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Keeping your iKnow domain synchronized

If you've worked with iKnow domain definitions, you know they allow you to easily define multiple data locations iKnow needs to fetch its data from when building a domain. If you've worked with DeepSee cube definitions, you'll know how they tie your cube to a source table and allow you to not just build your cube, but also synchronize it, only updating the facts that actually changed since the last time you built or synced the cube. As iKnow also supports loading from non-table data sources like files, globals and RSS feeds, the same tight synchronization link doesn't come out of the box. In this article, we'll explore two approaches for modelling DeepSee-like synchronization from table data locations using callbacks and other features of the iKnow domain definition infrastructure.

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Introduction to the iKnow REST APIs

After a five-part series on sample iKnow applications (parts 1, 2, 3, 4, 5), let's turn to a new feature coming up in 2017.1: the iKnow REST APIs, allowing you to develop rich web and mobile applications. Where iKnow's core COS APIs already had 1:1 projections in SQL and SOAP, we're now making them available through a RESTful service as well, in which we're trying to offer more functionality and richer results with fewer buttons and less method calls. This article will take you through the API in detail, explaining the basic principles we used when defining them and exploring the most important ones to get started.

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Accessing the iKnow REST APIs in 2017.1

This earlier article already announced the new iKnow REST APIs that are included in the 2017.1 release, but since then we've added extensive documentation for those APIs through the OpenAPI Specification (aka Swagger), which you'll find in the current 2017.1 release candidate. Without wanting to repeat much detail on how the APIs are organised, this article will show you how you can consult that elaborate documentation easily with Swagger-UI, an open source utility that reads OpenAPI specs and uses it to generate a very helpful GUI on top of your API.

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How do I calculate the difference between two texts using iKnow?

I'm in a process of acquiring a corpus  of documents on educational courses. 

For example there is an educational course called "OOP" and it can have documents from 2008, 2009, ... 2016 etc.
And there are a lot of these courses, each one with programs from different years (hopefully)

So 1 document is 1 programm of one course for one year.

I want to calculate how much does a course changes per year.

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[Research] iKnow and algorithms.

Hello! 

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InterSystems Technologies on Amazon EC2: Reference Architecture

Enterprises need to grow and manage their global computing infrastructures rapidly and efficiently while simultaneously optimizing and managing capital costs and expenses. Amazon Web Services (AWS) and Elastic Compute Cloud (EC2) computing and storage services meet the needs of the most demanding Caché based application by providing
 a highly robust global computing infrastructure.

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Free Text Search: The Way To Search Your Text Fields That SQL Developers Are Hiding From You!*

Have some free text fields in your application that you wish you could search efficiently?  Tried using some methods before but found out that they just cannot match the performance needs of your customers?  Do I

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Adding sources to existing domain

The iKnow documentation shows an example for adding sources to a domain after an initial loading of sources.

The example uses text files. However, our data is now in Cache SQL tables.

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Getting started with Text Categorization

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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Bachelor thesis: Automated quality rating of emergency calls using NLP

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.

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iKnow - Text categorization "Category 1 covers the whole dataset"

Hi,

I am using iknow text categorization to classify texts. I have 11 medical articles as my training set. Here is part of the source code:

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Iknow concepts

How to retrive  the unstructure data using iknow concept in Cache . Given real time Example  of these concepts?

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Using complex filters

In a conference call earlier this week, a customer described how they built an iKnow domain with clinical notes and now 

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iKnow demo apps (part 4) - Rules Builder Demo

This is the fourth article in a series on iKnow demo applications, showcasing how the concepts and context provided through iKnow's unique bottom-up approach can be used to implement relevant use cases and help users be more productive in their daily tasks. Previous articles discussed the Knowledge Portal, the Set Analysis Demo and the Dictionary Builder Demo, each of which gradually implemented slightly more advanced interactions with what iKnow gleans from unstructured data.

This week, we'll look into one more demo application, the Rules Builder Demo, in which we'll build on previous work but again climb a step on the level ladder, implementing a more high-level use case than in the previous ones. The idea came from an opportunity where we were asked to help the customer in the finance sector make sense of vast volumes of contract data. They wanted to semi-automate the extraction of logical rules from that text (in fluent legalese!), so they could be fed into other systems. While this was an exciting use case to work on (and more on it in this GS2016 presentation), we've also used it in other cases, for example to extract mentions of ejection fraction from Electronic Health Records.

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