Read e-book online Accelerating Discovery: Mining Unstructured Information for PDF

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By Scott Spangler

ISBN-10: 1482239132

ISBN-13: 9781482239133

Unstructured Mining ways to unravel advanced clinical Problems

As the quantity of medical info and literature raises exponentially, scientists desire extra robust instruments and strategies to approach and synthesize details and to formulate new hypotheses which are probably to be either real and significant. Accelerating Discovery: Mining Unstructured details for speculation Generation describes a unique method of medical learn that makes use of unstructured information research as a generative software for brand new hypotheses.

The writer develops a scientific technique for leveraging heterogeneous dependent and unstructured info resources, information mining, and computational architectures to make the invention procedure speedier and more desirable. This approach speeds up human creativity through permitting scientists and inventors to extra quite simply learn and understand the distance of chances, evaluate possible choices, and observe solely new approaches.

Encompassing systematic and sensible views, the publication presents the mandatory motivation and methods in addition to a heterogeneous set of accomplished, illustrative examples. It unearths the significance of heterogeneous info analytics in helping medical discoveries and furthers facts technological know-how as a discipline.

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Additional resources for Accelerating Discovery: Mining Unstructured Information for Hypothesis Generation

Sample text

It introduced the idea that animals produce more offspring than typically actually survive. This created a “struggle for existence” among competing offspring. ” The Origin of Species was published in 1859, 28 years after the Beagle left on its voyage. And of course, it was many decades later before Darwin’s theory would be generally accepted. ” The first has to do with the 20 years it took Darwin to collect and analyze the data he felt was necessary to develop and validate his theory. The second is related to the connection that Darwin made between his own work and that of Malthus.

The answer is that the representation provides a way to evaluate and predict new properties of entities and new relationships between entities. The precise means of carrying out such prediction may vary from discipline to discipline, and for the most part it will necessarily lie outside the scope of this book. In the example chapters, we will show a few methods by which this may be accomplished, but this should in no way be considered the full set of what is possible. Inferring properties of an entity based on similar entities, using the documents that contain those entities and the text in those documents as a means of defining similarity.

New consumer product formations are mostly done on a trialand-error basis. There is a need across all industries for a reliable, repeatable process to make discovery more cost-effective. COMPUTATIONAL TOOLS THAT ENABLE ACCELERATED DISCOVERY Accelerated Discovery is not just one capability or algorithm but a combination of many complementary approaches and strategies for synthesizing information and formulating hypotheses. The following existing technologies represent the most important enablers of better hypothesis generation in science.

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Accelerating Discovery: Mining Unstructured Information for Hypothesis Generation by Scott Spangler

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