EDIA Blog 2024年11月26日
Modern content aggregation: the innovation your company needs
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现代内容聚合公司建立在模块化内容创建、版权清理和内容分发平台三大支柱之上。然而,这些支柱的根基在于元数据聚合,特别是自动化标签。文章强调了模块化和细粒度数据处理的重要性,指出传统方法无法满足现代内容聚合的需求。自动化标签成为构建内容聚合的关键基础,只有具备完善的元数据管理,公司才能跟上市场发展,并为未来做好准备。文章还预告了后续将深入探讨内容元数据及其不同类型。

🤔**模块化是内容聚合的核心理念**: 内容聚合公司需要对内容进行细粒度的标签化处理,例如将书籍细化到章节、段落甚至句子级别,而不是简单地用一个标签概括其类型。

📚**自动化标签是内容聚合的基础**: 传统的标签手动管理方式难以满足现代内容聚合的需求,自动化标签成为构建内容聚合的关键基础,它能够帮助公司高效地管理和组织海量内容。

⚙️**元数据聚合是内容聚合的关键环节**: 元数据聚合涵盖了版权信息、用户数据和内容信息等多个方面,文章重点关注内容元数据,并预告后续将深入探讨这一领域。

📈**自动化标签是未来内容聚合的必要创新**: 为了跟上市场发展,内容聚合公司必须拥抱自动化标签,并建立起完善的元数据管理体系,才能在未来的竞争中立于不败之地。

Today's modern content aggregation companies are built on the same three pillars: modular content creation and ingestion, rights clearance, and a platform for content distribution. In our past few blog posts, we have discussed these pillars, showing how they fit into the overarching picture. But what about the foundation they rest on? Let's have a closer look at the common denominator: metadata aggregation.

The common denominator

Each pillar has its own parameters, but they're all centred around the idea of modularity: it's crucial to label content at a granular level. So, modularity is the common denominator. What this means is that data should be handled minutely as well.

Old-fashioned libraries may simply use one label to indicate a book's genre, but modern content aggregation companies have to dig a lot deeper. Every single content component requires its own label, so labels should be generated and stored meticulously. Those who try to do this manually will go mad in no time. The truth is, it's an unfeasible task.

Solid foundation required

The foundation the three pillars rest on is automated labelling, whose importance should not be underestimated: without it, companies won't be able to participate in modern content aggregation efforts. To keep up with market developments, they simply can't do without well-organised metadata at the most granular level. Each company that wants to be ready for the future should embrace automated labelling. Simply put, it's a necessary innovation.

Of course, there are several types of labels and metadata. They're used at various levels, including rights, user data, and content. In the following weeks, we'll be focusing on the latter — content metadata — which is a field in its own right.

Want to know more about the different types of labels and metadata? Keep an eye on our next blog posts.

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相关标签

内容聚合 元数据 自动化标签 模块化 内容管理
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