"Leveraging Social Media to Buy Fake Reviews," by Sherry He et al., represents a breakthrough in our empirical understanding of fake reviews on Amazon.
Shreyas Sekar From Communications of the ACM | October 2023
In "A Manifold View of Connectivity in the Private Backbone Networks of Hyperscalers," Salamatian et al. assemble techniques from the two broad strategies developed...Sara Alouf From Communications of the ACM | August 2023
We present a new empirical approach for elucidating connectivity in privately owned and operated backbone networks.
Loqman Salamatian, Scott Anderson, Joshua Mathews, Paul Barford, Walter Willinger, Mark Crovella From Communications of the ACM | August 2023
The authors of "Offline and Online Algorithms for SSD Management" propose a more accurate theoretical model of flash-based SSDs that views each page as containing...Ramesh K. Sitaraman From Communications of the ACM | July 2023
We explore the problem of reducing high internal overhead of flash media which is referred to as write amplification from an algorithmic perspective, considering...Tomer Lange, Joseph (Seffi) Naor, Gala Yadgar From Communications of the ACM | July 2023
FoundationDB, as explored in "FoundationDB: A Distributed Key-Value Store," by Jingyu Zhou et al., pioneered the development of a scalable distributed key-value...Alfons Kemper From Communications of the ACM | June 2023
FoundationDB, an open-source transactional key-value store, is one of the first systems to combine the flexibility and scalability of NoSQL architectures with the...Jingyu Zhou, Meng Xu, Alexander Shraer, Bala Namasivayam, Alex Miller, Evan Tschannen, Steve Atherton, Andrew J. Beamon, Rusty Sears, John Leach, Dave Rosenthal, Xin Dong, Will Wilson, Ben Collins, David Scherer, Alec Grieser, Yang Liu, Alvin Moore, Bhaskar Muppana, Xiaoge Su, Vishesh Yadav From Communications of the ACM | June 2023
"Traffic Classification in an Increasingly Encrypted Web," by Iman Akbari et al., does a great job in reviewing related work in the network traffic classification...Athina Markopoulou From Communications of the ACM | October 2022
In this paper, we design a novel feature engineering approach used for encrypted Web protocols, and develop a neural network architecture based on stacked long...Iman Akbari, Mohammad A. Salahuddin, Leni Ven, Noura Limam, Raouf Boutaba, Bertrand Mathieu, Stephanie Moteau, Stephane Tuffin From Communications of the ACM | October 2022
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
The authors of "Cognitive Biases in Software Development" rightly highlight the need for situated studies that examine cognitive bias 'in the wild' during software...Marian Petre From Communications of the ACM | April 2022
We conducted a two-part field study to examine the extent to which cognitive biases occur, the consequences of these biases on developer behavior, and the practices...Souti Chattopadhyay, Nicholas Nelson, Audrey Au, Natalia Morales, Christopher Sanchez, Rahul Pandita, Anita Sarma From Communications of the ACM | April 2022