Add nar to readme

README.md

@@ -36,6 +36,7 @@ The currently supported data patterns are:
    - set-based axiomatization (discovery)
    - list-based axiomatization (discovery)
 * Metric functional dependencies (validation)
+* Numerical association rules (discovery)
 * Fuzzy algebraic constraints (discovery)
 * Differential Dependencies (discovery)
 * Unique column combinations:
@@ -219,6 +220,8 @@ Here is a list of papers about patterns, organized in the recommended reading or
    - [Sebastian Kruse and Felix Naumann. 2018. Efficient discovery of approximate dependencies. Proc. VLDB Endow. 11, 7 (March 2018), 759–772.](https://www.vldb.org/pvldb/vol11/p759-kruse.pdf)
 * Association rules
    - [Charu C. Aggarwal, Jiawei Han. 2014. Frequent Pattern Mining. Springer Cham. pp 471.](https://link.springer.com/book/10.1007/978-3-319-07821-2)
+* Numerical association rules
+   - [Minakshi Kaushik, Rahul Sharma, Iztok Fister Jr., and Dirk Draheim. 2023. Numerical Association Rule Mining: A Systematic Literature Review. 1, 1 (July 2023), 50 pages.](https://arxiv.org/abs/2307.00662)
 * Matching dependencies
    - [Philipp Schirmer, Thorsten Papenbrock, Ioannis Koumarelas, and Felix Naumann. 2020. Efficient Discovery of Matching Dependencies. ACM Trans. Database Syst. 45, 3, Article 13 (September 2020), 33 pages. https://doi.org/10.1145/3392778](https://dl.acm.org/doi/10.1145/3392778)
 * Denial constraints

examples/basic/README.md

@@ -16,6 +16,7 @@ These scenarios showcase a single pattern by discussing its definition and provi
 + [mining_ind.py](https://github.com/Desbordante/desbordante-core/tree/main/examples/basic/mining_ind.py) — a scenario showing how to discover inclusion dependencies.
 + [mining_list_od.py](https://github.com/Desbordante/desbordante-core/tree/main/examples/basic/mining_list_od.py) — a scenario showing how to discover order dependencies based on list axiomatization.
 + [mining_md.py](https://github.com/Desbordante/desbordante-core/tree/main/examples/basic/mining_md.py) — a scenario showing how to discover matching dependencies.
++ [mining_nar.py](https://github.com/Desbordante/desbordante-core/tree/main/examples/basic/mining_nar.py) — a scenario showing how to discover numerical association rules.
 + [mining_pfd.py](https://github.com/Desbordante/desbordante-core/tree/main/examples/basic/mining_pfd.py) — a scenario showing how to discover probabilistic functional dependencies.
 + [mining_set_od_1.py](https://github.com/Desbordante/desbordante-core/tree/main/examples/basic/mining_set_od_1.py) — a scenario showing how to discover order dependencies based on set axiomatization, part 1.
 + [mining_set_od_2.py](https://github.com/Desbordante/desbordante-core/tree/main/examples/basic/mining_set_od_2.py) — a scenario showing how to discover order dependencies based on set axiomatization, part 2.