Accepted Papers – SISAP 2021
14th International Conference on Similarity Search and Applications
Dortmund, Germany, Sept 29 – Oct 01, 2021
Accepted papers for the main conference (long and short papers, including the special sessions and the PhD Symposium):
- Fabian Fier and Johann-Christoph Freytag
Scaling Up Set Similarity Joins Using A Cost-Based Distributed-Parallel Framework - Lucas Gnecco Heredia, Nicolas Boria, Sébastien Bougleux, Florian Yger and David Blumenthal
The Minimum Edit Arborescence Problem and Its Use in Compressing Graph Collections - Felix Borutta, Peer Kröger and Matthias Renz
A Cost Model for Reverse Nearest Neighbor Query Processing on R-trees Using Self Pruning - Terézia Slanináková, Matej Antol, Jaroslav Oľha, Vojtěch Kaňa and Vlastislav Dohnal
Data-driven Learned Metric Index: an Unsupervised Approach - Miloš Savić, Vladimir Kurbalija and Miloš Radovanović
Local Intrinsic Dimensionality and Graphs: Towards LID-aware Graph Embedding Algorithms - Benjamin Paaßen
An A*-algorithm for the Unordered Tree Edit Distance with Custom Costs - Maciej Gawinecki, Wojciech Szmyd, Urszula Żuchowicz and Marcin Walas
What makes a movie good recommendation? Feature selection for Content-Based Filtering - Vladimir Mic, Tomáš Raček, Aleš Křenek and Pavel Zezula
Similarity Search for an Extreme Application: Experience & Implementation - Erich Schubert
A Triangle Inequality for Cosine Similarity - Franka Bause, David B. Blumenthal, Erich Schubert and Nils M. Kriege
Metric Indexing for Graph Similarity Search - Lucia Vadicamo, Claudio Gennaro and Giuseppe Amato
On Generalizing Permutation-Based Representations for Approximate Search - Stephane Marchand-Maillet, Oscar Pedreira and Edgar Chavez
Structural Intrinsic Dimensionality - James Bailey, Michael E. Houle and Xingjun Ma
Relationships between Local Intrinsic Dimensionality and Tail Entropy - Omid Jafari, Preeti Maurya, Khandker Mushfiqul Islam and Parth Nagarkar
Optimizing Fair Approximate Nearest Neighbor Searches using Threaded B+-Trees - Jakub Peschel, Michal Batko, Jakub Valcik, Jan Sedmidubsky and Pavel Zezula
FIMSIM: Discovering Communities by Frequent Item-Set Mining and Similarity Search - Maximilian Hünemörder, Peer Kröger and Matthias Renz
Towards a Learned Index Structure for Approximate Nearest Neighbor Search Query Processing - Mathias Fuchs and Kaspar Riesen
Graph Embedding in Vector Spaces Using Matching-Graphs - Tomas Skopal, David Bernhauer, Petr Skoda, Jakub Klimek and Martin Necasky
Similarity vs. Relevance: From Simple Searches to Complex Discovery - Erik Thordsen and Erich Schubert
MESS: Manifold Embedding Motivated Super Sampling - Miriama Jánošová, David Procházka and Vlastislav Dohnal
Organizing Similarity Spaces using Metric Hulls - Magnus Lie Hetland and Halvard Hummel
Fairest Neighbors: Tradeoffs Between Metric Queries - Ahmed Askar and Andreas Züfle
Clustering Adverse Events of COVID-19 Vaccines across the United States - Michael E. Houle and Ken-ichi Kawarabayashi
The Effect of Random Projection on Local Intrinsic Dimensionality - Erich Schubert, Andreas Lang and Gloria Feher
Accelerating Spherical k-Means - Jakub Lokoc and Tomáš Souček
How Many Neighbours for Known-item Search? - Jonatan Møller Nuutinen Gøttcke and Arthur Zimek
Handling Class Imbalance in k-Nearest Neighbor Classification by Balancing Prior Probabilities - Fernando Luque, Jorge L. López-López and Edgar Chavez
Indexed Polygon Matching under Similarities - Jonatan Møller Nuutinen Gøttcke, Arthur Zimek and Ricardo José Gabrielli Barreto Campello
Non-Parametric Semi-Supervised Learning by Bayesian Label Distribution Propagation - Marco Postiglione
Towards an Italian Healthcare Knowledge Graph - Luca Zecchini
Progressive Query-driven Entity Resolution - Fabrizio Scarrone
Discovering Latent Information from Noisy Sources in the Cultural Heritage Domain