Tootfinder

Dreamdata, which offers a B2B marketing analytics platform, raised a $55M Series B led by PeakSpan, bringing its total funding to $67M (Mary Ann Azevedo/Crunchbase News)
https://news.crunchbase.com/venture/b2b-marketing-analytics-startup-dreamd…

Exclusive: B2B Marketing Analytics Startup Dreamdata Lands $55M Series B
Dreamdata, a B2B marketing analytics platform, has secured a $55 million Series B round of funding, the company told Crunchbase News exclusively.

"hey what does your database do?"
"uhhh Ads and analytics mostly"
"... and aaaaalso?"
"And also high energy physics at CERN."

Embodied Natural Language Interaction (NLI): Speech Input Patterns in Immersive Analytics
Hyemi Song, Matthew Johnson, Kirsten Whitley, Eric Krokos, Amitabh Varshney
https://arxiv.org/abs/2510.12156

Embodied Natural Language Interaction (NLI): Speech Input Patterns in Immersive Analytics
Embodiment shapes how users verbally express intent when interacting with data through speech interfaces in immersive analytics. Despite growing interest in Natural Language Interaction (NLI) for visual analytics in immersive environments, users' speech patterns and their use of embodiment cues in speech remain underexplored. Understanding their interplay is crucial to bridging the gap between users' intent and an immersive analytic system. To address this, we report the results from 15 partici…

Twenty-two U.S. states are either on the brink of an economic recession or already in one,
according to a new analysis from Moody's Analytics.
Moody's Chief Economist Mark Zandi shared the findings,
saying that states making up nearly a third of the national gross domestic product
are either in or at high risk of recession,
with another third just holding steady, and the remaining third growing.

Cumulus Media sues Nielsen, accusing it of anticompetitive moves by requiring the purchase of local radio ratings data in order to access its national analytics (Mike Scarcella/Reuters)
https://www.reuters.com/legal/litigation/r

COSTAR-A: A prompting framework for enhancing Large Language Model performance on Point-of-View questions
Nzubechukwu C. Ohalete (School of Data Science and Analytics, Kennesaw State University, GA, USA), Kevin B. Gittner (School of Data Science and Analytics, Kennesaw State University, GA, USA), Lauren M. Matheny (School of Data Science and Analytics, Kennesaw State University, GA, USA)

COSTAR-A: A prompting framework for enhancing Large Language Model performance on Point-of-View questions
Large Language Models (LLMs) are highly sensitive to prompt design, and making optimized prompting techniques is crucial for generating consistent, high-quality outputs. In this study, we introduce COSTAR-A, a novel prompt engineering framework that enhances the existing COSTAR method, which stands for Context, Objective, Style, Tone, Audience, and Response, by adding the 'Answer' component at the end. We demonstrate that while the original COSTAR framework improves prompt clarity and aligns ou…

Explainability, risk modeling, and segmentation based customer churn analytics for personalized retention in e-commerce
Sanjula De Alwis, Indrajith Ekanayake
https://arxiv.org/abs/2510.11604

Explainability, risk modeling, and segmentation based customer churn analytics for personalized retention in e-commerce
In online retail, customer acquisition typically incurs higher costs than customer retention, motivating firms to invest in churn analytics. However, many contemporary churn models operate as opaque black boxes, limiting insight into the determinants of attrition, the timing of retention opportunities, and the identification of high-risk customer segments. Accordingly, the emphasis should shift from prediction alone to the design of personalized retention strategies grounded in interpretable ev…

Real-Time Health Analytics Using Ontology-Driven Complex Event Processing and LLM Reasoning: A Tuberculosis Case Study
Ritesh Chandra, Sonali Agarwal, Navjot Singh
https://arxiv.org/abs/2510.09646

Real-Time Health Analytics Using Ontology-Driven Complex Event Processing and LLM Reasoning: A Tuberculosis Case Study
Timely detection of critical health conditions remains a major challenge in public health analytics, especially in Big Data environments characterized by high volume, rapid velocity, and diverse variety of clinical data. This study presents an ontology-enabled real-time analytics framework that integrates Complex Event Processing (CEP) and Large Language Models (LLMs) to enable intelligent health event detection and semantic reasoning over heterogeneous, high-velocity health data streams. The a…

Millions impacted by PornHub, SoundCloud data breaches https://therecord.media/millions-impacted-pornhub-soundcloud-breaches

Security — A data breach at analytics giant Mixpanel leaves a lot of open questions
A cybersecurity incident at analytics provider Mixpanel announced just hours before the U.S. Thanksgiving holiday weekend could set a new standard for how not to announce a data breach.
📍 https://

A data breach at analytics giant Mixpanel leaves a lot of open questions | TechCrunch
We sent over a dozen questions to Mixpanel's CEO about the company's data breach. Here's what we want to know.

Human-Centered Development of Indicators for Self-Service Learning Analytics: A Transparency through Exploration Approach
Shoeb Joarder, Mohamed Amine Chatti
https://arxiv.org/abs/2510.08395

Human-Centered Development of Indicators for Self-Service Learning Analytics: A Transparency through Exploration Approach
The aim of learning analytics is to turn educational data into insights, decisions, and actions to improve learning and teaching. The reasoning of the provided insights, decisions, and actions is often not transparent to the end-user, and this can lead to trust and acceptance issues when interventions, feedback, and recommendations fail. In this paper, we shed light on achieving transparent learning analytics by following a transparency through exploration approach. To this end, we present the …

Newsletter platform Beehiiv announces new features, including for AI website creation, podcast hosting, digital product sales, and real-time analytics (Dominic-Madori Davis/TechCrunch)
https://techcrunch.com/2025/11/13/news

Newsletter platform beehiiv adds AI website building, creator tools in major expansion | TechCrunch
Newsletter platform beehiiv announced a massive expansion to its platform on Thursday, including offering real-time analytics and AI website creation.

