13th International Conference on Similarity Search and Applications, SISAP 2020

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 need similarity searching as a necessary supporting service. Please see the call for papers for more details.

This year's SISAP features a special session on Artificial Intelligence and Similarity & Similarity Techniques in Machine Learning.

SISAP 2020 also features a doctoral symposium. If you are a PhD student, please consider submitting a paper about your project.

The SISAP initiative (www.sisap.org) aims to become a forum to exchange real-world, challenging and innovative examples of applications, new indexing techniques, common test-beds and benchmarks, source code and up-to-date literature through its web page, serving the similarity search community. Traditionally, SISAP puts emphasis on the distance-based searching, but in general the conference concerns both the effectiveness and efficiency aspects of any similarity search problem.

The series started in 2008 as a workshop and has developed over the years into an international conference with Lecture Notes in Computer Science (LNCS) proceedings. As in previous editions, a small selection of the best papers presented at the conference will be recommended for inclusion in a special issue of Information Systems. There will be a Best Paper and Best Student Paper Award. The best student paper award carries a prize of EUR 500 Euro (thanks to the generosity of Springer). SISAP will take place in Copenhagen, Denmark.