683 lines
26 KiB
HTML
683 lines
26 KiB
HTML
<!doctype html>
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<html lang="en">
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<head>
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<meta charset="utf-8">
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<title>Embracing Uncertainty</title>
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<meta name="description" content="Mimir, an awesome system for embracing uncertainty">
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<meta name="author" content="Oliver Kennedy">
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<meta name="apple-mobile-web-app-capable" content="yes" />
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<meta name="apple-mobile-web-app-status-bar-style" content="black-translucent" />
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<meta name="viewport" content="width=device-width, initial-scale=1.0, maximum-scale=1.0, user-scalable=no, minimal-ui">
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<link rel="stylesheet" href="../reveal.js-3.1.0/css/reveal.css">
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<link rel="stylesheet" href="ubodin.css" id="theme">
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<!-- Code syntax highlighting -->
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<link rel="stylesheet" href="../reveal.js-3.1.0/lib/css/zenburn.css">
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<!-- Printing and PDF exports -->
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<script>
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var link = document.createElement( 'link' );
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link.rel = 'stylesheet';
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link.type = 'text/css';
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link.href = window.location.search.match( /print-pdf/gi ) ? '../reveal.js-3.1.0/css/print/pdf.css' : '../reveal.js-3.1.0/css/print/paper.css';
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document.getElementsByTagName( 'head' )[0].appendChild( link );
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<!--[if lt IE 9]>
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<script src="../reveal.js-3.1.0/lib/js/html5shiv.js"></script>
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<![endif]-->
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</head>
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<body>
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<div class="reveal">
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<!-- Any section element inside of this container is displayed as a slide -->
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<div class="header">
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<!-- Any Talk-Specific Header Content Goes Here -->
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Embracing Uncertainty
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</div>
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<div class="footer">
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<!-- Any Talk-Specific Footer Content Goes Here -->
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<div style="float: left; margin-top: 15px; ">
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Exploring <u><b>O</b></u>nline <u><b>D</b></u>ata <u><b>In</b></u>teractions
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</div>
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<img src="graphics/FullText-white.png" height="40" style="float: right;"/>
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</div>
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<div class="slides">
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<section>
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<h2>Embracing Uncertainty</h2>
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<h3>Oliver Kennedy</h3>
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</section>
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<section>
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<h2>Embracing Uncertainty</h2>
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<h4>Oliver Kennedy</h4>
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Joint work with:<br/>
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<h4>
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Ying Yang, Niccolo Meneghetti, Arindam Nandi, <br/>Vinayak Karuppasamy<br/>
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Ronny Fehling, Zhen-Hua Liu, Dieter Gawlick, Boris Glavic
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</h4>
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</section>
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<section>
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<section>
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<h3>A Big Data Fairy Tale</h3>
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</section>
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<section>
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<img src="graphics/dagobert83-female-user-icon-800px.png" height="300" />
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<h4>Meet Alice</h4>
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<attribution>(OpenClipArt.org)</attribution>
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</section>
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<section>
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<img src="graphics/dagobert83-female-user-icon-800px.png" height="300" />
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<img src="graphics/littlestorefront-800px.png" height="300" />
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<h4>Alice has a Store</h4>
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<attribution>(OpenClipArt.org)</attribution>
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</section>
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<section>
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<img src="graphics/littlestorefront-800px.png" height="300" style=" vertical-align: middle;"/>
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<span style="font-size: 3em; vertical-align: middle;">→</span>
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<img src="graphics/matt-icons_text-x-log-300px.png" height="300" style=" vertical-align: middle;" />
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<h4>Alice's store collects sales data</h4>
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<attribution>(OpenClipArt.org)</attribution>
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</section>
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<section>
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<img src="graphics/dagobert83-female-user-icon-800px.png" height="300" style=" vertical-align: middle;"/>
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<span style="font-size: 3em; vertical-align: middle;">+</span>
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<img src="graphics/matt-icons_text-x-log-300px.png" height="300" style=" vertical-align: middle;" />
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<span style="font-size: 3em; vertical-align: middle;">=</span>
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<img src="graphics/saco-800px.png" height="300" style=" vertical-align: middle;" />
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<h4>Alice wants to use her sales data to run a promotion</h4>
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<attribution>(OpenClipArt.org)</attribution>
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</section>
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<section>
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<img src="graphics/matt-icons_text-x-log-300px.png" height="300" style=" vertical-align: middle;"/>
