Titlebook: Similarity Search and Applications; 15th International C Tomáš Skopal,Fabrizio Falchi,Marco Patella Conference proceedings 2022 The Editor(

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On the Expected Exclusion Power of Binary Partitions for Metric Searchtion defined over the space, therefore each element of the space is contained within precisely one of the equivalence classes of the partition. All attempts to search a finite space efficiently, whether exactly or approximately, rely on some set of principles which imply that if the query is within

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Similarity Search with the Distance Density Modelts of identity and symmetry prevent from expressing the subjectivity and dependence on the context perceived by humans. In this paper, we study the suitability of the Distance density model of similarity for searching. First, we use the Local Outlier Factor (LOF) to estimate a data density in search

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Generalized Relative Neighborhood Graph (GRNG) for Similarity Search the .NN approach. We suggest, however, that the notion of a neighbor must recognize higher-order relationship, to capture neighbors in all directions. Proximity graphs, such as the Relative Neighbor Graphs (RNG), use . relationships which capture the notion of direction and have been successfully u

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HubHSP Graph: Effective Data Sampling for Pivot-Based Representation Strategiesrategies to seed algorithms (such as .-means) and for pivot-based data indexing techniques. We discuss the geometrical and statistical facets of such a definition..We propose the Hubness Half Space Partitioning (HubHSP) strategy as an effective sampling heuristic that combines both geometric and sta

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Graph Edit Distance Compacted Search Treees the different edit operations by numbers and the needed remaining vertices and edges by BitSets. The second represents the tree succinctly by bit-vectors. The proposed methods require 24 to 250 times less memory than traditional versions without negatively influencing the running time.

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Clustering by Direct Optimization of the Medoid Silhouetteerent clustering quality measures, which try to provide a general measure to validate clustering results. A very popular measure is the Silhouette. We discuss the efficient medoid-based variant of the Silhouette, perform a theoretical analysis of its properties, and provide two fast versions for the

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Conference proceedings 2022, Italy in October 2022..SISAP 2022 is an annual international conference for researchers focusing on similarity search challenges and related theoretical/practical problems, as well as the design of content-based similarity search applications. The 15 full papers presented together with 8 short and