"The AFU are the only real fighting force left in Europe" – Peter Dickinson | Wrap-Up Analytics: https://benborges.xyz/2025/10/12/ampquotthe-afu-are-the-only.html

VisPile: A Visual Analytics System for Analyzing Multiple Text Documents With Large Language Models and Knowledge Graphs
Adam Coscia, Alex Endert
https://arxiv.org/abs/2510.09605

VisPile: A Visual Analytics System for Analyzing Multiple Text Documents With Large Language Models and Knowledge Graphs
Intelligence analysts perform sensemaking over collections of documents using various visual and analytic techniques to gain insights from large amounts of text. As data scales grow, our work explores how to leverage two AI technologies, large language models (LLMs) and knowledge graphs (KGs), in a visual text analysis tool, enhancing sensemaking and helping analysts keep pace. Collaborating with intelligence community experts, we developed a visual analytics system called VisPile. VisPile inte…

Prepared for the Unknown: Adapting AIOps Capacity Forecasting Models to Data Changes
Lorena Poenaru-Olaru, Wouter van 't Hof, Adrian Stando, Arkadiusz P. Trawinski, Eileen Kapel, Jan S. Rellermeyer, Luis Cruz, Arie van Deursen
https://arxiv.org/abs/2510.10320

Prepared for the Unknown: Adapting AIOps Capacity Forecasting Models to Data Changes
Capacity management is critical for software organizations to allocate resources effectively and meet operational demands. An important step in capacity management is predicting future resource needs often relies on data-driven analytics and machine learning (ML) forecasting models, which require frequent retraining to stay relevant as data evolves. Continuously retraining the forecasting models can be expensive and difficult to scale, posing a challenge for engineering teams tasked with balanc…

📈 #LogsQL query language provides fast full-text search, advanced analytics, and data extraction/transformation at query time. Can be combined with Unix tools like grep, less, sort, and jq for log analysis.
🎯 Optimized for high cardinality fields like trace_id, user_id, and ip addresses. Supports logs with hundreds of fields (wide events), multitenancy, out-of-order ingestion, live taili…

Alembic, which offers AI-powered data analytics for marketers, raised a $145M Series B led by Prysm and Accenture at a $645M valuation, up from $49M in 2024 (Patrick Coffee/Wall Street Journal)
https://www.wsj.com/articles/accenture-and

Replaced article(s) found for cs.AI. https://arxiv.org/list/cs.AI/new
[4/6]:
- VIDEE: Visual and Interactive Decomposition, Execution, and Evaluation of Text Analytics with Int...
Sam Yu-Te Lee, Chenyang Ji, Shicheng Wen, Lifu Huang, Dongyu Liu, Kwan-Liu Ma

Federated Data Analytics for Cancer Immunotherapy: A Privacy-Preserving Collaborative Platform for Patient Management
Mira Raheem, Michael Papazoglou, Bernd Kr\"amer, Neamat El-Tazi, Amal Elgammal
https://arxiv.org/abs/2510.09155

Federated Data Analytics for Cancer Immunotherapy: A Privacy-Preserving Collaborative Platform for Patient Management
Connected health is a multidisciplinary approach focused on health management, prioritizing pa-tient needs in the creation of tools, services, and treatments. This paradigm ensures proactive and efficient care by facilitating the timely exchange of accurate patient information among all stake-holders in the care continuum. The rise of digital technologies and process innovations promises to enhance connected health by integrating various healthcare data sources. This integration aims to persona…

Edge-to-Cloud Computations-as-a-Service in Software-Defined Energy Networks for Smart Grids
Jack Jackman, David Ryan, Arun Narayanan, Pedro Nardelli, Indrakshi Dey
https://arxiv.org/abs/2510.11286

Edge-to-Cloud Computations-as-a-Service in Software-Defined Energy Networks for Smart Grids
Modern power grids face an acute mismatch between where data is generated and where it can be processed: protection relays, EV (Electric Vehicle) charging, and distributed renewables demand millisecond analytics at the edge, while energy-hungry workloads often sit in distant clouds leading to missed real-time deadlines and wasted power. We address this by proposing, to our knowledge, the first-ever SDEN (Software Defined Energy Network) for CaaS (Computations-as-a-Service) that unifies edge, fo…

Parrot Analytics: movies made up ~50% of streaming revenue across Netflix, Prime Video, Disney , and WBD in 2024, up from ~27% in 2022, based on engagement data (Alejandro Rojas/The Hollywood Reporter)
https://www.hollywoodreporter.com/business/b…

How Movies Increasingly Drive Streaming Revenue
A Parrot Analytics analysis of thousands of titles across Amazon Prime Video, Disney+, Netflix, and Max finds that movies deliver disproportionately high engagement relative to the volume of content hours they represent.

