Rakuten Institute of Technology
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This document discusses improving a product catalog through classification and attribute extraction from product information using machine learning techniques. Key tasks involve product genre classification, attribute extraction, and merchant/item review analysis. Technologies used include gradient boosted decision trees, deep learning models like RNNs and CNNs, and computing massive numbers of NLP features. The goal is to automatically predict categories and attributes from text/images to organize the catalog according to customer expectations and precisely search/measure merchant performance.
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What gaming industry can learn from the more mature industries in optimizing ...
What gaming industry can learn from the more mature industries in optimizing ...
Conquer the Interwebs: The Three Pillars of Web Analytics
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Make your Data feeds the rock star of your PPC campigns
Make your Data feeds the rock star of your PPC campigns
How to Transform CPG Performance with Category Focused Digital Shelf Analytics
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コードレビュー改善のためにJenkinsとIntelliJ IDEAのプラグインを自作してみた話
CI/CDツールであるJenkinsとIDEであるIntelliJ IDEA。両者の共通点は、Javaで書かれている点と、プラグインによって機能を拡張できる点です。つまり、Javaを用いてプラグインを実装することで、自分が欲しい機能を追加することができます。本セッションでは、コードレビュープロセスを改善するためにJenkinsとIntelliJ IDEAのプラグインを自作した経験を踏まえて、実装方法に触れつつ、得られた結果や苦労した点について話します。
What Makes Software Green?
This document discusses how to make software more green and environmentally friendly. It defines green software as software that is carbon efficient, energy efficient, hardware efficient, and carbon aware. It provides recommendations for various roles within an organization on driving green initiatives, including focusing on efficiency for CxOs, architects, infrastructure engineers, and developers. Examples include optimizing resource usage, using public clouds effectively, prioritizing equipment standardization, and developing applications that can run more efficiently.
Simple and Effective Knowledge-Driven Query Expansion for QA-Based Product At...
The document proposes a knowledge-driven query expansion approach for question answering (QA)-based product attribute extraction. It trains QA models using attribute-value pairs from training data as knowledge, while mimicking imperfect knowledge at test time through techniques like knowledge dropout and token mixing. This helps induce better query representations, especially for rare and ambiguous attributes. Experiments on a cleaned product attribute dataset show the proposed approach with all techniques outperforms baseline methods in both macro and micro F1 scores.
DataSkillCultureを浸透させる楽天の取り組み
Rakuten Developer Meetup vol.03
大規模クラウドの仕組みと秘密
https://rakuten.connpass.com/event/254762/
大規模なリアルタイム監視の導入と展開
Rakuten Developer Meetup vol.03
大規模クラウドの仕組みと秘密
https://rakuten.connpass.com/event/254762/
楽天における大規模データベースの運用
Rakuten Developer Meetup vol.03
大規模クラウドの仕組みと秘密
https://rakuten.connpass.com/event/254762/
楽天サービスを支えるネットワークインフラストラクチャー
Rakuten Developer Meetup vol.03
大規模クラウドの仕組みと秘密
https://rakuten.connpass.com/event/254762/
楽天の規模とクラウドプラットフォーム統括部の役割
Rakuten Developer Meetup vol.03
大規模クラウドの仕組みと秘密
https://rakuten.connpass.com/event/254762/
Rakuten Services and Infrastructure Team.pdf
Rakuten Developer Meetup vol.02: How to Manage Large-scale Infrastructure
https://rakuten.connpass.com/event/243219/
The Data Platform Administration Handling the 100 PB.pdf
Rakuten Developer Meetup vol.02: How to Manage Large-scale Infrastructure
https://rakuten.connpass.com/event/243219/
Supporting Internal Customers as Technical Account Managers.pdf
Rakuten Developer Meetup vol.02: How to Manage Large-scale Infrastructure
https://rakuten.connpass.com/event/243219/
Making Cloud Native CI_CD Services.pdf
Rakuten Developer Meetup vol.02: How to Manage Large-scale Infrastructure
https://rakuten.connpass.com/event/243219/
How We Defined Our Own Cloud.pdf
This document summarizes Andrew Hajinikitas' work developing Rakuten's private cloud infrastructure. It describes the key components of Rakuten's infrastructure including metal instances, microservers, and GPU servers. It provides details on Rakuten's software stack and their goals to expand managed services. Currently, Rakuten operates 9 data centers in Japan and overseas providing around 30,000 servers to support their ecosystem. Their future plans include extending network self-service, making GPU resources available as a platform service, and improving efficiency through optimized hardware selection.
