Papers with AMOSA

1 papers
Incorporating Deep Visual Features into Multiobjective based Multi-view Search Results Clustering (C18-1)

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Challenge: Existing approaches to search result clustering use multiple views and visual and textual views.
Approach: They propose to use multi-view learning to learn search results from web-snippets . they propose to obtain a single consensus partitioning after consulting two views .
Outcome: The proposed approach on a benchmark dataset shows that visual and text-based views can achieve better clustering.

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