6 Traits of Highly Effective Content Discovery Engines
Posted by Romain Goday on Sun, Oct 23, 2011
What Is a Content Discovery Engine?
Content discovery engines are similar to, but different from search engines. Like search engines, discovery engines exist to help people consume information. But with Web content doubling every two years, traditional search engines make it difficult to keep up with new and relevant information. The biggest difference between a discovery engine and a search engine is a discovery engine aggregates information and highlights key pieces of information as they relate to a topic of interest. So, instead of simply providing results for a specific search query, discovery engines allow users to monitor topic-specific developments. There are many types of discovery engines, and the technology that drives them and the way they present information differs greatly.
Why Are Content Discovery Engines Gaining Importance?
Content discovery engines are growing in popularity as more people recognize their potential to transform information consumption. Discovery engines are moving progressively from amusement tools towards becoming instruments that save time and encourage effective information consumption. Listed below are six traits that we believe will determine the future of highly effective discovery engines and their impact on productivity.
6 Traits of Highly Effective Content Discovery Engines
Monitor Unique Topics of Interest
A unique personal interest is one that does not currently exist in the scope of existing tags or categories. If a user needs to monitor developments in pharmaceutical product developments related to cholesterol or the latest trends in the Italian shoe manufacturing materials, it should be possible. The technology should allow the topic of interest to be precise enough to make the discovery engine fulfill the specific information need of the user.
In Real-Time
The discovery process is time sensitive. Users gain value in finding out instantly about important events that are taking place. Real-time platforms, like Twitter, gained a lot of momentum and democratized the spread of information. As its membership grew, the ever-increasing volume of information is too large for the ordinary person to follow. A good content discovery engine should continue the legacy of real-time awareness without the pain of information overload.
Independent From Sources
Information comes from a variety of sources these days. The way that information is prioritized depends highly on inbound links, popularity or social graphs. In order to discover relevant information, users are forced to rely on the way these sources compute popularity to digitally curate content on their behalf. Rather than rely on the way sources display information, a good content discovery engine should be dependent only on the content itself. The source of the information should not influence whether it is displayed or not.
Human-Centered
The user must be at the center of the curation process. The content discovery engine must leverage the personal experience and expertise of the user instead of using assumptions to personalize the content on his behalf. The premise that machines can replace the human brain is faulty for several reasons. Relying on technology to personalize content based on past behaviors, social graphs or other methods is not optimal because user motivations are dynamic and differ from that of their network of friends. The meaning and value of a piece of content depends entirely on the context. Only a user possesses the ability to place a piece of information within context and no algorithm can come close to recreating that ability.
Eliminate the Noise
An effective content discovery engine should aggregate and present information that comes from a scope that is broad enough to ensure that no important content is missed. However, if the breadth of information is broad then there is a risk that the result would be too noisy and would impede on a user’s ability to identify valuable pieces of information. Thus, the challenge of a discovery engine is that it must sift through a broad scope of information while simultaneously reducing the noise. In order to do this, an effective content discovery engine should be equipped with a user interface that allows users to quickly isolate areas to explore further, to avoid spending time on meaningless information, but cover a broad enough range to avoid missing anything important.
Display Emerging Patterns
To truly know what is going on, simple facts are not enough. One must see the correlations between said facts and the patterns with which they evolve. An effective discovery engine does not merely report on new pieces of information but shows how those new pieces of information relate to new developments. This can only be done by detecting the patterns between the facts and the order in which they emerge, evolve and disappear. Doing so would enable users to focus their attentions on underlying aspects not readily available to search engine or news site users. Patterns are the key to information awareness.
Conclusion
There is an increasing need for relevant content to benefit users of the web. As content repository increases in size, discovery engines will be a primary means of finding new information. In order for content discovery engines to succeed, they will need to find the right balance between:
- Reducing the noise of irrelevant information without filtering out information or making assumptions about useful data for a user
- Cast a wide net to ensure that nothing important is overlooked, while helping the user focus on the information that matters
- Inform the user on developments while demonstrating the relationships between events
Liked this post?
Subscribe to our blog at the top of the page or follow @Darwineco!
............................................................................................................................................................
Related Articles:
Content Curation: Why Detecting Emerging Patterns is Crucial
Content Curation Tools: 5 Different Approaches
5 Reasons Content Discovery Engines Need a Human Touch
Search and Discovery: How They Complement Each Other
............................................................................................................................................................