Slicing Is All You Need: Towards A Universal One-Sided Algorithm for Distributed Matrix Multiplication
Benjamin Brock, Renato Golin
https://arxiv.org/abs/2510.08874 https://

Slicing Is All You Need: Towards A Universal One-Sided Algorithm for Distributed Matrix Multiplication
Many important applications across science, data analytics, and AI workloads depend on distributed matrix multiplication. Prior work has developed a large array of algorithms suitable for different problem sizes and partitionings including 1D, 2D, 1.5D, and 2.5D algorithms. A limitation of current work is that existing algorithms are limited to a subset of partitionings. Multiple algorithm implementations are required to support the full space of possible partitionings. If no algorithm implemen…

Spiral Model Technique For Data Science & Machine Learning Lifecycle
Rohith Mahadevan
https://arxiv.org/abs/2510.06987 https://arxiv.org/pdf/2510.06987…

Spiral Model Technique For Data Science & Machine Learning Lifecycle
Analytics play an important role in modern business. Companies adapt data science lifecycles to their culture to seek productivity and improve their competitiveness among others. Data science lifecycles are fairly an important contributing factor to start and end a project that are data dependent. Data science and Machine learning life cycles comprises of series of steps that are involved in a project. A typical life cycle states that it is a linear or cyclical model that revolves around. It is…

MobilityDuck: Mobility Data Management with DuckDB
Nhu Ngoc Hoang, Ngoc Hoa Pham, Viet Phuong Hoang, Esteban Zim\'anyi
https://arxiv.org/abs/2510.07963 https://

MobilityDuck: Mobility Data Management with DuckDB
The analytics of spatiotemporal data is increasingly important for mobility analytics. Despite extensive research on moving object databases (MODs), few systems are ready on production or lightweight enough for analytics. MobilityDB is a notable system that extends PostgreSQL with spatiotemporal data, but it inherits complexity of the architecture as well. In this paper, we present MobilityDuck, a DuckDB extension that integrates the MEOS library to provide support spatiotemporal and other temp…

Generative AI for Software Project Management: Insights from a Review of Software Practitioner Literature
Lakshana Iruni Assalaarachchi, Zainab Masood, Rashina Hoda, John Grundy
https://arxiv.org/abs/2510.10887

Generative AI for Software Project Management: Insights from a Review of Software Practitioner Literature
Software practitioners are discussing GenAI transformations in software project management openly and widely. To understand the state of affairs, we performed a grey literature review using 47 publicly available practitioner sources including blogs, articles, and industry reports. We found that software project managers primarily perceive GenAI as an "assistant", "copilot", or "friend" rather than as a "PM replacement", with support of GenAI in automating routine tasks, predictive analytics, co…

Troy Aikman's guiding principle for 'Monday Night Football': 'I try to be fair' https://www.nytimes.com/athletic/6869981/2025/12/09/troy-aikman-espn-mnfl-nfl-joe-buck/

The Virginia Community College System (#AS22845) had long been announcing two IPv4 prefixes, a /16 and a /24. Most of the /16 has now been disaggregated.
A variety of explanations could account for such a major change, such as:
1. Operational mistake
2. Prelude to re-allocate or transfer
3. Traffic engineering
4. DDoS mitigation

Troy Aikman's guiding principle for 'Monday Night Football': 'I try to be fair' https://www.nytimes.com/athletic/6869981/2025/12/09/troy-aikman-espn-mnfl-nfl-joe-buck/

Glen Grant: “Putin’s Army Is Bleeding, But the West Still Doesn’t Get It” | Wrap-Up Analytics: https://benborges.xyz/2025/11/09/glen-grant-putins-army-is.html

Bernstein Analytics enthüllt: KI-Chatbots zitieren am liebsten die #Tagesschau. Der Grund? Öffentlich-rechtliche Inhalte sind für Tech-Konzerne gratis. Wer Bezahlschranken hat, wird ignoriert. (Wen wundert es?) Die #FAZ fragt natürlich : Wer entscheidet hier über ‚Relevanz‘ – Algorithmen oder der Mar…

KI-Chatbots greifen am häufigsten auf tagesschau.de als Quelle zurück
Die Firma Bernstein Analytics hat untersucht, wen ChatGPT, Gemini, Perplexity und Grok im deutschsprachigen Raum auf häufigsten zitieren. Es ist tagesschau.de. Dafür gibt es einen Grund, den die Erhebung nicht nennt.

Troy Aikman's guiding principle for 'Monday Night Football': 'I try to be fair' https://www.nytimes.com/athletic/6869981/2025/12/09/troy-aikman-espn-mnfl-nfl-joe-buck/

Degradation-Aware Model Predictive Control for Battery Swapping Stations under Energy Arbitrage
Ruochen Li (Department of Systems Engineering, City University of Hong Kong, Kowloon, Hong Kong, China), Zhichao Chen (Department of Systems Engineering, City University of Hong Kong, Kowloon, Hong Kong, China), Zhaoting Zhang (Department of Systems Engineering, City University of Hong Kong, Kowloon, Hong Kong, China), Renjie Guo (Department of Decision Analytics and Operations, City Univers…

Degradation-Aware Model Predictive Control for Battery Swapping Stations under Energy Arbitrage
Battery swapping stations (BSS) offer a fast and scalable alternative to conventional electric vehicle (EV) charging, gaining growing policy support worldwide. However, existing BSS control strategies typically rely on heuristics or low-fidelity degradation models, limiting profitability and service level. This paper proposes BSS-MPC: a real-time, degradation-aware Model Predictive Control (MPC) framework for BSS operations to trade off economic incentives from energy market arbitrage and long-…

Opal: A Modular Framework for Optimizing Performance using Analytics and LLMs
Mohammad Zaeed, Tanzima Z. Islam, Vladimir In{\dj}i\'c
https://arxiv.org/abs/2510.00932 https:/…

Opal: A Modular Framework for Optimizing Performance using Analytics and LLMs
Large Language Models (LLMs) show promise for automated code optimization but struggle without performance context. This work introduces Opal, a modular framework that connects performance analytics insights with the vast body of published by guiding LLMs to generate informed, trustworthy optimizations. Unlike traditional performance tools that identify bottlenecks but stop short of actionable suggestions, Opal bridges this long-standing gap by linking dynamic insights from hardware counters an…

Unveiling Gamer Archetypes through Multi modal feature Correlations and Unsupervised Learning
Moona Kanwal, Muhammad Sami Siddiqui, Syed Anael Ali
https://arxiv.org/abs/2510.10263

