ルールベースによるTwitter タイムライン感情分析
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This document discusses a project to analyze the sentiment levels of timelines posted on Twitter using natural language processing. The project aims to quantify the sentiment levels of posts, create evaluation metrics for casual posts' sentiment levels using NLP, and improve sentiment analysis algorithms and scores. It describes preprocessing tweets obtained from the Twitter API, using morphological analysis, sentiment dictionaries, FastText models trained on Wikipedia, and product review data to score tweets. The results show that current methods do not accurately score slang terms like "uzai", and future work could involve using deep learning to better capture context and extend evaluation.
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Discover the seamless integration of RPA (Robotic Process Automation), COMPOSER, and APM with AWS IDP enhanced with Slack notifications. Explore how these technologies converge to streamline workflows, optimize performance, and ensure secure access, all while leveraging the power of AWS IDP and real-time communication via Slack notifications.
Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
UiPath Test Automation using UiPath Test Suite series, part 6
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.
Throughout the session, participants will discover how this synergy empowers testers to automate repetitive tasks, enhance testing accuracy, and expedite the software testing life cycle. Topics covered include the seamless integration process, practical use cases, and the benefits of harnessing AI-driven automation for UiPath testing initiatives. By attending this webinar, testers, and automation professionals can gain valuable insights into harnessing the power of AI to optimize their test automation workflows within the UiPath ecosystem, ultimately driving efficiency and quality in software development processes.
What will you get from this session?
1. Insights into integrating generative AI.
2. Understanding how this integration enhances test automation within the UiPath platform
3. Practical demonstrations
4. Exploration of real-world use cases illustrating the benefits of AI-driven test automation for UiPath
Topics covered:
What is generative AI
Test Automation with generative AI and Open AI.
UiPath integration with generative AI
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
TrustArc Webinar - 2024 Global Privacy Survey
How does your privacy program stack up against your peers? What challenges are privacy teams tackling and prioritizing in 2024?
In the fifth annual Global Privacy Benchmarks Survey, we asked over 1,800 global privacy professionals and business executives to share their perspectives on the current state of privacy inside and outside of their organizations. This year’s report focused on emerging areas of importance for privacy and compliance professionals, including considerations and implications of Artificial Intelligence (AI) technologies, building brand trust, and different approaches for achieving higher privacy competence scores.
See how organizational priorities and strategic approaches to data security and privacy are evolving around the globe.
This webinar will review:
- The top 10 privacy insights from the fifth annual Global Privacy Benchmarks Survey
- The top challenges for privacy leaders, practitioners, and organizations in 2024
- Key themes to consider in developing and maintaining your privacy program
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.
Building RAG with self-deployed Milvus vector database and Snowpark Container...
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Communications Mining Series - Zero to Hero - Session 1
This session provides introduction to UiPath Communication Mining, importance and platform overview. You will acquire a good understand of the phases in Communication Mining as we go over the platform with you. Topics covered:
• Communication Mining Overview
• Why is it important?
• How can it help today’s business and the benefits
• Phases in Communication Mining
• Demo on Platform overview
• Q/A
Presentation of the OECD Artificial Intelligence Review of Germany
Consult the full report at https://www.oecd.org/digital/oecd-artificial-intelligence-review-of-germany-609808d6-en.htm
Large Language Model (LLM) and it’s Geospatial Applications
Large Language Model (LLM) and it’s Geospatial Applications.
Pushing the limits of ePRTC: 100ns holdover for 100 days
At WSTS 2024, Alon Stern explored the topic of parametric holdover and explained how recent research findings can be implemented in real-world PNT networks to achieve 100 nanoseconds of accuracy for up to 100 days.
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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...
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Communications Mining Series - Zero to Hero - Session 1
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Presentation of the OECD Artificial Intelligence Review of Germany
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Large Language Model (LLM) and it’s Geospatial Applications
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Pushing the limits of ePRTC: 100ns holdover for 100 days
ルールベースによるTwitter タイムライン感情分析
- 3. Twitter API CSV 前処理 形態素解析 プロジェクトの概要 評価極性辞書 辞書化 FastText レビュー データ 拡張 Google Natural Language ① ② ③ ④ ①〜④スコアを それぞれ比較，効果検証
- 4. Google Natural Language Twitter API 前処理 GCP スコア ・Twitter API でキーワードを検索 → ７日間分のタイムラインを取得 ・csvファイルを取得 ・Google Natural Language API → スコア化 ・絵文字の除去；関数 ・リンクの除去；正規表現 ・TimeStamp変換 ・データの読み込み −1 ≤ 𝑠 ≤ 1 ・投稿をスコア化
- 6. 評価極性辞書 テキスト 評価極性辞書 照合 助詞，連体詞，助動詞 除外 形態素の平均値を算出 ・彼； ・は； ・面白い； ・賢い； NAN NAN 0.989199 0.999486 注）「NAN」は形態素の要素としてカウントしない Ex） 𝑠𝑐𝑜𝑟𝑒 = (0.989199 + 0.999486) 2 = 0.9943425
- 9. レビューサイトによる重要度のスコア化 𝑠 = 𝑛𝑤𝑒𝑖𝑔ℎ𝑡 × log(𝑑𝑓 𝑡 ) 𝑑𝑓 𝑡 ；文章における単語の出現頻度 𝑛𝑤𝑒𝑖𝑔ℎ𝑡；レビューサイトの評価（ −5 ≤ 𝑛𝑤𝑒𝑖𝑔ℎ𝑡 ≤ 5 ） スコアの極性 ・文章中の単語の頻度→単語の極性=スコアの指標 ・レビューの星の数(評価)→ネガティブ(負)かポジティブ(正)の分類
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- 13. プロジェクトの評価 ・FastText ・レビューデータ score = -0.521852で平均値化 学習用に利用したWikipediaの記事には 「うざい」という項目がない