It has been widely reported that the volume of papers emerging form the world’s universities is exploding, with estimates as high as 10,000 new papers being published every day.  To help deal with this, a number of tools have been developed to help people to keep on top of things.

For instance, I’ve written previously about Semantic Scholar, Meta and Meta Bus, all of which aim to help people find the proverbial needle in the haystack.

The latest product to hit the market is Omnity, a semantic search platform that aims to find value in the connections between pieces of content.

Conceptual bridges

The platform harvests an array of rare, yet shared, words to form a query that is then used to find connections between content that can help users derive contextual understanding of a topic.  The tool is nice because it isn’t necessary for articles to link to one another for connections to be made.

Of course, whilst there are clear use cases for this in terms of scientific literature, the platform is capable of performing this semantic analysis of any data source, whether it’s internal product data, clinical trial data or legal analysis.

“We’ve cracked the code on connecting researchers with content they typically would spend enormous cost and time to discover in a far simpler and more cost-effective platform,” the team say. “Now we’ve expanded our platform’s unique technology so they can actually seek, find and structure the data they desire in their own fully customized experience.”

Digital assistance

An alternative approach has been taken by researchers at the Universities of Strathclyde and Glasgow.  They developed a search agent that was designed to trawl literature, and in an experiment that pitted the agent against experts in the field, the agent was the clear victor.

“An autonomous search agent could be useful for researchers reviewing vast amounts of literature in subjects such as law and medicine. In this type of information-intensive review, it could read through and assess information while the researcher is working on other things, then suggest other sources of information that would be relevant,” the researchers say.

The researchers had built on previous attempts to perform this task that were found to be somewhat unintelligent.  They would often behave randomly as opposed to intelligently acting on the information they found.

“The model we have developed takes account of what the autonomous agents knows, has done and has seen, along with what it considers to be relevant. It is constantly evolving,” they say.

When the system was put through its paces against 48 experts, the human beings were comprehensively beaten by the autonomous agents.  The results suggest that not only are such agents capable of recreating the way humans search for information, but can often do so more comprehensively.

The data deluge shows little sign of abating, so tools such as Omnity and the others that are entering the market will be increasingly important to help knowledge workers stay on top of it.