Unveiling Gamer Archetypes through Multi modal feature Correlations and Unsupervised Learning
Profiling gamers provides critical insights for adaptive game design, behavioral understanding, and digital well-being. This study proposes an integrated, data-driven framework that combines psychological measures, behavioral analytics, and machine learning to reveal underlying gamer personas. A structured survey of 250 participants, including 113 active gamers, captured multidimensional behavioral, motivational, and social data. The analysis pipeline integrated feature engineering, association…

Prompts are not as private as you think they are.
https://www.quantable.com/ai/the-old-rules-are-dead/

そういえばTootleについて、危険であるという指摘もありましたね。
謎にクリップボードアクセスしていること、Google Analytics for Firebaseで行動追跡情報を収集していること、それらのプライバシーポリシー（収集範囲や用途制限の宣言）が公開されていないこと、かな。通知をリレーするサーバが情報収集しやすいという話もあります。
こちらに収集している情報のjsonとか書いておきました。
https://

Years ago, I saw someone say "My love language is removing tracking links from URLs that I share" and it has lived in my brain rent-free ever since.
Today I realized that if a site I like and want to promote isn't yet on the fediverse, changing utm_medium from (say) email to mastodon might show them a weird result in their google analytics (or whatever) dashboard.
I know, I know, Mastodon is not the fediverse. But it has enough mindshare tha…

Poseidon: A OneGraph Engine
Brad Bebee, \"Umit V. \c{C}ataly\"urek, Olaf Hartig, Ankesh Khandelwal, Simone Rondelli, Michael Schmidt, Lefteris Sidirourgos, Bryan Thompson
https://arxiv.org/abs/2510.11166

Poseidon: A OneGraph Engine
We present the Poseidon engine behind the Neptune Analytics graph database service. Customers interact with Poseidon using the declarative openCypher query language, which enables requests that seamlessly combine traditional querying paradigms (such as graph pattern matching, variable length paths, aggregation) with algorithm invocations and has been syntactically extended to facilitate OneGraph interoperability, such as the disambiguation between globally unique IRIs (as exposed via RDF) vs. l…

Here's a quote from HuffPost:
"According to Bluesky analytics site VQV, the official White House account quickly became the platform’s second-most blocked profile, with around 95,000 users smashing the block button to presumably preempt their feeds being filled with AI slop and divisive rants.
"The only account with more blocks on the platform is Vice President JD Vance, who’s been blocked by more than 167,000 users since joining in June."

OpenAI discloses API customer data breach via Mixpanel vendor hack
Mixpanel reported that the attack “impacted a limited number of our customers” and resulted from a smishing (SMS phishing) campaign that the company detected on November 8.
OpenAI received details of the affected dataset on November 25 after being informed of Mixpanel’s ongoing investigation.
The AI company notes that the exposed information may include:

• Name that was provided to …

OpenAI discloses API customer data breach via Mixpanel vendor hack
OpenAI is notifying some ChatGPT API customers that limited identifying information was exposed following a breach at its third-party analytics provider Mixpanel.

Replaced article(s) found for cs.OH. https://arxiv.org/list/cs.OH/new
[1/1]:
- The Junction of Immersive Analytics and Virtual Reconstructions -- A Case Study on the Mausoleum ...
Kerle-Malcharek, Hann-von-Weyhern, Hailer, Diefenbach, Feyer, Klein, Schreiber

All I want is a new Cookie attribute added to the spec, so that when a website tries to set a cookie, along with the name and expiry date and domain and httponly flags, there is a "type".
Valid values for type are "preference", "storage", "login", "session", "analytics", "tracking" and "evil".

Efficient Learning-based Graph Simulation for Temporal Graphs
Sheng Xiang, Chenhao Xu, Dawei Cheng, Xiaoyang Wang, Ying Zhang
https://arxiv.org/abs/2510.05569 https://

Efficient Learning-based Graph Simulation for Temporal Graphs
Graph simulation has recently received a surge of attention in graph processing and analytics. In real-life applications, e.g. social science, biology, and chemistry, many graphs are composed of a series of evolving graphs (i.e., temporal graphs). While most of the existing graph generators focus on static graphs, the temporal information of the graphs is ignored. In this paper, we focus on simulating temporal graphs, which aim to reproduce the structural and temporal properties of the observed…

War of attrition: Russian troops advance, but with heavy losses | Wrap-Up Analytics: https://benborges.xyz/2025/12/07/war-of-attrition-russian-troops.html

Rivaling Transformers: Multi-Scale Structured State-Space Mixtures for Agentic 6G O-RAN
Farhad Rezazadeh, Hatim Chergui, Merouane Debbah, Houbing Song, Dusit Niyato, Lingjia Liu
https://arxiv.org/abs/2510.05255

Rivaling Transformers: Multi-Scale Structured State-Space Mixtures for Agentic 6G O-RAN
In sixth-generation (6G) Open Radio Access Networks (O-RAN), proactive control is preferable. A key open challenge is delivering control-grade predictions within Near-Real-Time (Near-RT) latency and computational constraints under multi-timescale dynamics. We therefore cast RAN Intelligent Controller (RIC) analytics as an agentic perceive-predict xApp that turns noisy, multivariate RAN telemetry into short-horizon per-User Equipment (UE) key performance indicator (KPI) forecasts to drive antici…

Software Engineering Data Analytics: A Framework Based on a Multi-Layered Abstraction Mechanism
Chaman Wijesiriwardana, Prasad Wimalaratne
https://arxiv.org/abs/2509.21881 https…

Software Engineering Data Analytics: A Framework Based on a Multi-Layered Abstraction Mechanism
This paper presents a concept of a domain-specific framework for software analytics by enabling querying, modeling, and integration of heterogeneous software repositories. The framework adheres to a multi-layered abstraction mechanism that consists of domain-specific operators. We showcased the potential of this approach by employing a case study.

