Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Clustering with the agglomerative information bottleneck (aIB) algorithm suffers from the sub-optimality problem, which cannot guarantee to preserve as much relative information as possible. To handle this problem,  introduce a density connectivity chain, by which  consider not only the information beten two data elements, but also the information among the neighbors of a data element. Based on this idea,  propose DCIB, a density connectivity information bottleneck algorithm that applies the information bottleneck method to quantify the relative information during the clustering procedure. As a hierarchical algorithm, the DCIB algorithm produces a pruned clustering tree-structure and gets clustering results in different sizes in a single execution. The experiment results in the documentation clustering indicate that the DCIB algorithm can preserve more relative information and achieve higher precision than the aIB algorithm.
['Yongli Ren', 'Yangdong Ye', 'Gang Li']
I am writing a research paper on a idea The Density Connectivity Information Bottleneck
[{"from": "human", "value": "I am writing a research paper on a idea The Density Connectivity Information Bottleneck"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Clustering with the agglomerative information bottleneck (aIB) algorithm suffers from the sub-optimality problem, which cannot guarantee to preserve as much relative information as possible. To handle this problem,  introduce a density connectivity chain, by which  consider not only the information beten two data elements, but also the information among the neighbors of a data element. Based on this idea,  propose DCIB, a density connectivity information bottleneck algorithm that applies the information bottleneck method to quantify the relative information during the clustering procedure. As a hierarchical algorithm, the DCIB algorithm produces a pruned clustering tree-structure and gets clustering results in different sizes in a single execution. The experiment results in the documentation clustering indicate that the DCIB algorithm can preserve more relative information and achieve higher precision than the aIB algorithm."}]