Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Traditional clustering models define similarity by distance over dimensions. Hover, distance functions are not always adequate in capturing correlations among the objects. Pattern-based clustering can discover this kind of clusters. But state-of-the-art pattern-based clustering methods are inefficient and haven't criteria to evaluate the quality of clusters.  presents a novel pattern similarity-based subspace clustering with the pattern tree (PPSC for short) that offers these capabilities. The method uses new evaluation criteria to discover best clusters, which enables user to find clusters according to different needs. Meanwhile, observing the analogy beten mining frequent itemsets and discovering subspace clusters around random points,  apply the pattern-tree to determine subspace by scanning the database once, so it can perform efficiently in large datasets.
['Yanglan Gan', 'Jihong Guan', 'Hao Wang']
I am writing a research paper on a idea A Fast Subspace Clustering Algorithm Based on Pattern Similarity
[{"from": "human", "value": "I am writing a research paper on a idea A Fast Subspace Clustering Algorithm Based on Pattern Similarity"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Traditional clustering models define similarity by distance over dimensions. Hover, distance functions are not always adequate in capturing correlations among the objects. Pattern-based clustering can discover this kind of clusters. But state-of-the-art pattern-based clustering methods are inefficient and haven't criteria to evaluate the quality of clusters.  presents a novel pattern similarity-based subspace clustering with the pattern tree (PPSC for short) that offers these capabilities. The method uses new evaluation criteria to discover best clusters, which enables user to find clusters according to different needs. Meanwhile, observing the analogy beten mining frequent itemsets and discovering subspace clusters around random points,  apply the pattern-tree to determine subspace by scanning the database once, so it can perform efficiently in large datasets."}]