SISAP 2015 : 8th International Conference on Similarity Search and Applications
Conference Series : Similarity Search and Applications
Call For Papers
CALL FOR PAPERS - SISAP 2015
8th International Conference on Similarity Search and Applications
Glasgow, Scotland, UK, October, 12 - 14, 2015
The 8th 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.
The specific topics include, but are not limited to:
• Similarity queries – k-NN, range, reverse NN, top-k, etc.
• Similarity operations – joins, ranking, classification, categorization, filtering, etc.
• Evaluation techniques for similarity queries and operations
• Merging/combining multiple similarity modalities
• Cost models and analysis for similarity data processing
• Indexing and access methods for similarity-based processing
• Scalability issues and high-performance similarity data management
• Feature extraction for similarity-based indexing and retrieval
• Feature selection
• Test collections and benchmarks
• Performance studies, benchmarks, and comparisons
• Similarity search over outsourced data repositories
• Similarity search cloud services
• Languages for similarity databases
• New modes of similarity for complex data understanding
• Applications of similarity-based operations
• Visual analitics for similarity-based operations
• Image, video, voice, and music (multimedia) retrieval systems
• Similarity for forensics and security
• Surveillance and defense
Paper Submission and Publication
Papers submitted to SISAP 2015 must be written in English and formatted according to the LNCS guidelines (http://www.springer.com/computer/lncs). Full papers can be up to 12 pages, while short papers, case-studies/applications, and demos can be up to 6 pages (read below for types of contribution). By submitting a paper, its authors commit to having the paper presented at the conference by at least one of them if the paper is accepted.
Papers will be submitted in PDF format through EasyChair (https://www.easychair.org/conferences/?conf=sisap2015).
If you experience any problems during the submission, you can contact the organization at firstname.lastname@example.org
Authors are invited to submit previously unpublished papers on their research in the area of similarity search and applications. Papers should present original research contributions which bring out the importance of algorithms to applications. SISAP submissions can be of three kinds (full details will be announced shortly):
• Papers (full and short): SISAP accepts both full (12 pages) and short papers (6 pages). The full papers are expected to be descriptions of complete technical work, while the short papers will describe interesting, innovative ideas, which nevertheless require more work to mature - vision papers should also be submitted as short papers. Contributions can also describe applications of existing similarity search technologies to interesting problems, including a description of the encountered challenges, how they were overcome, and the lessons learned. All papers, regardless of size, will be given an entry in the conference proceedings.
• Demonstration papers: Submissions should provide the motivation for the demonstrated concepts, the information about the technology and the system to be demonstrated (including a system description, functionality and figures when applicable), and should state the significance of the contribution. Evaluation criteria for the demonstration proposals include: the novelty, the technical advances and challenges, and the overall practical attractiveness of the demonstrated system. Demonstration papers (4 pages) will also be given an entry in the conference proceedings – online demos are expected at the conference.
• Posters: Domain-specific spaces and similarities: papers that challenge and motivate for searching in new spaces (i.e. domain-specific similarity search). This type of contribution is expected to provide a thorough study of the non/metric space properties (e.g., its intrinsic dimension) or the similarity measure, and must include code for the similarity computation and datasets for the Web site. For this kind of paper a real-world domain-specific application of similarity search is expected (e.g., multimedia databases, (bio)chemical & medical databases, biometric databases, scientific & sensory databases, etc.). Poster contributions (6 pages) will also be given an entry in the conference proceedings.
Special Session for Industry
A special session devoted to industrial applications and case studies on similarity search will also take place. A separate call for papers will be issued later in due time.
When: October 12-14, 2015
Where: Glasgow, Scotland, UK
Abstract Registration: May 18, 2015 (Extended)
Submission Deadline: May 25, 2015 (Extended)
Notification: June 29, 2015 (Extended)
Final Version: July 19, 2015 (Extended)
Publication: Lecture Notes in Computer Science (LNCS), and selected best papers will be hosted in a special section of Information Systems journal.
K. Bobby Jaros - Yahoo Labs.: Deep Learning and Similarity Search
Rasmus Pagh - IT University of Copenhagen, Denmark: Large-scale Similarity Joins
Billy Wallace - Founding Developer, ThinkAnalytics: Television Recommender Systems
Local arrangements and Finance chair
Richard Connor, University of Strathclyde, Glasgow, UK
Edgar Chavez, Universidad Nacional Autónoma de México, Mexico
Pavel Zezula, Masaryk University, Czech Republic
Richard Connor, University of Strathclyde, Glasgow, UK
Giuseppe Amato, ISTI - CNR, Pisa, Italy
Claudio Gennaro, ISTI - CNR, Pisa, Italy
Fabrizio Falchi, ISTI - CNR, Pisa, Italy