Communications of the ACM
Latest Research
From Communications of the ACM
Sampling Near Neighbors in Search for Fairness
We propose several efficient data structures for the exact and approximate variants of the fair near neighbor problem.
From Communications of the ACM
Technical Perspective: Can Data Structures Treat Us Fairly?
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...
From Communications of the ACM
Technical Perspective: Visualization Search: From Sketching to Natural Language
"Expressive Querying for Accelerating Visual Analytics," by Tarique Siddiqui et al., provides a general abstraction, along with advanced interfaces, focusing on...
From Communications of the ACM
Expressive Querying for Accelerating Visual Analytics
In this work, we introduce the problem of visualization search and highlight two underlying challenges of search enumeration and visualization matching.
From Communications of the ACM
Technical Perspective: Evaluating Sampled Metrics Is Challenging
"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...
From Communications of the ACM
On Sampled Metrics for Item Recommendation
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...
From Communications of the ACM
Technical Perspective: Leveraging Social Context for Fake News Detection
In "FANG," the authors focus on a strategy of automatically detecting disinformation campaigns on online media with a new graph-based, contextual technique for...
From Communications of the ACM
FANG: Leveraging Social Context for Fake News Detection Using Graph Representation
We propose Factual News Graph (FANG), a novel graphical social context representation and learning framework for fake news detection.
From Communications of the ACM
Technical Perspective: Personalized Recommendation of PoIs to People with Autism
"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...
From Communications of the ACM
Supporting People with Autism Spectrum Disorders in the Exploration of PoIs: An Inclusive Recommender System
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...
From Communications of the ACM
Technical Perspective: Finding the Sweet Spot Amid Accuracy and Performance
"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...
From Communications of the ACM
Multi-Itinerary Optimization as Cloud Service
We describe multi-itinerary optimization, a novel Bing Maps service that automates the process of building itineraries for multiple agents while optimizing their...
From Communications of the ACM
Technical Perspective: The Importance of WINOGRANDE
"WINOGRANDE" explores new methods of dataset development and adversarial filtering, expressly designed to prevent AI systems from making claims of smashing through...
From Communications of the ACM
WinoGrande: An Adversarial Winograd Schema Challenge at Scale
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...
From Communications of the ACM
Technical Perspective: The Strength of SuRF
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...
From Communications of the ACM
Succinct Range Filters
We present the Succinct Range Filter (SuRF), a fast and compact data structure for approximate membership tests.
From Communications of the ACM
Technical Perspective: Progress in Spatial Computing for Flood Prediction
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...
From Communications of the ACM
Flood-Risk Analysis on Terrains
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...
From Communications of the ACM
Technical Perspective: Computing the Value of Location Data
"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...
From Communications of the ACM