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Chapter and Conference Paper
A Relational Instance-Based Clustering Method with Contrastive Learning for Open Relation Extraction
Unsupervised text representations significantly narrow the gap with supervised pretraining, and relation clustering has gradually become an important method of open relational extraction (OpenRE). However, dif...
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Chapter and Conference Paper
TNT: An Effective Method for Finding Correlations Between Two Continuous Variables
Determining whether two continuous variables are relevant, either linearly or non-linearly correlated, is a fundamental problem in data science. To test whether two continuous variables have a linear correlati...
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Chapter and Conference Paper
Feature Selection Based on Graph Structure
Feature selection is an important part of data preprocessing. Selecting effective feature subsets can effectively reduce feature redundancy and reduce irrelevant features, and reduce training costs. Based on t...
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Chapter and Conference Paper
A Modified Genetic Algorithm for Agricultural By-products Logistics Delivery Route Planning Problem
Agricultural by-products collection and delivery route planning is one of the important issues of delivery scheduling optimization for agricultural regional logistics. Aimed at agricultural by-products logist...