I-Corps: Transmedia publishing platform and service system

这个I-Corps项目的更广泛的影响/商业潜力将使新闻和广泛的媒体消费者以及出版和印刷业受益。该项目增加了印刷出版物与数字互动媒体内容，无论是策划和创建的用户合作。媒体丰富的阅读体验会提升阅读兴趣和新闻媒体消费。在项目期间获得的数据可能会导致新的方法，使不同的受众参与新闻媒体消费。项目？的商业影响源于通过提高读者保留率和增加发行量来扩展印刷媒体传播业的生存能力。更大的受众和基于硬数据的紧密定位市场的能力增加了广告收入。企业及其广告代理商将通过向最终用户提供更相关的广告而受益，每花费一美元就能产生更大的影响力。这个I-Corps项目使用增强现实技术来整合多种信息渠道，包括实体印刷和数字媒体。数字媒体资产被托管在服务器上并且由用户通过自适应界面来访问，该自适应界面基于可用内容和用户偏好来选择性地显示控件。扫描的出版物页面使用在文档数据库上训练的机器学习算法进行分类，并使用图像匹配进一步识别，以实现必要的效率和精度。该系统收集使用数据和交互历史，以了解阅读习惯和媒体交互。这些数据用于分析，也可作为图像匹配工作流程的输入。原型是使用迭代的以用户为中心的设计开发的，并在实验中测试了首选的功能和用户体验。

The broader impact/commercial potential of this I-Corps project will benefit news and broad media consumers, as well as the publishing and printing industries. The project augments print publications with digital interactive media content, both curated and created collaboratively by users. Media rich reading experience will enhance interest in reading and news media consumption. The data obtained during the project may lead to new approaches on engaging different audiences with news media consumption. The project?s commercial impact stems from extending the viability of print media communication industry by both improving reader retention and increasing circulation. A larger audience and the ability to closely target a market based on hard data increases revenue from advertising. Corporations and their advertising agencies will benefit by providing more relevant advertising to end users, delivering more impact per dollar spent.This I-Corps project uses Augmented Reality to integrate multiple information channels including both physical print and digital media. The digital media assets are hosted on a server and accessed by users through an adaptive interface that selectively displays controls based on the available content and user preferences. Scanned publication pages are classified using a machine learning algorithm trained on a document database and further identified using image matching to allow necessary efficiency and precision. The system collects usage data and interaction history to learn about reading habits and media interaction. These data are used for analytics and also as an input for the image matching workflow. The prototype was developed using iterative user-centered design and tested in experiments for preferred functionality and user experience.