Travel & Leisure Platform Department's tech info
The document discusses the Travel & Leisure Platform Dept and its responsibilities related to data and platform management. It provides an overview of the technical stack including private/public clouds, databases, containers, and automation/monitoring tools. It then discusses recent projects involving business continuity, containerization, alert integration, and automation. Finally, it describes open roles for a DBA and DevOps position and their responsibilities related to database provisioning, backup/recovery, infrastructure as code, and providing platforms and tools for developers.
OWASPTop10_Introduction
This presentation introduces the OWASP Top 10:2021.
It explains how to look at the data related to OWASP Top 10:2021, and provides detailed explanations of items with distinctive data. It also introduces the OWASP Project related to each item.
Introduction of GORA API Group technology
Gora API Group technology provides a microservices architecture and APIs for Rakuten's golf course reservation system, improving the user experience and increasing customer loyalty and annual golf rounds. The architecture migrates the monolithic reservation system to microservices using Kotlin, Spring Boot, and other technologies, exposing APIs for the frontend and new products while sustaining the legacy system through services, queues, continuous delivery, and operations monitoring.
100PBを越えるデータプラットフォームの実情
Rakuten Developer Meetup vol.01: 楽天エコシステムを支えるインフラエンジニア
https://rakuten.connpass.com/event/232707/
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Rakuten Developer Meetup vol.01: 楽天エコシステムを支えるインフラエンジニア
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Simple and Effective Knowledge-Driven Query Expansion for QA-Based Product At...
Simple and Effective Knowledge-Driven Query Expansion for QA-Based Product At...
The Data Platform Administration Handling the 100 PB.pdf
The Data Platform Administration Handling the 100 PB.pdf
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みなさんこんにちはこれ何文字まで入るの？40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの？えこ...
ここ3000字までしか入らないけどタイトルの方がたくさん文字入ると思います。
Infrastructure Challenges in Scaling RAG with Custom AI models
Building Retrieval-Augmented Generation (RAG) systems with open-source and custom AI models is a complex task. This talk explores the challenges in productionizing RAG systems, including retrieval performance, response synthesis, and evaluation. We’ll discuss how to leverage open-source models like text embeddings, language models, and custom fine-tuned models to enhance RAG performance. Additionally, we’ll cover how BentoML can help orchestrate and scale these AI components efficiently, ensuring seamless deployment and management of RAG systems in the cloud.
Monitoring and Managing Anomaly Detection on OpenShift.pdf
Monitoring and Managing Anomaly Detection on OpenShift
Overview
Dive into the world of anomaly detection on edge devices with our comprehensive hands-on tutorial. This SlideShare presentation will guide you through the entire process, from data collection and model training to edge deployment and real-time monitoring. Perfect for those looking to implement robust anomaly detection systems on resource-constrained IoT/edge devices.
Key Topics Covered
1. Introduction to Anomaly Detection
- Understand the fundamentals of anomaly detection and its importance in identifying unusual behavior or failures in systems.
2. Understanding Edge (IoT)
- Learn about edge computing and IoT, and how they enable real-time data processing and decision-making at the source.
3. What is ArgoCD?
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4. Deployment Using ArgoCD for Edge Devices
- Step-by-step guide on deploying anomaly detection models on edge devices using ArgoCD.
5. Introduction to Apache Kafka and S3
- Explore Apache Kafka for real-time data streaming and Amazon S3 for scalable storage solutions.
6. Viewing Kafka Messages in the Data Lake
- Learn how to view and analyze Kafka messages stored in a data lake for better insights.
7. What is Prometheus?
- Get to know Prometheus, an open-source monitoring and alerting toolkit, and its application in monitoring edge devices.
8. Monitoring Application Metrics with Prometheus
- Detailed instructions on setting up Prometheus to monitor the performance and health of your anomaly detection system.
9. What is Camel K?
- Introduction to Camel K, a lightweight integration framework built on Apache Camel, designed for Kubernetes.
10. Configuring Camel K Integrations for Data Pipelines
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11. What is a Jupyter Notebook?
- Overview of Jupyter Notebooks, an open-source web application for creating and sharing documents with live code, equations, visualizations, and narrative text.
12. Jupyter Notebooks with Code Examples
- Hands-on examples and code snippets in Jupyter Notebooks to help you implement and test anomaly detection models.
