Unstructured Data

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A group of students at the Chalmers University of Technology (Gothenburg, Sweden) tried different approaches to automatically rating the quality of emergency calls, including iKnow.

Excerpt: "The most impressive results produced by iKnow is its ability to correctly classify 100% of the calls using the Average algorithm. This is quite surprising since iKnow only compares low-level concepts, how words relates to each other."

Last comment 3 November 2016
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The Data Platforms department here at InterSystems is gearing up for this year's crop of interns, and I for one am very excited to meet them all next week!

We've got folks from top technical colleges with diverse specialties from hard core engineers to pure computer scientists to mathematicians to business professionals. They come from countries around the world like Vietnam, China, and Finland and they all come with impressive backgrounds. We're sure they will do very well this summer.

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This article contains the tutorial document for a Global Summit academy session on Text Categorization and provides a helpful starting point to learn about Text Categorization and how iKnow can help you to implement Text Categorization models. This document was originally prepared by Kerry Kirkham and Max Vershinin and should work based on the sample data provided in the SAMPLES namespace.

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Unstructured Data, iKnow

iKnow is unique technology for text exploration because it starts with the data itself - a bottom up approach. Embed iKnow text analysis into your application and give users insights based on all the data to enable better decisions.

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So calling this lookup manually from the console works as expected:

PHR>set key = "WMMC_IMM"
PHR>w ##class(Ens.Util.FunctionSet).Lookup("BlockFeed",key)
1

 

However, calling it from a method with some concatination to build the key is giving me problems:

Last comment 22 January 2016
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Caché, Unstructured Data, iKnow

Michael Brands, Product Manager for iKnow, presents information about the real-world demands of working with big data and how to use active analytics with big data.

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Presenter: Danny Wijnschenk
Task: Help people make better decisions by letting application deal with all the data.
Approach: As an example, we’ll extend a demo asset management application for portfolio and trade compliance, using iKnow technology to translate agreements into rules that ensure portfolio compliance prior to trade execution.
 

In this session, we’ll discuss how easy it is to extend a classic application that deals with straightforward transactions, to also offer insights and actions based on more complex, unstructured data. We’ll present a use case on portfolio compliance from the financial services industry.

 

Content related to this session, including slides, video and additional learning content can be found here.

Last comment 14 April 2016
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Presenter: Misha Bouzinier
Task: Gain an understanding of natural language processing and the current state of the art
Approach: Discuss how InterSystems iKnow technology fits into the NLP ecosystem and complements the output of other components such as Lucene and Stanford NLP tools
 

A 101 session on Natural Language Processing that positions Intersystems tools in the broader ecosystem Problem: we’ve been touting “unstructured data” for five years, but many people both internally and externally still don’t know what it means to “process natural language” in general and how iKnow and our upcoming UIMA capabilities fit in this NLP ecosystem. This session will describe what a number of common technologies offer and how bare-bone NLP output typically needs to be complemented with more classic analytics or inference tooling to get the value out.

 

Content related to this session, including slides, video and additional learning content can be found here.

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Unstructured Data, iKnow

Incorporating unstructured text analysis in you application using iKnow can be as simple as Data Exploration - understanding what is in your text or as extensive as determining specific elements in your text.

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Presenter: Dirk Van Hyfte
Task: Leverage unstructured data to improve how clinicians deliver care
Approach: Give real-world examples of organizations that are benefiting from using their unstructured data
 

This session will feature real-world examples of how healthcare organizations can benefit from exposing unstructured data to clinicians at point-of-care as well as to clinical informatics building predictive models. Presenters are Wesley Williams, PhD, Vice President and Chief Information Officer, Mental Health Center of Denver; Augie Turano PhD. IT Director Veterans Informatics and Computer Infrastructure (VINCI); and Dirk Van Hyfte, MD, PhD, Senior Research Consultant.

 

Content related to this session, including slides, video and additional learning content can be found here.

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Unstructured Data, iKnow

Basic iKnow terminology is illustrated with user interface web sites provided as examples of how to use the iKnow APIs. How iKnow works is also discussed.

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Presenter: Benjamin De Boe
Task: Extract specialized information from your unstructured data
Approach: Combine InterSystems iKnow technology with third-party and custom text-processing tools
 

This session explains how you can easily combine ISC, third-party and custom text processing tools to get the broadest insights in your unstructured data.

 

Content related to this session, including slides, video and additional learning content can be found here.

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Unstructured Data, iKnow

Creating and building an iKnow Domain is achieved using the iKnow APIs and a class. Querying the Domain is done using the iKnow APIs and SQL.

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Unstructured Data, iKnow

iKnow provides several mechanisms to query data in your domain. Several tables are built allowing SQL access to your iKnow data. There are three flavors of API access as well: Object Script, SQL Procedures and Web Services.

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Introduction

Experts estimate that 85% of all data exists in unstructured formats – held in e-mails, documents (contracts, memos, clinical notes, legal briefs), social media feeds, etc. Where structured data typically accounts for quantitative facts, the more interesting and potentially more valuable expert opinions and conclusions are often hidden in these unstructured formats. And with massive volumes of text being generated at unprecedented speed, there’s very little chance this information can be made useful without some process of synthesis or automation.

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Hi Community!

Check the new video of the week on the InterSystems Developers YouTube Channel:

Adding Alchemy to Unstructured Data

 

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Introduction - Analyzing Textual Big Data

Big Data for Enriching Analytical Capabilities - Big data is revolutionizing the world of business intelligence and analytics. Gartner predicts that big data will drive $232 billion in spending through 2016, Wikibon claims that by 2017 big data revenue will have grown to $47.8 billion, and McKinsey Global Institute indicates that big data has the potential to increase the value of the US health care industry by $300 billion and to increase the industry value of Europe's public sector administration by Ä250 billion.

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Hi, Community!

This week we have two videos.

Please find the second Developer Community Video of the week on InterSystems Developers YouTube Channel

Turning Accountants into Explorers

 

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