Bogus #BGP routes that were little noticed. The origin ASN appears to have been a typo for #AS327885 (Viettel Tanzania), perhaps in a failed attempt at a government directed shutdown?

📊 Comprehensive notification analytics with delivery tracking, open rates, click-through analytics, and user engagement metrics for data-driven improvements
🛡️ Security best practices for notification systems including rate limiting, content sanitization, encrypted payloads, and user permission management
🌐 https://

Multi-Value-Product Retrieval-Augmented Generation for Industrial Product Attribute Value Identification
Huike Zou, Haiyang Yang, Yindu Su, Liyu Chen, Chengbao Lian, Qingheng Zhang, Shuguang Han, Jufeng Chen
https://arxiv.org/abs/2509.23874

Multi-Value-Product Retrieval-Augmented Generation for Industrial Product Attribute Value Identification
Identifying attribute values from product profiles is a key task for improving product search, recommendation, and business analytics on e-commerce platforms, which we called Product Attribute Value Identification (PAVI) . However, existing PAVI methods face critical challenges, such as cascading errors, inability to handle out-of-distribution (OOD) attribute values, and lack of generalization capability. To address these limitations, we introduce Multi-Value-Product Retrieval-Augmented Generat…

EPIC: Generative AI Platform for Accelerating HPC Operational Data Analytics
Ahmad Maroof Karimi, Woong Shin, Jesse Hines, Tirthankar Ghosal, Naw Safrin Sattar, Feiyi Wang
https://arxiv.org/abs/2509.16212

EPIC: Generative AI Platform for Accelerating HPC Operational Data Analytics
We present EPIC, an AI-driven platform designed to augment operational data analytics. EPIC employs a hierarchical multi-agent architecture where a top-level large language model provides query processing, reasoning and synthesis capabilities. These capabilities orchestrate three specialized low-level agents for information retrieval, descriptive analytics, and predictive analytics. This architecture enables EPIC to perform HPC operational analytics on multi-modal data, including text, images, …

Tracing pT-differential radial flow from blast-wave analytics to quark coalescence
Jie Wan, Chun-Zheng Wang, Yu-Gang Ma, Qi-Ye Shou
https://arxiv.org/abs/2509.24889 https://

Tracing pT-differential radial flow from blast-wave analytics to quark coalescence
The observable $v_0(\pt)$, which quantifies event-by-event fluctuations in the differential transverse-momentum spectrum, is proposed as a direct and penetrating probe of radial flow in heavy-ion collisions. Recent measurements at the LHC exhibit a clear mass ordering for pions, kaons and protons at low \pt and a baryon-meson splitting at intermediate \pt, resembling to the well-known features of elliptic flow ($v_2$). In this letter, we first derive an analytic expression of $v_0(\pt)$ within …

At Berlin Buzzwords 2025, Dotan Horovits discussed how OpenSearch is improving search and observability at scale! Now part of The Linux Foundation, OpenSearch continues to evolve with vector search, NLP and real-time analytics. Learn about its latest innovations, performance boosts, and growing ecosystem.
Watch the full session: https://youtu.be/bCTYB8Ufq0o?si=5bKtBhl-MIVUKH3E
Berlin Buzzwords returns on 7-9 June 2026! Get 36% off with our Trust Us Ticket: https://tickets.plainschwarz.com/bbuzz26/c/8Hvk0ZvJA/

End-to-End Co-Simulation Testbed for Cybersecurity Research and Development in Intelligent Transportation Systems
Minhaj Uddin Ahmad, Akid Abrar, Sagar Dasgupta, Mizanur Rahman
https://arxiv.org/abs/2509.16489

End-to-End Co-Simulation Testbed for Cybersecurity Research and Development in Intelligent Transportation Systems
Intelligent Transportation Systems (ITS) have been widely deployed across major metropolitan regions worldwide to improve roadway safety, optimize traffic flow, and reduce environmental impacts. These systems integrate advanced sensors, communication networks, and data analytics to enable real-time traffic monitoring, adaptive signal control, and predictive maintenance. However, such integration significantly broadens the ITS attack surface, exposing critical infrastructures to cyber threats th…

Kantar Media appoints former WPP boss Mark Read as its chairman, after HIG Capital acquired the analytics company from Kantar Group in a $1.1B deal in August (Daniel Thomas/Financial Times)
https://www.ft.com/content/dd68b487-a24e-4dc7-b8e3-de7056f6a118

Former WPP boss Mark Read set to become Kantar Media chair
Appointment to media analytics group follows its acquisition this year by HIG Capital

Human Activity Recognition Based on Electrocardiogram Data Only
Sina Montazeri, Waltenegus Dargie, Yunhe Feng, Kewei Sha
https://arxiv.org/abs/2509.19328 https://

Human Activity Recognition Based on Electrocardiogram Data Only
Human activity recognition is critical for applications such as early intervention and health analytics. Traditional activity recognition relies on inertial measurement units (IMUs), which are resource intensive and require calibration. Although electrocardiogram (ECG)-based methods have been explored, these have typically served as supplements to IMUs or have been limited to broad categorical classification such as fall detection or active vs. inactive in daily activities. In this paper, we ad…

Sources: data integration company Fivetran is in talks to acquire data management company dbt Labs in a deal valuing the combined entity at between $5B and $10B (The Information)
https://www.theinformation.com/articles/data-startup-fi…

Data Startup Fivetran In Talks to Buy Dbt Labs in Multibillion Dollar Deal
Fivetran, a startup used by companies to manage and prepare data for analytics and artificial intelligence, is in talks to buy data management companydbt Labs, according to people with direct knowledge of the deal. The deal would combine two data companies that are facing competition from ...