“I’m still / I’m still / Chaining from the Block”
“An Outlook of the Ongoing and Future Relationship between Blockchain Technologies and Process-aware Information Systems.” Invited talk at the joint workshop on Blockchain for Information Systems (BC4IS) and Blockchain for Trusted Data Sharing (B4TDS), co-located with with the 36th International Conference on Advanced Information Systems Engineering (CAiSE), 3 June 2024, Limassol, Cyprus.
National Security Agency - NSA mobile device best practices
Threats to mobile devices are more prevalent and increasing in scope and complexity. Users of mobile devices desire to take full advantage of the features
available on those devices, but many of the features provide convenience and capability but sacrifice security. This best practices guide outlines steps the users can take to better protect personal devices and information.
Columbus Data & Analytics Wednesdays - June 2024
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Ocean Lotus cyber threat actors represent a sophisticated, persistent, and politically motivated group that poses a significant risk to organizations and individuals in the Southeast Asian region. Their continuous evolution and adaptability underscore the need for robust cybersecurity measures and international cooperation to identify and mitigate the threats posed by such advanced persistent threat groups.
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During the hour, we’ll take you through:
Guest Speaker Segment with Hannah Barrington: Dive into the world of dynamic real estate marketing with Hannah, the Marketing Manager at Workspace Group. Hear firsthand how their team generates engaging descriptions for thousands of office units by integrating diverse data sources—from PDF floorplans to web pages—using FME transformers, like OpenAIVisionConnector and AnthropicVisionConnector. This use case will show you how GenAI can streamline content creation for marketing across the board.
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We’ll wrap up with a live Q&A session where you can engage with our experts on your specific use cases, and learn more about optimizing your data workflows with AI.
This webinar is ideal for professionals seeking to harness the power of AI within their data management systems while ensuring high levels of customization and security. Whether you're a novice or an expert, gain actionable insights and strategies to elevate your data processes. Join us to see how FME and AI can revolutionize how you work with data!
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Welcome to UiPath Test Automation using UiPath Test Suite series part 6. In this session, we will cover Test Automation with generative AI and Open AI.
UiPath Test Automation with generative AI and Open AI webinar offers an in-depth exploration of leveraging cutting-edge technologies for test automation within the UiPath platform. Attendees will delve into the integration of generative AI, a test automation solution, with Open AI advanced natural language processing capabilities.
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What will you get from this session?
1. Insights into integrating generative AI.
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3. Practical demonstrations
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Topics covered:
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Test Automation with generative AI and Open AI.
UiPath integration with generative AI
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
“Building and Scaling AI Applications with the Nx AI Manager,” a Presentation...
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For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2024/06/building-and-scaling-ai-applications-with-the-nx-ai-manager-a-presentation-from-network-optix/
Robin van Emden, Senior Director of Data Science at Network Optix, presents the “Building and Scaling AI Applications with the Nx AI Manager,” tutorial at the May 2024 Embedded Vision Summit.
In this presentation, van Emden covers the basics of scaling edge AI solutions using the Nx tool kit. He emphasizes the process of developing AI models and deploying them globally. He also showcases the conversion of AI models and the creation of effective edge AI pipelines, with a focus on pre-processing, model conversion, selecting the appropriate inference engine for the target hardware and post-processing.
van Emden shows how Nx can simplify the developer’s life and facilitate a rapid transition from concept to production-ready applications.He provides valuable insights into developing scalable and efficient edge AI solutions, with a strong focus on practical implementation.Essentials of Automations: The Art of Triggers and Actions in FME
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
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Imagine a world where machines not only perform tasks but also learn, adapt, and make decisions. This is the promise of Artificial Intelligence (AI), a technology that's not just enhancing our lives but revolutionizing entire industries.
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAU
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-und-domino-lizenzkostenreduzierung-in-der-welt-von-dlau/
DLAU und die Lizenzen nach dem CCB- und CCX-Modell sind für viele in der HCL-Community seit letztem Jahr ein heißes Thema. Als Notes- oder Domino-Kunde haben Sie vielleicht mit unerwartet hohen Benutzerzahlen und Lizenzgebühren zu kämpfen. Sie fragen sich vielleicht, wie diese neue Art der Lizenzierung funktioniert und welchen Nutzen sie Ihnen bringt. Vor allem wollen Sie sicherlich Ihr Budget einhalten und Kosten sparen, wo immer möglich. Das verstehen wir und wir möchten Ihnen dabei helfen!