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<span style="font-size: 3em; vertical-align: middle;">→</span>
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<img src="graphics/database-server-800px.png" height="300" style=" vertical-align: middle;" />
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<h4>So Alice loads up her sales data in her trusty database/hadoop/spark/etc... server.</h4>
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<attribution>(OpenClipArt.org)</attribution>
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</section>
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<section>
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<img src="graphics/database-server-800px.png" height="300" style=" vertical-align: middle;" />
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<span style="font-size: 3em; vertical-align: middle;">+ ?</span>
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<h4>... asks her question ...</h4>
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<attribution>(OpenClipArt.org)</attribution>
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</section>
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<section>
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<img src="graphics/database-server-800px.png" height="300" style=" vertical-align: middle;" />
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<span style="font-size: 3em; vertical-align: middle;">+ ? →</span>
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<img src="graphics/crystalball-800px.png" height="300" style=" vertical-align: middle;" />
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<h4>... and basks in the limitless possibilities of big data.</h4>
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<attribution>(OpenClipArt.org)</attribution>
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</section>
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</section>
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<section>
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<section>
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<h2>Why is this a fairy tale?</h2>
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</section>
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<section>
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<img src="graphics/matt-icons_text-x-log-300px.png" height="300" style=" vertical-align: middle;"/>
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<span style="font-size: 3em; vertical-align: middle;">→</span>
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<img src="graphics/database-server-800px.png" height="300" style=" vertical-align: middle;" />
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<h4>It's never this easy...</h4>
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</section>
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<section>
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<h2>Loading Data<h2>
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<small>
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<ul>
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<li class="fragment">Validating and Fixing Outliers</li>
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<li class="fragment">Handling Missing Data</li>
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<li class="fragment">Matching Schemas</li>
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<li class="fragment">Fixing Schemas</li>
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<li class="fragment">Managing Stale Data</li>
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<li class="fragment">Deduplicating Records</li>
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<li class="fragment">... and lots more</li>
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</ul>
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</small>
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</section>
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</section>
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<section>
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<section>
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<h2>Data Cleaning is Hard!</h2>
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</section>
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<section>
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<h3>State of the Art</h3>
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<img src="graphics/BI-Analyst.jpg" height="400" />
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<attribution>(skilledup.com)</attribution>
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<p>Alice spends weeks cleaning her data before using it.</p>
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</section>
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<section>
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<h3>Newer State of the Art</h3>
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<img src="graphics/azure-data-lake.png" height=500 />
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<attribution>(azure.microsoft.com)</attribution>
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</section>
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<section>
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<img src="graphics/data-lake-to-data-swamp.jpg" height=500 />
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<attribution>(timoelliott.com)</attribution>
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</section>
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</section>
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<section>
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<section>
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<h2>Making Cleaning Easier</h2>
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<svg width=500 height=300>
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<polygon
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points="60,50 60,60 40,50 60,40 60,50 440,50 440,40 460,50 440,60 440,50"
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style="
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stroke: black;
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fill: black;
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stroke-width: 2;
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"
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/>
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<text x=0 y=30 style="font-size: 0.75em">Scalability</text>
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<text x=370 y=30 style="font-size: 0.75em">Reliability</text>
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<text class="fragment" x=-220 y=400 style="font-size: 0.75em" transform="rotate(-90 20,20)">Expert Analysis</text>
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<text class="fragment" x=-220 y=250 style="font-size: 0.75em" transform="rotate(-90 20,20)">Crowdsourcing</text>
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<text class="fragment" x=-180 y=100 style="font-size: 0.75em" transform="rotate(-90 20,20)">Automation</text>
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</svg>
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<p class="fragment">Can we start with automation and work our way up?</p>
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</section>
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<section>
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<h3>
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In the name of Codd,<br/><span class="fragment grow highlight-current-blue">thou shalt not give the user a wrong answer.</span>
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</h3>
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<h4 class="fragment">
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... but what if we did?