Ranking the top 10 shutdown cornerbacks of the 2025 NFL season so far https://www.nfl.com/news/ranking-the-top-10-shutdown-cornerbacks-of-the-2025-nfl-season-so-far

Scaling Generalist Data-Analytic Agents
Shuofei Qiao, Yanqiu Zhao, Zhisong Qiu, Xiaobin Wang, Jintian Zhang, Zhao Bin, Ningyu Zhang, Yong Jiang, Pengjun Xie, Fei Huang, Huajun Chen
https://arxiv.org/abs/2509.25084

Scaling Generalist Data-Analytic Agents
Data-analytic agents are emerging as a key catalyst for automated scientific discovery and for the vision of Innovating AI. Current approaches, however, rely heavily on prompt engineering over proprietary models, while open-source models struggle to face diverse-format, large-scale data files and long-horizon, multi-step reasoning that real-world analytics demands. This paper introduces DataMind, a scalable data synthesis and agent training recipe designed to build generalist data-analytic agen…

CoChen (#AS49608), recently went offline. Their website suggests they provide circuits to businesses and consumers in select markets in HK, JP, KR and US.
Seems unlikely. They were single homed behind Kaopu Cloud. They were announcing a handful of leased IP4 blocks. Previous BGP upstreams were Latitude.sh (BR hosting provider), Pyschz (US hosting provider), and others.

SPH-Net: A Co-Attention Hybrid Model for Accurate Stock Price Prediction
Yiyang Wu, Hanyu Ma, Muxin Ge, Xiaoli Ma, Yadi Liu, Ye Aung Moe, Zeyu Han, Weizheng Xie
https://arxiv.org/abs/2509.15414

SPH-Net: A Co-Attention Hybrid Model for Accurate Stock Price Prediction
Prediction of stock price movements presents a formidable challenge in financial analytics due to the inherent volatility, non-stationarity, and nonlinear characteristics of market data. This paper introduces SPH-Net (Stock Price Prediction Hybrid Neural Network), an innovative deep learning framework designed to enhance the accuracy of time series forecasting in financial markets. The proposed architecture employs a novel co-attention mechanism that initially processes temporal patterns throug…

Interplay between Security, Privacy and Trust in 6G-enabled Intelligent Transportation Systems
Ahmed Danladi Abdullahi, Erfan Bahrami, Tooska Dargahi, Mohammed Al-Khalidi, Mohammad Hammoudeh
https://arxiv.org/abs/2510.02487

Interplay between Security, Privacy and Trust in 6G-enabled Intelligent Transportation Systems
The advancement of 6G technology has the potential to revolutionize the transportation sector and significantly improve how we travel. 6G-enabled Intelligent Transportation Systems (ITS) promise to offer high-speed, low-latency communication and advanced data analytics capabilities, supporting the development of safer, more efficient, and more sustainable transportation solutions. However, various security and privacy challenges were identified in the literature that must be addressed to enable…

A LoRa IoT Framework with Machine Learning for Remote Livestock Monitoring in Smart Agriculture
Hitesh Mohapatra
https://arxiv.org/abs/2510.07322 https://a…

A LoRa IoT Framework with Machine Learning for Remote Livestock Monitoring in Smart Agriculture
This work presents AgroTrack, a LoRa-based IoT framework for remote livestock monitoring in smart agriculture. The system is designed for low-power, long-range communication and supports real-time tracking and basic health assessment of free-range livestock through GPS, motion, and temperature sensors integrated into wearable collars. Data is collected and transmitted via LoRa to gateways and forwarded to a cloud platform for visualization, alerts, and analytics. To enhance its practical deploy…

Integrating AI and Ensemble Forecasting: Explainable Materials Planning with Scorecards and Trend Insights for a Large-Scale Manufacturer
Saravanan Venkatachalam
https://arxiv.org/abs/2510.01006

Integrating AI and Ensemble Forecasting: Explainable Materials Planning with Scorecards and Trend Insights for a Large-Scale Manufacturer
This paper presents a practical architecture for after-sales demand forecasting and monitoring that unifies a revenue- and cluster-aware ensemble of statistical, machine-learning, and deep-learning models with a role-driven analytics layer for scorecards and trend diagnostics. The framework ingests exogenous signals (installed base, pricing, macro indicators, life cycle, seasonality) and treats COVID-19 as a distinct regime, producing country-part forecasts with calibrated intervals. A Pareto-a…

“Freedom always comes at a cost — I’ve seen that cost up close” – Matthew Sampson | WrapUp Analytics: https://benborges.xyz/2025/10/26/freedom-always-comes-at-a.html

Numeric, which automates accounting workflows, raised a $51M Series B led by IVP, bringing its total funding to $89M, and says OpenAI and Brex are clients (Ryan Lawler/Axios)
https://www.axios.com/pro/fintech-deals/2025/11/19/numeric-51-million-acc…

Exclusive: Numeric raises $51M to automate accounting
Company connects close, cash and analytics in one data layer.

