Titlebook: Similarity Search and Applications; 6th International Co Nieves Brisaboa,Oscar Pedreira,Pavel Zezula Conference proceedings 2013 Springer-V

有斑点

巧思

Evaluation of LBP Variants Using Several Metrics and kNN Classifiersnary pattern (LBP) as well as some of its most recent variants: Adaptive Local Binary Pattern (ALBP), Complete Local Binary Pattern (CLBP) and Local Binary Pattern Variance (LBPV). All the descriptors have been tested using two different dataset, KTH-TIPS 2a, a challenging multiclass dataset for mat

Emmenagogue

Evaluation of Jensen-Shannon Distance over Sparse Datahas other properties which make it an excellent choice for many high-dimensional spaces in ℝ...The metric as defined is however expensive to evaluate. In sparse spaces over many dimensions the Intrinsic Dimensionality of the metric space is typically very high, making similarity-based indexing ineff

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拔出

Text Categorization via Similarity Searchsion of the 2012 Cybersecurity Data Mining Competition (CDMC’2012) and a 3rd prize overall. The algorithm is quite different from existing approaches in that it is based on similarity search in the metric space of measure distributions on the dictionary. At the preprocessing stage, given a labeled l

果仁

Quantized Ranking for Permutation-Based Indexingndexing strategy is built to be fast, memory efficient and scalable without excessively sacrificing on search precision. This is experimentally demonstrated in comparison to existing proposals using several large-scale dataset of millions of documents and different dimensions.

畏缩

Quicker Similarity Joins in Metric Spacesithm probabilistic while still obtaining most of the relevant results. We also show how to use Quickjoin to compute .-nearest neighbor joins. The experimental results show that the method works well in practice.

表否定

Evaluation of Different Metrics for Shape Based Image Retrieval Using a New Contour Points Descriptoatest difference between the original method and our proposal can be seen clearly using MPEG2 dataset. Another advantage of our retrieval method, apart from the success rate, is the computational cost which is clearly better than the one achieved with the original Earth Mover Distance classifier used in the CPDH original method.

不能逃避

Text Categorization via Similarity Searchion stage, an unlabeled text is assigned a text category as defined by the closest labeled neighbour to the point representing the frequency distribution of the words in the text. The algorithm is both effective and efficient, as further confirmed by experiments on the Reuters 21578 dataset.