2015/8/25に開催されたLeading the way to W3C TPAC 2015での発表資料です。
7月にGoogleから発表されたbeacon-platform、特にEddystoneについての話、また、それらがこれまで実験的なものとして進められてきたPhysical Webのプロジェクトとどう関係するのかなど、複雑になってきているビーコン関連の業界動向を一度整理してみました。
Koji Ishimoto gives a presentation on front-end engineering. He defines a front-end engineer's responsibilities as including JavaScript, version control with Git, modular code, browser developer tools, command line, templating, CSS preprocessors, testing, automation, code quality and manuals. He discusses common front-end tools, managing tools with Grunt, and tracking speed with tools like WebPageTest to monitor performance. The talk aims to provide an overview of the front-end landscape and importance of performance.
The document outlines the divisions and focus areas of a large company, with most resources allocated to technology R&D, including deep learning and CNN. Other divisions include infrastructure, promotions, UI design, SEO, big data, IT, recruiting, staffing services, and administration.
HTML5 Conference 2012 の講演資料
WebIntentsとRaw Socket APIのコンビネーションにより、WebからTVが直接操作できること。そして、シームレスなデバイス連携に関わる最新標準化動向
I strongly believe that People become to access cloud service and local devices in seamless way.
Company Recommendation for New Graduates via Implicit Feedback Multiple Matri...Recruit Technologies
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This document describes a method for recommending suitable companies to new graduates based on their browsing history and other data. It proposes using implicit matrix factorization of browsing data along with Bayesian optimization of hyperparameters to focus recommendations on less popular, low-browsed companies. An evaluation on Japanese student and company data showed this approach achieved higher recall of suitable matches for low-browsed companies compared to other methods, especially when incorporating additional student and company profile information.
The document discusses the BIG DATA department of Recruit Technologies. It describes how the department has used Amazon's Elastic MapReduce (EMR) and Elastic Compute Cloud (EC2) services since 2010 to perform big data analytics on datasets using Hadoop. It provides details on how the department configures and manages EMR clusters on EC2 spot instances to perform tasks like log analysis and recommendation algorithms in a cost-effective manner. Various strategies are discussed around optimizing the use of spot instances and EMR to reduce costs while managing reliability.