Prefetching in Deep Memory Hierarchies with NVRAM as Main Memory
Manel Lurbe, Miguel Avargues, Salvador Petit, Maria E. Gomez, Rui Yang, Guanhao Wang, Julio Sahuquillo
https://arxiv.org/abs/2509.17388 …

Prefetching in Deep Memory Hierarchies with NVRAM as Main Memory
Emerging applications, such as big data analytics and machine learning, require increasingly large amounts of main memory, often exceeding the capacity of current commodity processors built on DRAM technology. To address this, recent research has focused on off-chip memory controllers that facilitate access to diverse memory media, each with unique density and latency characteristics. While these solutions improve memory system performance, they also exacerbate the already significant memory la…

Piquant$\varepsilon$: Private Quantile Estimation in the Two-Server Model
Hannah Keller, Jacob Imola, Fabrizio Boninsegna, Rasmus Pagh, Amrita Roy Chowdhury
https://arxiv.org/abs/2509.14035

Piquant$\varepsilon$: Private Quantile Estimation in the Two-Server Model
Quantiles are key in distributed analytics, but computing them over sensitive data risks privacy. Local differential privacy (LDP) offers strong protection but lower accuracy than central DP, which assumes a trusted aggregator. Secure multi-party computation (MPC) can bridge this gap, but generic MPC solutions face scalability challenges due to large domains, complex secure operations, and multi-round interactions. We present Piquant$\varepsilon$, a system for privacy-preserving estimation of…

Integrating AI and Ensemble Forecasting: Explainable Materials Planning with Scorecards and Trend Insights for a Large-Scale Manufacturer
Saravanan Venkatachalam
https://arxiv.org/abs/2510.01006

Integrating AI and Ensemble Forecasting: Explainable Materials Planning with Scorecards and Trend Insights for a Large-Scale Manufacturer
This paper presents a practical architecture for after-sales demand forecasting and monitoring that unifies a revenue- and cluster-aware ensemble of statistical, machine-learning, and deep-learning models with a role-driven analytics layer for scorecards and trend diagnostics. The framework ingests exogenous signals (installed base, pricing, macro indicators, life cycle, seasonality) and treats COVID-19 as a distinct regime, producing country-part forecasts with calibrated intervals. A Pareto-a…

Muse-it: A Tool for Analyzing Music Discourse on Reddit
Jatin Agarwala, George Paul, Nemani Harsha Vardhan, Vinoo Alluri
https://arxiv.org/abs/2509.20228 https://

Muse-it: A Tool for Analyzing Music Discourse on Reddit
Music engagement spans diverse interactions with music, from selection and emotional response to its impact on behavior, identity, and social connections. Social media platforms provide spaces where such engagement can be observed in natural, unprompted conversations. Advances in natural language processing (NLP) and big data analytics make it possible to analyze these discussions at scale, extending music research to broader contexts. Reddit, in particular, offers anonymity that encourages div…

Crypto media company Blockworks is closing its newsroom, launched in 2021, and will focus on software and data, continuing its main newsletters and podcasts (Pooja Rajkumari/TheStreet)
https://www.thestreet.com/crypto/jobs/blockworks-s…

Da sind erstmal Firmen. Die haben hier ein super schweres Standing.
Unis und öffentliche Einrichtungen geht gerade noch, aber "Reichweite" und "Zugewinn" können Sie nicht erwarten. Das ist hier wie eine Homepage ohne Analytics ins Netz zu stellen.
Don't get me wrong: Die Stadtbibliothek (z.B.) sollte das tun!
Und dann gibts noch Menschen die eigentlich Werbung sind. Man erkennt sie z.B. daran, dass sie auf allen Netzwerken das Gleiche posten, und das eigentlich für Insta optimiert ist?

VisMoDAl: Visual Analytics for Evaluating and Improving Corruption Robustness of Vision-Language Models
Huanchen Wang, Wencheng Zhang, Zhiqiang Wang, Zhicong Lu, Yuxin Ma
https://arxiv.org/abs/2509.14571

VisMoDAl: Visual Analytics for Evaluating and Improving Corruption Robustness of Vision-Language Models
Vision-language (VL) models have shown transformative potential across various critical domains due to their capability to comprehend multi-modal information. However, their performance frequently degrades under distribution shifts, making it crucial to assess and improve robustness against real-world data corruption encountered in practical applications. While advancements in VL benchmark datasets and data augmentation (DA) have contributed to robustness evaluation and improvement, there remai…

Analyzing the Raiders' blocking and win rates entering Week 3 https://raiderswire.usatoday.com/story/sports/nfl/raiders/2025/09/18/analyzing-the-raiders-blocking-and-win-rates-entering-week-3/8621489…

Crosslisted article(s) found for cs.CL. https://arxiv.org/list/cs.CL/new
[1/1]:
- Learning Analytics from Spoken Discussion Dialogs in Flipped Classroom
Su, Dzodzo, Li, Zhao, Geng, Li, Jaggi, Meng

Deleuze's "Postscript on the Societies of Control" Updated for Big Data and Predictive Analytics
James Brusseau (Philosophy,Computer Science, Pace University NYC,University of Trento, Italy)
https://arxiv.org/abs/2509.18194

AI-driven formative assessment and adaptive learning in data-science education: Evaluating an LLM-powered virtual teaching assistant
Fadjimata I Anaroua, Qing Li, Yan Tang, Hong P. Liu
https://arxiv.org/abs/2509.20369

AI-driven formative assessment and adaptive learning in data-science education: Evaluating an LLM-powered virtual teaching assistant
This paper presents VITA (Virtual Teaching Assistants), an adaptive distributed learning (ADL) platform that embeds a large language model (LLM)-powered chatbot (BotCaptain) to provide dialogic support, interoperable analytics, and integrity-aware assessment for workforce preparation in data science. The platform couples context-aware conversational tutoring with formative-assessment patterns designed to promote reflective reasoning. The paper describes an end-to-end data pipeline that transfor…

WiFiSim: Simulating WiFi Probe Requests via AOSP Analysis and Device Behavior Modeling
Lifei Hao, Yue Cheng, Min Wang, Bing Jia, Baoqi Huang
https://arxiv.org/abs/2509.15501 htt…

