Term-weighting approaches in automatic text retrieval
Information Processing and Management: an International Journal
ACM Computing Surveys (CSUR)
A vector space model for automatic indexing
Communications of the ACM
The Earth Mover's Distance as a Metric for Image Retrieval
International Journal of Computer Vision
Machine learning in automated text categorization
ACM Computing Surveys (CSUR)
Image indexing and retrieval using signature trees
Data & Knowledge Engineering
Efficient Color Histogram Indexing for Quadratic Form Distance Functions
IEEE Transactions on Pattern Analysis and Machine Intelligence
Exploiting hierarchical domain structure to compute similarity
ACM Transactions on Information Systems (TOIS)
Projective Clustering by Histograms
IEEE Transactions on Knowledge and Data Engineering
Query by image and video content: a colored-based stochastic model approach
Data & Knowledge Engineering
Signatures versus histograms: Definitions, distances and algorithms
Pattern Recognition
A survey of content-based image retrieval with high-level semantics
Pattern Recognition
An Efficient Earth Mover's Distance Algorithm for Robust Histogram Comparison
IEEE Transactions on Pattern Analysis and Machine Intelligence
A new similarity measure for histogram comparison and its application in time series analysis
Pattern Recognition Letters
Taxonomy of nominal type histogram distance measures
MATH'08 Proceedings of the American Conference on Applied Mathematics
A Communication Perspective on Automatic Text Categorization
IEEE Transactions on Knowledge and Data Engineering
Collaborative clustering with background knowledge
Data & Knowledge Engineering
Histogram similarity measure using variable bin size distance
Computer Vision and Image Understanding
Approximating sliding windows by cyclic tree-like histograms for efficient range queries
Data & Knowledge Engineering
From frequency to meaning: vector space models of semantics
Journal of Artificial Intelligence Research
The quadratic-chi histogram distance family
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part II
Multi-resolution region-based clustering for urban analysis
International Journal of Remote Sensing - Spatial Information Retrieval, Analysis, Reasoning and Modelling
Semantic hierarchies for image annotation: A survey
Pattern Recognition
Support vector machines for histogram-based image classification
IEEE Transactions on Neural Networks
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We propose a new distance called Hierarchical Semantic-Based Distance (HSBD), devoted to the comparison of nominal histograms equipped with a dissimilarity matrix providing the semantic correlations between the bins. The computation of this distance is based on a hierarchical strategy, progressively merging the considered instances (and their bins) according to their semantic proximity. For each level of this hierarchy, a standard bin-to-bin distance is computed between the corresponding pair of histograms. In order to obtain the proposed distance, these bin-to-bin distances are then fused by taking into account the semantic coherency of their associated level. From this modus operandi, the proposed distance can handle histograms which are generally compared thanks to cross-bin distances. It preserves the advantages of such cross-bin distances (namely robustness to histogram translation and histogram bin size issues), while inheriting the low computational cost of bin-to-bin distances. Validations in the context of geographical data classification emphasize the relevance and usefulness of the proposed distance.