Wir erklären Ihnen, wie Sie häufige Konfigurationsprobleme lösen können, die dazu führen können, dass mehr Benutzer gezählt werden als nötig, und wie Sie überflüssige oder ungenutzte Konten identifizieren und entfernen können, um Geld zu sparen. Es gibt auch einige Ansätze, die zu unnötigen Ausgaben führen können, z. B. wenn ein Personendokument anstelle eines Mail-Ins für geteilte Mailboxen verwendet wird. Wir zeigen Ihnen solche Fälle und deren Lösungen. Und natürlich erklären wir Ihnen das neue Lizenzmodell.
Nehmen Sie an diesem Webinar teil, bei dem HCL-Ambassador Marc Thomas und Gastredner Franz Walder Ihnen diese neue Welt näherbringen. Es vermittelt Ihnen die Tools und das Know-how, um den Überblick zu bewahren. Sie werden in der Lage sein, Ihre Kosten durch eine optimierte Domino-Konfiguration zu reduzieren und auch in Zukunft gering zu halten.
Diese Themen werden behandelt
- Reduzierung der Lizenzkosten durch Auffinden und Beheben von Fehlkonfigurationen und überflüssigen Konten
- Wie funktionieren CCB- und CCX-Lizenzen wirklich?
- Verstehen des DLAU-Tools und wie man es am besten nutzt
- Tipps für häufige Problembereiche, wie z. B. Team-Postfächer, Funktions-/Testbenutzer usw.
- Praxisbeispiele und Best Practices zum sofortigen Umsetzen
OpenID AuthZEN Interop Read Out - Authorization
During Identiverse 2024 and EIC 2024, members of the OpenID AuthZEN WG got together and demoed their authorization endpoints conforming to the AuthZEN API
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みなさんこんにちはこれ何文字まで入るの？40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの？えこ...
みなさんこんにちはこれ何文字まで入るの？40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの？えこ...
Infrastructure Challenges in Scaling RAG with Custom AI models
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National Security Agency - NSA mobile device best practices
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Ocean lotus Threat actors project by John Sitima 2024 (1).pptx
Driving Business Innovation: Latest Generative AI Advancements & Success Story
Driving Business Innovation: Latest Generative AI Advancements & Success Story
How to Get CNIC Information System with Paksim Ga.pptx
How to Get CNIC Information System with Paksim Ga.pptx
UiPath Test Automation using UiPath Test Suite series, part 6
UiPath Test Automation using UiPath Test Suite series, part 6
“Building and Scaling AI Applications with the Nx AI Manager,” a Presentation...
“Building and Scaling AI Applications with the Nx AI Manager,” a Presentation...
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Essentials of Automations: The Art of Triggers and Actions in FME
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AI 101: An Introduction to the Basics and Impact of Artificial Intelligence
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAU
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAU
Rakuten Institute of Technology
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- 10. 10 Why are we working on this problem? (Key Benefits) ‣ To organize our catalog in accordance with customer expectations ‣ To precisely search our catalog for products and its variants ‣ To measure and enforce merchant KPI's. What are we doing? (Key Tasks) ‣ Product Genre Classification ‣ Attribute Extraction from Product Information ‣ Merchant and Item Review Analysis How are we doing it? (Key Technologies) ‣ Large-Scale Gradient Boosted Decision Trees ‣ Deep Learning (RNN's, CNN's, others) ‣ Computing Massive Number of NLP Features Product Catalog Businesses
- 11. 11 Each product can be assigned a category and attributes. For instance: +Category Grocery & food Subcategory Wine Each (sub)category has a number of relevant attributes with a list of valid values Challenge: this structured information is not always present or correct Goal: automatically predict category and attributes from text and/or images https://item.rakuten.co.jp/kawahara/345812/
- 12. 12 Classifier based on Deep Learning Algorithm (CNN) Prec@1 92% Prec@10 99% Classifier based on Deep Learning Algorithm (CNN) Prec@1 57% Prec@3 75% Extracting Words * Tested to Ichiba L3 category (1.5K categories) * Tested for PriceMinister Image Data Text Data • Item Title • Item Description Image Data
- 13. 13 我们真的很有诚意了。 你说我一个老总都亲 自跑了好几趟了。 Machine translation is A Rakuten group company which provides a video streaming service. Volunteers are editing subtitles and translated subtitles. https://www.viki.com/?locale=ja
- 14. 14 Hobby and Entertainment > Books and Magazine > Business Electronics > Audio > Earphone / Headphone Electronics > Smartphone > AC Adaptor / Battery
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- 20. 2020 Control!
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