Posts Tagged ‘definition’

A Better Definition for Machine Learning

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Bill Franks of the International Institute for Analytics recently opined, “In recent years, the use of the term Machine Learning has surged. What I struggle with is that many traditional data mining and statistical functions are being folded underneath the machine learning umbrella. There is no harm in this except that I don’t think that the general community understands that, in many cases, traditional algorithms are just getting a new label with a lot of hype and buzz appeal. Simply classifying algorithms in the machine learning category doesn’t mean that the algorithms have fundamentally changed in any way.” Read more

Machine Learning: Why It Matters

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Martin Hack of Wired recently wrote, “When Amazon recommends a book you would like, Google predicts that you should leave now to get to your meeting on time, and Pandora magically creates your ideal playlist, these are examples of machine learning over a Big Data stream. With Big Data projected to drive enterprise IT spending to $242 Billion according to Gartner, Big Data is here to stay, and as a result, more businesses of every size are getting into the game. To many enterprise organizations Big Data represents a strategic asset — it reflects the aggregate experience of the organization. Each customer, partner, or supplier response or non-response, transaction, defection, credit default, and complaint provides the enterprise the experience from which to learn.” Read more

Why Cognitive Computing Needs the Semantic Web

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James Kobielus of Info World recently wrote, “Cognitive computing can’t achieve its potential without a strong semantic-processing substrate that executes across diverse content sources… Nova Spivack references IBM Watson in this regard. The cloud service’s DeepQA technology incorporates semantic approaches into its very core, balancing the use of strict and shallow semantics and leveraging many loosely formed ontologies to deliver precise answers to natural-language queries. In my recent big data predictions for 2014, I state that cognitive computing — much of which will move into the cloud — incorporates and extends the innovations pioneered by the semantic Web community.” Read more

Entity Search: The Future of Search

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Paul Bruemmer of Search Engine Land recently wrote, “On September 26, Google took another step toward becoming that answer engine with its Hummingbird update. In Danny Sullivan‘s live blog about the Hummingbird algorithm, he explains how Google is rapidly adopting semantic Web technology while still retaining parts of its old algorithmThis is Google’s solution for evolving from text links to answers. Such a system will display more precise results faster, as it’s based on semantic technology focused on user intent rather than on search terms. To review Google’s progress in this direction: first came the Knowledge Graph, then Voice Search and Google Now — all providing answers, and sometimes even anticipating the questions. To serve these answers, Google relies on entities rather than keywords.” Read more

What You Need to Know About Semantic Search

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Chris Horton of Business 2 Community recently put together what he refers to as a quick primer on semantic search. Horton begins, “In May of 2012, Google rolled out its Knowledge Graph, an AI-like semantic search engine that would forever shift the search paradigm by focusing on ‘things not strings.’ These three simple words heralded a profound evolution in search, taking it from a static system that understood search queries as groups of keyword ‘strings’ to a more dynamic, context based system that could recognize and understand references to actual ‘things,’ i.e. ideas or entities. The dictionary defines the term entity as, ‘A thing with a distinct and independent existence.’ Read more

Infographic: The Importance of RDFa

Mind Development and Design has shared an infographic on The Importance of RDFa. The article states, “RDFa (or Resource Description Framework – in – attributes) is a W3C Recommendation that adds a set of attribute-level extensions to HTML, XHTML and various XML-based document types for embedding rich metadata within Web documents. What does that mean? It means that RDFa give your content more meaning… it allows content to make sense to the search engines.” Read more

Hedgehogs and Linked Data

Ross Spencer of the UK National Archives recently pointed to a project called Hedgehog Street. This is the premise: “Hedgehogs travel around one mile every night through our parks and gardens in their quest to find enough food and a mate. If you have an enclosed garden you might be getting in the way of their plans. Hedgehogs have enough barriers to contend with such as roads and rivers that we can’t do much about. However we can make their life a little easier by removing the barriers within our control – for example making holes in or under our garden fences and walls for them to pass through. The gap need only be around 15cm in diameter and so should not affect your pets’ safety.” Read more

Defining Open Government Data

Anupama Dokeniya has written an article for the World Bank blog discussing open government data. Dokeniya writes, “Even as the language of ‘Open Government’ has picked up steam over the past couple of years – driven initially by the ‘Obama Open Government Directive’, and further boosted by the multi-lateral Open Government Partnership –  the use of the term has tended to fairly broad, and mostly imprecise, lacking a shared, consistent definition. As Nathaniel Heller of Global Integrity, a key player in the OGP, cautioned in a recent blog: ‘The longer we allow ‘open government’ to mean any and everything to anyone, the risk increases that the term melts into a hollow nothingness of rhetoric’.” Read more

RDF: The Basics

A new article by Ric Roberts offers an introductory-level explanation of RDF for newcomers to the Semantic Technology space. Roberts begins, “Linked Data is based around describing real world things using RDF. A lot of articles about Linked Data assume you already know what RDF is all about: if you are coming to it for the first time, this article explains the basics. RDF stands for Resource Description Framework. It’s a W3C standard for modeling information.” Read more

What is a Data Scientist?

In a recent interview Daniel Tunkelang, the principal data scientist at LinkedIn shared his thoughts on what a data scientist is. Tunkelang said, “I’m a big fan of Hilary Mason, chief scientist at bit.ly, so I’ll cite her definition: a data scientist is someone who can obtain, scrub, explore, model and interpret data, blending hacking, statistics and machine learning. Data scientists not only are adept at working with data, but appreciate data itself as a first-class product. At LinkedIn, products pioneered by data scientists, such as People You May Know, harness the power of data to create value for users.” Read more

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