Quantitative Weighting Approach for Non-TI Clustering-Reference-Cited by-同舟云学术

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Quantitative Weighting Approach for Non-TI Clustering

Published:2021 Issue: Volume:184 Page:966-971
ISSN:1877-0509
Container-title:Procedia Computer Science
language:en
Short-container-title:Procedia Computer Science

Author:

Saha Sanjit Kumar,Schmitt Ingo

Publisher

Elsevier BV

Subject

General Engineering

Reference9 articles.

1. “QQL: A DB&IR Query Language”;Schmitt;VLDB J.,2008

2. “Incorporating Weights into a Quantum-Logic-Based Query Language”;Schmitt,2019

3. “A preference-based approach for interactive weight learning: learning weights within a logic-based query language”;Zellhöfer;Journal of Distributed and Parallel Databases,2009

4. “A formula for incorporating weights into scoring rules”;Ronald Fagin;Theoretical Computer Science,2000

5. “Non-TI Clustering in the Context of Social Networks”;Saha;Procedia Computer Science,2020

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A Relevance Feedback-Based Approach for Non-TI Clustering;Advanced Data Mining and Applications;2022

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