We propose several efficient data structures for the exact and approximate variants of the fair near neighbor problem.
Martin Aumüller, Sariel Har-Peled, Sepideh Mahabadi, Rasmus Pagh, Francesco Silvestri From Communications of the ACM | August 2022
In "Sampling Near Neighbors in Search for Fairness," Aumüller et al. investigate a basic problem in similarity search called near neighbor in the context of fair...Qin Zhang From Communications of the ACM | August 2022
"Expressive Querying for Accelerating Visual Analytics," by Tarique Siddiqui et al., provides a general abstraction, along with advanced interfaces, focusing on...Bill Howe From Communications of the ACM | July 2022
In this work, we introduce the problem of visualization search and highlight two underlying challenges of search enumeration and visualization matching.
Tarique Siddiqui, Paul Luh, Zesheng Wang, Karrie Karahalios, Aditya G. Parameswaran From Communications of the ACM | July 2022
"On Sampled Metrics for Item Recommendation," by Walid Krichene and Steffen Rendle, exposes a crucial aspect for the evaluation of algorithms and tools: the impact...Fabio Vandin From Communications of the ACM | July 2022
This paper investigates sampled metrics and shows that it is possible to improve the quality of sampled metrics by applying a correction, obtained by minimizing...Walid Krichene, Steffen Rendle From Communications of the ACM | July 2022
In "FANG," the authors focus on a strategy of automatically detecting disinformation campaigns on online media with a new graph-based, contextual technique for...Philippe Cudré-Mauroux From Communications of the ACM | April 2022
We propose Factual News Graph (FANG), a novel graphical social context representation and learning framework for fake news detection.
Van-Hoang Nguyen, Kazunari Sugiyama, Preslav Nakov, Min-Yen Kan From Communications of the ACM | April 2022
"Supporting People with Autism Spectrum Disorders in the Exploration of PoIs" is an example of work that takes seriously the task of supporting a small group that...Robin Burke From Communications of the ACM | February 2022
We propose a novel Top-N recommendation model that combines information about an autistic user's idiosyncratic aversions with her/his preferences in a personalized...Noemi Mauro, Liliana Ardissono, Federica Cena From Communications of the ACM | February 2022
"Multi-Itinerary Optimization as Cloud Service," by Alexandru Cristian et al., makes accessible an end-to-end cloud service that produces traffic-aware, real-time...Pascal Van Hentenryck From Communications of the ACM | November 2021
We describe multi-itinerary optimization, a novel Bing Maps service that automates the process of building itineraries for multiple agents while optimizing their...Alexandru Cristian, Luke Marshall, Mihai Negrea, Flavius Stoichescu, Peiwei Cao, Ishai Menache From Communications of the ACM | November 2021
"WINOGRANDE" explores new methods of dataset development and adversarial filtering, expressly designed to prevent AI systems from making claims of smashing through...Leora Morgenstern From Communications of the ACM | September 2021
We introduce WinoGrande, a large-scale dataset of 44k problems, inspired by the original Winograd Schema Challenge, but adjusted to improve both the scale and the...Keisuke Sakaguchi, Ronan Le Bras, Chandra Bhagavatula, Yejin Choi From Communications of the ACM | September 2021
The authors of "Succinct Range Filters" make a critical and insightful observation: For a given set of queries, the upper levels of the trie incur many more accesses...Stratos Idreos From Communications of the ACM | April 2021
We present the Succinct Range Filter (SuRF), a fast and compact data structure for approximate membership tests.
Huanchen Zhang, Hyeontaek Lim, Viktor Leis, David G. Andersen, Michael Kaminsky, Kimberly Keeton, Andrew Pavlo From Communications of the ACM | April 2021
There are few algorithms for multi-flow graphs beyond flow accumulation. The authors of "Flood-Risk Analysis on Terrains" take a big step to fill this knowledge...Shashi Shekhar From Communications of the ACM | September 2020
In this paper, we study a number of flood-risk related problems, give an overview of efficient algorithms for them, as well as explore the efficacy and efficiency...Aaron Lowe, Pankaj K. Agarwal, Mathias Rav From Communications of the ACM | September 2020
"Computing Value of Spatiotemporal Information," by Heba Aly et al., describes a technique for computing the monetary value of a person's location data for a potential...Cyrus Shahabi From Communications of the ACM | September 2020
We investigate the intrinsic value of location data in the context of strong privacy, where location information is only available from end users via purchase.
...Heba Aly, John Krumm, Gireeja Ranade, Eric Horvitz From Communications of the ACM | September 2020