This post is the fourth in a series on the eContext API and how our clients get value out of semantic classification. To learn more about our technology and its uses, feel free to get in touch.
Way back when we were in R&D here at eContext, you could find, at any given time, up to 200 language and subject-matter experts, working on a project basis, curating the vocabulary rules that became the core of eContext’s classification. When the mass development process was over, most of these guys moved on–some to new employment, others to post-grad academics, etc.
I can’t tell you how many times we’ve heard back from one of these former employees, saying something like: “Man… this place where I am right now? They could definitely use what we were building.”
Our last few posts have really been devoted to consumer-oriented applications of eContext: market research, personalization, improved navigation for publisher and ecommerce properties, etc. And yet, while increased convenience and relevance for consumers should absolutely be emphasized, we can’t overlook the benefits of semantic classification for enterprise-level knowledge management.
Imagine you work for a company with a sub-par system of organizing and retrieving documents (which, incidentally, is probably true for most of you). You’re tasked with updating all of your organization’s training and development materials, but since those documents aren’t all in one place, you have to do a little digging. To make matters worse, prior documents have used different terminology to refer to the same concepts, meaning you have to perform separate searches for things like “human resource development” and “corporate education”, among many others.
This kind of gophering isn’t just tedious. It’s expensive. According to research conducted by IDC, inefficiencies in working with documents can cost an organization $19,732 per information worker per year and result in a 21.3% decrease in organization’s overall productivity.
No one, neither a consumer nor an employee, should ever have to conduct multiple searches to look up one common topic. It’s outdated; we have the technology. So below are a few basic steps to use eContext for enterprise document management. If you’d like to know more about the nuts and bolts of integrating classification in your organization’s existing architecture, that’s a conversation we’d love to have with you.
Much like in consumer-oriented content delivery, organizing enterprise materials with semantic classification really involves two separate phases: labeling the documents themselves, then aligning those labels with user navigation methods.
Step One: Classify Content with the eContext API
Broadly speaking, there are a few API calls you’ll want to use here, depending on the type of content to be labeled:
- Classify/html – for HTML content
- Classify/social – for most user-generated content, including long-form documents, archived enterprise messaging, emails, etc.
- Classify/url – for any digital document that exists on a discoverable web page (this blog post, for example)
- Classify/keywords – for extremely short text strings, when you want to limit classification to one best-match topic
- Classify/text – for any general text data not satisfied by the above
Each API call (except for classify/keywords) will generate a list of labels describing the topics of the classified document; these labels can then be appended as part of the document’s metadata.
Step Two: Classify Searches for Apples-to-Apples Retrieval
eContext can be used to classify user searches in real-time, using the classify/keywords API call. For example, the search strings “leadership development” and “leadership instruction” would both be classified to the eContext topic, “Leadership Training”. Remember: eContext’s topics are organized hierarchically, so depending on how you opt to integrate topic classification into your existing infrastructure, you could retrieve content that matches your topic exactly, or include content that matches any of your topic’s subtypes.
Another feature of classify/keywords is the ability to constrain classification to one or more specified verticals. This is particularly helpful in select knowledge management applications where a given subject matter can be assumed. For example, in an organization that deals entirely in the buying and selling of automotive parts and accessories, searches can be automatically be classified to the most relevant automotive category.
While plenty of digital innovation is geared towards consumers, providing more convenience in exchange for increased sales and satisfaction, the technology of the office can often get overlooked, especially in small and medium sized businesses. Organizing your documents by topic–a portable, intuitive, and evergreen system–means employees can save their sanity and companies can save their cash.