved multi-support Apriori algorithm under the fuzzy item association condition." 2011 International Conference on Electronics, Communications and Control (ICECC). IEEE,. https://doi.org/10.1109/icecc.2011.6067661
- Liao, Sh-h., Yin-Ju, Ch., & Min-yi, D. (2010). Mining customer knowledge for tourism new product development and customer relationship management. Expert Systems with Applications, 37(6), 4212-4223. https://doi.org/10.1016/j.eswa.2009.11.081
- Malerba, D. (2003). Mining spatial association rules in census data. Research in Official Statistics. v5 i1, 19-44.
- Mehta, S. V., Shagun, S., & Dhaval, P. (2018). Spatial Co-location Pattern Mining-A new perspective using Graph Database." arXiv preprint arXiv:1810.09007
- Miller, Harvey J. (2004). Tobler's first law and spatial analysis. Annals of the association of American geographers, (94)2, 284-289.
- Miller, H. J., & Jiawei, H. (2011). Geographic data mining and knowledge discovery. CRC press.
- Priya, G. (2009). Mining co-location patterns from spatial data using rulebased approach. Journal of Global Research in Computer Science, 2(7), 58-61.
- Rocha, J., & José, T. (2018). editors. Spatial Analysis, Modelling and Planning. IntechOpen. https://doi.org/10.5772/intechopen.81049
- Romero, C. (2010). Mining rare association rules from e-learning data. Educational Data Mining 2010.
- Shah, C. (2022). A Hands-On Introduction to Machine Learning. Cambridge: Cambridge University Press.
- Shavlik, Jude W., Thomas, D., & Thomas, Glen D. eds. (1990). Readings in machine learning. Morgan Kaufmann.
- Shekhar, Sh., & Yan, H. (2001). Discovering spatial co-location patterns: A summary of results. International symposium on spatial and temporal databases. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-47724-1_13
- Sinaga, Kristina P., & Miin-Shen, Y. (2020). Unsupervised K-means clustering algorithm. IEEE access 8, 80716-80727. https://doi.org/10.1109/access.2020.2988796
- Tobler, Waldo R. (1970). A computer movie simulating urban growth in the Detroit region. Economic geography, 46.sup1 234-240. https://doi.org/10.2307/143141
- Verma, A., & Raman, K. (2022). Association Rule Generation using Pattern Mining Apriori Technique. Journal Of Algebraic Statistics, 13(2), 550-556.
- Yoo, Jin S., & Mark, B. (2012). Mining spatial colocation patterns: a different framework. Data Mining and Knowledge Discovery, 24(1), 159-194. https://doi.org/10.1007/s10618-011-0223-0
- Zhou, Zhi-Hua. (2021). Machine learning. Springer Nature.
|