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Sampling Near Neighbors in Search for Fairness
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.

Technical Perspective: Can Data Structures Treat Us Fairly?
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...

Technical Perspective: Visualization Search: From Sketching to Natural Language
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...

Expressive Querying for Accelerating Visual Analytics
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.

Technical Perspective: Evaluating Sampled Metrics Is Challenging
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...

On Sampled Metrics for Item Recommendation
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...

Technical Perspective: Leveraging Social Context for Fake News Detection
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...

FANG
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.

Technical Perspective: Personalized Recommendation of PoIs to People with Autism
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...

Supporting People with Autism Spectrum Disorders in the Exploration of PoIs
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...

Technical Perspective: Finding the Sweet Spot Amid Accuracy and Performance
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...

Multi-Itinerary Optimization as Cloud Service
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...

Technical Perspective: The Importance of WINOGRANDE
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...

WinoGrande
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...

Succinct Range Filters
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...

Flood-Risk Analysis on Terrains
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...

Computing Value of Spatiotemporal Information
From Communications of the ACM

Computing Value of Spatiotemporal Information

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. ...
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