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</h4>
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<h4 class="fragment">
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What would it take for that to be ok?
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</h4>
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</section>
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</section>
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<section>
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<ul>
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<li>Automate educated guesses for fast cleaning<ul>
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<li><b class="fragment highlight-blue" data-fragment-index="5">Lenses</b>: A family of simple data-cleaning operators</li>
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<li class="fragment" data-fragment-index="1">... but what if the guesses are wrong?</li>
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</ul></li>
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<li class="fragment" data-fragment-index="2">Annotate 'best guess' relations with the guesses<ul>
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<li class="fragment shrink fade-out" data-fragment-index="5"><b>Virtual C-Tables</b>: A lineage model based on views, labeled nulls, and lazy evaluation.</li>
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<li class="fragment" data-fragment-index="3">... so now the user needs to interpret your guesses?</li>
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</ul></li>
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<li class="fragment" data-fragment-index="4">Rank guesses by their impact on result uncertainty<ul>
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<li><b class="fragment highlight-blue" data-fragment-index="5">CPI</b>: A greedy heuristic for ranking sources of uncertainty.</li>
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</ul></li>
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</ul>
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</section>
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<section>
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<section>
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<h3>Lenses</h3>
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<p class="fragment">Here's a problem with my data. <span class="fragment">Fix it.</span></p>
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<ul>
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<li class="fragment">What type is this column? (majority vote)</li>
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<li class="fragment">How do the columns of these relations line up? (pick your favorite schema matching paper)</li>
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<li class="fragment">How do I query heterogeneous JSON objects? (see above)</li>
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<li class="fragment">What should these missing values be? (learning-based interpolation)</li>
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<ul>
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</section>
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<!--
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## Points to get across ##
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* Lenses have minimal configuration
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* Lens = VG-RA Query + Model
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-->
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<section>
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<h3>VG-Relational Algebra<br/><small>(Variable-Generating Relational Algebra)</small></h3>
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<ul>
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<li>Relational Algebra</li>
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<li>Labeled Nulls</li>
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<li>Lazy Evaluation</li>
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</ul>
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</section>
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<section>
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<h3>Labeled Nulls</h3>
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<p>$Var(\ldots)$ constructs new variables</p>
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<ul>
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<li class="fragment">$Var('X')$ constructs a new variable $X$</li>
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<li class="fragment">$Var('X', 1)$ constructs a new variable $X_{1}$</li>
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<li class="fragment">$Var('X', ROWID)$ evaluates $ROWID$ and then constructs a new variable $X_{ROWID}$</li>
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</ul>
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</section>
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<section>
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<h3>Lazy Evaluation</h3>
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<p>Variables can't be evaluated until they are bound.<br/>So, we allow arbitrary expressions to represent data.</p>
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<ul>
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<li class="fragment">$X$ is a legitimate data value.</li>
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<li class="fragment">$X+1$ is a legitimate data value.</li>
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<li class="fragment">$1+1$ is a legitimate data value<span class="fragment">, but can be reduced to $2$.</span></li>
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</ul>
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<p class="fragment">A lazy value without variables is <b>deterministic</b></p>
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</section>
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<section>
