12th International Conference on Similarity Search and Applications SISAP 2019
The 12th 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, computer vision, pattern recognition, computational biology, geography, biometrics, machine learning, and many others that need similarity searching as a necessary supporting service.
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. The Best Paper Award carries a prize of EUR 1,000 Euro (thanks to the generosity of Springer). SISAP will take place in Newark NJ, USA
SISAP is one of the 4374 conference ranked by Microsoft Academic (https://academic.microsoft.com/conferences).
Rank with respect to H-Index, on a Five Years time span is: Topic: Computer science->Machine learning->k-nearest neighbors algorithm->Nearest neighbor search: rank 6 (https://academic.microsoft.com/conferences/41008148,119857082,113238511,116738811) Topic:Computer Science->Information Retrieval->Search Engine Indexing: rank 15 (https://academic.microsoft.com/conferences/41008148,23123220,75165309) Topic:Computer Science->Computer Vision->Image Retrieval: rank 19 (https://academic.microsoft.com/conferences/41008148,31972630,1667742) Topic: Computer science->Machine learning->k-nearest neighbors algorithm: rank 29 (https://academic.microsoft.com/conferences/41008148,119857082,113238511)
