Group items tagged

"Discovery is the most important business capability in the emerging Age of Insight - it's the missing ingredient that makes Big Data a source of value for businesses and people. The Language of Discovery is an essential tool for providing discovery capability, whether at the scale of designing a single discovery application, determining the value proposition of a new product or service, or managing a strategic portfolio of technology and business initiatives. This presentation outlines the Age of Insight, and suggests deep structural and historic precedents visible in the Age of Reason, especially in the central parallels between Natural Philosophy and the emerging discipline of Data Science. We then review the language of discovery, and consider widely visible examples of products and services that demonstrate the language. We review our own usage of the framework as an analytical and generative toolkit for providing discovery capability, and share best practices for employing this perspective across a variety of levels of need."

One of the most magical things about the Internet is that it's a whimsical rabbit hole of discovery - we start somewhere familiar and click our way to a wonderland of curiosity and fascination we never knew existed. What makes this contagion of semi-serendipity possible is an intricate ecosystem of "link love" - a via-chain of attribution that allows us to discover new sources through those we already know and trust. 

A question for you: How does discovering and sharing online information make you feel? [I'd bet a good number of you are frustrated, feeling the negative effects of what Eli Pariser calls the "filter bubble"...] Well, here's something else to consider: discovering and sharing information - and the means for curating it - should be serendipitous. Really, it should. A Form of Collective Intelligence I had the fortunate pleasure of meeting up with my friend Jarno Koponen while in Helsinki this past week. Jarno and his founding partner, Marko Anderson, have spent the last two plus years building a predictive discovery engine, called Futureful.

AMHERST, Mass. - As computer scientists this year celebrate the 100th anniversary of the birth of the mathematical genius Alan Turing, who set out the basis for digital computing in the 1930s to anticipate the electronic age, they still quest after a machine as adaptable and intelligent as the human brain. Now, computer scientist Hava Siegelmann of the University of Massachusetts Amherst, an expert in neural networks, has taken Turing's work to its next logical step. She is translating her 1993 discovery of what she has dubbed "Super-Turing" computation into an adaptable computational system that learns and evolves, using input from the environment in a way much more like our brains do than classic Turing-type computers. She and her post-doctoral research colleague Jeremie Cabessa report on the advance in the current issue of Neural Computation. "This model is inspired by the brain," she says. "It is a mathematical formulation of the brain's neural networks with their adaptive abilities." The authors show that when the model is installed in an environment offering constant sensory stimuli like the real world, and when all stimulus-response pairs are considered over the machine's lifetime, the Super Turing model yields an exponentially greater repertoire of behaviors than the classical computer or Turing model. They demonstrate that the Super-Turing model is superior for human-like tasks and learning.

With the unprecedented levels of published information, it is very difficult for Internet users to stay up to date on what matters to them. This situation is especially dramatic for information professionals that must remain aware of new happenings in order to stay ahead of the curve. Content curation is the process of picking the most relevant and valuable content for a specific audience. There is an important human component to content discovery and curation because only users can fully understand the context of the information they are working with. Technology can support content curation by computing large volumes of information on behalf of the user by helping to discover new pieces of Web information.

Social technologies and collaboration tools start to find broad acceptance in the enterprise domain. As well, semantic technologies have been around for a while, offering a range of benefits in the handling of information, including the pervasive linking of content, fostering new forms of content discovery and navigation, and improving content metadata and information retrieval.

Semantics can enhance a broad variety of information processing - search, integration, analysis, pattern extraction and mining, discovery, situational awareness, and question-answering. Consider search: a search system that could distinguish between "Merry Christmas" as a greeting and one of the 60 or so songs named "Merry Christmas" as cataloged in MusicBrainz (a community-created music encyclopedia; http://musicbrainz.org) would have a powerful semantic search capability.