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<p>The $Var()$ operator can be inlined into SQL</p>
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<pre><code>
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SELECT A, VAR('X', B)+2 AS C FROM R;
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</code></pre>
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<center><div style="width: 600px" class="fragment">
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<table style="float: left">
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<thead>
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<tr><th>A</th><th>B</th></tr>
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</thead><tbody>
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<tr><td>1</td><td>2</th></tr>
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<tr><td>3</td><td>4</th></tr>
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<tr><td>5</td><td>6</th></tr>
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</tbody>
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</table>
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<table style="float: right" class="fragment">
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<tr><th>A</th><th>C</th></tr>
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<tr><td>1</td><td>$X_2+2$</th></tr>
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<tr><td>3</td><td>$X_4+2$</th></tr>
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<tr><td>5</td><td>$X_6+2$</th></tr>
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</table>
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</div></center>
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<div style="clear: both;"> </div>
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</section>
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<section>
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<p>Selects on $Var()$ need to be deferred too...</p>
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<pre><code>
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SELECT A FROM R WHERE VAR('X', B) > 2;
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</code></pre>
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<center><div style="width: 600px">
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<table style="float: left">
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<thead>
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<tr><th>A</th><th>B</th></tr>
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</thead><tbody>
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<tr><td>1</td><td>2</th></tr>
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<tr><td>3</td><td>4</th></tr>
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<tr><td>5</td><td>6</th></tr>
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</tbody>
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</table>
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<table style="float: right" class="fragment">
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<tr><th>A</th><th>$\phi$</th></tr>
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<tr><td>1</td><td>$X_2>2$</th></tr>
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<tr><td>3</td><td>$X_4>2$</th></tr>
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<tr><td>5</td><td>$X_6>2$</th></tr>
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</table>
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</div></center>
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<div style="clear: both;"> </div>
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<p class="fragment">When evaluating the table, rows where $\phi = \bot$ are dropped.</p>
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</section>
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</section>
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<section>
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<section>
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<h3>C-Tables</h3>
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<ul>
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<li>Original Formulation <small>[Imielinski, Lipski 1981]</small></li>
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<li class="fragment">PC-Tables <small>[Green, Tannen 2006]</small></li>
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<li class="fragment">Systems<ul>
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<li>Orchestra <small>[Green, Karvounarakis, Taylor, Biton, Ives, Tannen 2007]</small></li>
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<li>MayBMS <small>[Huang, Antova, Koch, Olteanu 2009]</small></li>
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<li>Pip <small>[Kennedy, Koch 2009]</small>
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<li>Sprout <small>[Fink, Hogue, Olteanu, Rath 2011]</small></li>
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</ul></li>
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<li class="fragment">Generalized PC-Tables <small>[Kennedy, Koch 2009]</small></li>
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</ul>
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</section>
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<section>
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<h3>Lenses</h3>
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<ul>
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<li class="fragment">A VG-RA Expression</li>
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<li class="fragment">A 'Model' <span class="fragment"> that defines for each variable...</span><ul>
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<li class="fragment">A sampling process</li>
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<li class="fragment">A best guess estimator</li>
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<li class="fragment">A human-readable description</li>
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</ul></li>