WiFiSim: Simulating WiFi Probe Requests via AOSP Analysis and Device Behavior Modeling
WiFi probe request (PR) frames encode fine-grained device interactions and serve as a critical basis for mobility and crowd analytics. However, pervasive MAC address randomization and the scarcity of labeled datasets hinder progress in PR-based studies. We introduce WiFiSim, a simulation framework that reconstructs PR generation through Android Open Source Project (AOSP) protocol analysis and finite-state device behavior modeling. WiFiSim identifies the key determinants of PR structure and timi…

OpenLens AI: Fully Autonomous Research Agent for Health Infomatics
Yuxiao Cheng, Jinli Suo
https://arxiv.org/abs/2509.14778 https://arxiv.org/pdf/2509.1477…

OpenLens AI: Fully Autonomous Research Agent for Health Infomatics
Health informatics research is characterized by diverse data modalities, rapid knowledge expansion, and the need to integrate insights across biomedical science, data analytics, and clinical practice. These characteristics make it particularly well-suited for agent-based approaches that can automate knowledge exploration, manage complex workflows, and generate clinically meaningful outputs. Recent progress in large language model (LLM)-based agents has demonstrated promising capabilities in lit…

A Scoping Review of Mixed Initiative Visual Analytics in the Automation Renaissance
Shayan Monadjemi, Yuhan Guo, Kai Xu, Alex Endert, Anamaria Crisan
https://arxiv.org/abs/2509.19152

ExtGraph: A Fast Extraction Method of User-intended Graphs from a Relational Database
Jeongho Park, Geonho Lee, Min-Soo Kim
https://arxiv.org/abs/2509.18534 https://

Comparative Analysis of STEM and non-STEM Teachers' Needs for Integrating AI into Educational Environments
Bahare Riahi, Veronica Catete
https://arxiv.org/abs/2509.16276 htt…

Comparative Analysis of STEM and non-STEM Teachers' Needs for Integrating AI into Educational Environments
There is an increasing imperative to integrate programming platforms within AI frameworks to enhance educational tasks for both teachers and students. However, commonly used platforms such as Code.org, Scratch, and Snap fall short of providing the desired AI features and lack adaptability for interdisciplinary applications. This study explores how educational platforms can be improved by incorporating AI and analytics features to create more effective learning environments across various subjec…

Sentinel Agents for Secure and Trustworthy Agentic AI in Multi-Agent Systems
Diego Gosmar, Deborah A. Dahl
https://arxiv.org/abs/2509.14956 https://arxiv.o…

Sentinel Agents for Secure and Trustworthy Agentic AI in Multi-Agent Systems
This paper proposes a novel architectural framework aimed at enhancing security and reliability in multi-agent systems (MAS). A central component of this framework is a network of Sentinel Agents, functioning as a distributed security layer that integrates techniques such as semantic analysis via large language models (LLMs), behavioral analytics, retrieval-augmented verification, and cross-agent anomaly detection. Such agents can potentially oversee inter-agent communications, identify potenti…

Balancing Innovation and Oversight: AI in the U.S. Treasury and IRS: A Survey
Sohail Shaikh
https://arxiv.org/abs/2509.16294 https://arxiv.org/pdf/2509.162…

Balancing Innovation and Oversight: AI in the U.S. Treasury and IRS: A Survey
This paper explores how the U.S. Department of Treasury, particularly the Internal Revenue Service (IRS), is adopting artificial intelligence (AI) to modernize tax administration. Using publicly available information, the survey highlights the applications of AI for taxpayer support, operational efficiency, fraud detection, and audit optimization. Key initiatives include AI-powered chatbots, robotic process automation, machine learning for case selection, and advanced analytics for fraud preven…

STARQA: A Question Answering Dataset for Complex Analytical Reasoning over Structured Databases
Mounica Maddela, Lingjue Xie, Daniel Preotiuc-Pietro, Mausam
https://arxiv.org/abs/2509.19508

STARQA: A Question Answering Dataset for Complex Analytical Reasoning over Structured Databases
Semantic parsing methods for converting text to SQL queries enable question answering over structured data and can greatly benefit analysts who routinely perform complex analytics on vast data stored in specialized relational databases. Although several benchmarks measure the abilities of text to SQL, the complexity of their questions is inherently limited by the level of expressiveness in query languages and none focus explicitly on questions involving complex analytical reasoning which requir…

Process-Driven Visual Analysis of Cybersecurity Capture the Flag Exercises
Radek O\v{s}lej\v{s}ek, Radoslav Chudovsk\'y, Martin Macak
https://arxiv.org/abs/2509.15589 https:…

Process-Driven Visual Analysis of Cybersecurity Capture the Flag Exercises
Hands-on training sessions become a standard way to develop and increase knowledge in cybersecurity. As practical cybersecurity exercises are strongly process-oriented with knowledge-intensive processes, process mining techniques and models can help enhance learning analytics tools. The design of our open-source analytical dashboard is backed by guidelines for visualizing multivariate networks complemented with temporal views and clustering. The design aligns with the requirements for post-trai…

ARCADE: A Real-Time Data System for Hybrid and Continuous Query Processing across Diverse Data Modalities
Jingyi Yang, Songsong Mo, Jiachen Shi, Zihao Yu, Kunhao Shi, Xuchen Ding, Gao Cong
https://arxiv.org/abs/2509.19757

ARCADE: A Real-Time Data System for Hybrid and Continuous Query Processing across Diverse Data Modalities
The explosive growth of multimodal data - spanning text, image, video, spatial, and relational modalities, coupled with the need for real-time semantic search and retrieval over these data - has outpaced the capabilities of existing multimodal and real-time database systems, which either lack efficient ingestion and continuous query capability, or fall short in supporting expressive hybrid analytics. We introduce ARCADE, a real-time data system that efficiently supports high-throughput ingestio…