The 13th International Conference on Similarity Search and Applications (SISAP) is an annual forum for researchers and application developers in the area of similarity data management. It aims at the technological problems shared by numerous application domains, such as data mining, information retrieval, multimedia retrieval, computer vision, pattern recognition, computational biology, geography, biometrics, machine learning, and many others that make use of similarity search as a necessary supporting service. From its roots in metric indexing, SISAP has expanded to become the only international conference entirely devoted to all issues surrounding the theory, design, analysis, practice, and application of content-based and feature-based similarity search.

Website: http://sisap.org/2020/

Topics of Interest
------------------

The specific topics include, but are not limited to:

- Similarity
  - Similarity queries (k-NN, range, reverse NN, top-k, approximate, etc.)
  - Similarity measures (graph, structural, time series, complex data, tensors, secondary similarity, etc.)
  - Similarity operations (joins, ranking, classification, categorization, filtering, etc.)
- Scalability
  - Indexing and access methods for similarity-based processing
  - High-performance/large-scale similarity search (distributed, parallel, etc.)
  - Data management (transaction support, dynamic maintenance, etc.)
- Theory
  - Languages for similarity databases
  - Models of similarity
  - Intrinsic dimensionality
  - Discriminability and contrast
  - Manifolds and subspaces
- Analytics, Learning, Artificial Intelligence
  - Visual analytics for similarity-based operations
  - Feature selection and extraction for similarity search
  - Merging/combining multiple similarity modalities
  - Learning/adaptive similarity measures
  - Similarity in learning and mining
- Evaluation
  - Evaluation techniques for similarity queries and operations
  - Cost models and analysis for similarity data processing
  - Performance studies and comparisons
  - Test collections and benchmarks
- Applications
  - Multimedia retrieval systems
  - Applications of similarity-based operations
  - Industrial applications and case studies
  - Similarity for forensics and security
  - Similarity search cloud services
  - Security and privacy of in similarity search

Special Sessions
----------------

SISAP 2020 will feature the following three special sessions:

- Artificial Intelligence and Similarity (organized by Giuseppe Amato, Fabrizio Falchi, Claudio Gennaro, and Fabio Carrara)
- Adversarial Machine Learning & Similarity (AMLS) (organized by Laurent Amsaleg and Michael Houle)
- Similarity Techniques in Machine Learning (SiTe-ML) (organized by Anshumali Shrivastava, Sanjiv Kumar, and Rasmus Pagh)

Special session papers will supplement the regular research papers and be included in the proceedings of SISAP 2020, which will be published by Springer as a volume in the Lecture Notes in Computer Science (LNCS) series.

Please see the website at http://sisap.org/2020/ for more information about these special sessions.