Frequent Knot Discovery
Floris Geerts
Abstract
We explore the possibility of applying the framework of frequent pattern mining to a class of continuous objects appearing in nature, namely knots. We introduce the frequent knot mining problem and present a solution. The key observation is that a database consisting of knots can be transformed into a transactional database. This observation is based on the Prime Decomposition Theorem of knots.
Create a lesson
Related papers
Navigating Runtime Dynamism in Semantic Query Serving
Hengrui Zhang, Xupeng Miao
SQLoom: Set-Contrastive Learning of Syntactic, Semantic, and Logical Dependencies for Text-to-SQL
Hao Fu, Degang Sun, Wan Wei et al.
Stop Handcrafting Your Engine! GenDB-V: Towards AI-Generated and Formally Verified Database Systems
Jiale Lao, Immanuel Trummer
Recast: Refinement-Centered Approximate Nearest Neighbor Search Optimized for Storage
Zehai Yang, Fengyi Tao, Wenzhuo Dong et al.
USDB: Scaling Storage for Next-Generation Recommender Systems at ByteDance
Xiaoran Zhu, Jieming Cai, Weiping Yu et al.
Mixed-Type Relational Database Synthesis with Graph-Prompted Language Model
Yuxiang Sun, Mengshi Chen, Jianwei Wang et al.