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</ul>
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<p class="fragment"><b>Lenses implement PC-Tables</b></p>
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</section>
|
||
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<section>
|
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<pre><code>
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CREATE LENS PRODUCTS
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AS SELECT * FROM PRODUCTS_RAW
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USING DOMAIN_REPAIR(DEPARTMENT NOT NULL);
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</code></pre>
|
||
|
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<ul>
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<li><code>AS</code> clause defines source data.</li>
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<li><code>USING</code> clause requests repairs.</li>
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</ul>
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||
|
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</section>
|
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|
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<section>
|
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<pre><code>
|
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CREATE LENS PRODUCTS
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AS SELECT * FROM PRODUCTS_RAW
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USING DOMAIN_REPAIR(DEPARTMENT NOT NULL);
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</code></pre>
|
||
|
||
<div>
|
||
<h4>The Query</h4>
|
||
<pre><code>
|
||
CREATE VIEW PRODUCTS
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||
AS SELECT ID, NAME, ...,
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CASE WHEN DEPARTMENT IS NOT NULL THEN DEPARTMENT
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ELSE VAR('PRODUCTS.DEPARTMENT', ROWID)
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END AS DEPARTMENT
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FROM PRODUCTS_RAW;
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||
</code></pre>
|
||
</div>
|
||
|
||
<small class="fragment">
|
||
<table>
|
||
<tr><th>ID</th><th>Name</th><th>...</th><th>Department</th></tr>
|
||
<tr><td>123</td><td>Apple 6s, White</td><td>...</td><td>Phone</td></tr>
|
||
<tr><td>34234</td><td>Dell, Intel 4 core</td><td>...</td><td>Computer</td></tr>
|
||
<tr><td>34235</td><td>HP, AMD 2 core</td><td>...</td><td class="fragment">$Prod.Dept_3$</td></tr>
|
||
<tr><td>...</td><td>...</td><td>...</td><td>...</td></tr>
|
||
</table>
|
||
</small>
|
||
</section>
|
||
|
||
<section>
|
||
<pre><code>
|
||
CREATE LENS PRODUCTS
|
||
AS SELECT * FROM PRODUCTS_RAW
|
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USING DOMAIN_REPAIR(DEPARTMENT NOT NULL);
|
||
</code></pre>
|
||
|
||
<div>
|
||
<h4>The Model</h4>
|
||
<pre><code>
|
||
SELECT * FROM PRODUCTS_RAW;
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||
</code></pre>
|
||
</div>
|
||
<div class="fragment">
|
||
<div style="font-size: 1em; vertical-align: middle;">↓</div>
|
||
<div>
|
||
<img src="graphics/weka.png" />
|
||
</div>
|
||
</div>
|
||
<div class="fragment">
|
||
<div style="font-size: 1em; vertical-align: middle;">↓</div>
|
||
<div><p>An estimator for <small style="vertical-align: baseline;">$PRODUCTS.DEPARTMENT_{ROWID}$</small><p></div>
|
||
</div>
|
||
|
||
</section>
|
||
</section>
|
||
|
||
<section>
|
||
<section>
|
||
<h2>The User's View</h2>
|
||
<pre><code>
|
||
SELECT NAME, DEPARTMENT FROM PRODUCTS;
|
||
</code></pre>
|
||
<table class="fragment" data-fragment-index="1">
|
||
<tr><th>Name</th><th>Department</th></tr>
|
||
<tr><td>Apple 6s, White</td><td>Phone</td></tr>
|
||
<tr><td>Dell, Intel 4 core</td><td>Computer</td></tr>
|
||
<tr><td>HP, AMD 2 core</td><td class="fragment highlight-red" data-fragment-index="2">Computer</td></tr>
|
||
<tr><td>...</td><td>...</td></tr>
|
||
</table>
|
||
<p class="fragment" data-fragment-index="2"><b>Simple UI:</b> Highlight values that are based on guesses.</p>
|
||
</section>
|
||
|
||
<section>
|
||
<pre><code>
|
||
SELECT NAME, DEPARTMENT FROM PRODUCTS;
|
||
</code></pre>
|
||
<small>
|
||
<table>
|
||
<tr><th>Name</th><th>Department</th></tr>
|
||
<tr><td>Apple 6s, White</td><td>Phone</td></tr>
|
||
<tr><td>Dell, Intel 4 core</td><td>Computer</td></tr>
|
||
<tr><td>HP, AMD 2 core</td><td style="color: red;">Computer</td></tr>
|
||
<tr><td>...</td><td>...</td></tr>
|
||
</table>
|
||
</small>
|
||
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|
||
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|
||
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|
||
<g stroke="none" stroke-opacity="1" stroke-dasharray="none" fill="none" fill-opacity="1">
|
||
<title>Canvas 1</title>
|
||
<g>
|
||
<title>Layer 1</title>
|
||
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<path d="M 279 351 L 243 369 L 279 387 L 279 389 C 279 394.52285 283.47715 399 289 399 L 494 399 C 499.52285 399 504 394.52285 504 389 L 504 289 C 504 283.47715 499.52285 279 494 279 L 289 279 C 283.47715 279 279 283.47715 279 289 Z" stroke="black" stroke-linecap="round" stroke-linejoin="round" stroke-width="1"/>
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<text transform="translate(293 293)" fill="black"><tspan font-family="Helvetica Neue" font-size="16" font-weight="bold" x="0" y="16" textLength="16.896" class="fragment" data-fragment-index="2">Pr</tspan><tspan font-family="Helvetica Neue" font-size="16" font-weight="bold" x="16.608" y="16" textLength="69.28" class="fragment" data-fragment-index="2">obability:</tspan><tspan font-family="Helvetica Neue" font-size="16" font-weight="500" x="85.888" y="16" textLength="38.24" class="fragment" data-fragment-index="2"> 95%</tspan><tspan font-family="Helvetica Neue" font-size="16" font-weight="bold" x="0" y="53" textLength="62.224" class="fragment" data-fragment-index="3">Reason:</tspan><tspan font-family="Helvetica Neue" font-size="16" font-weight="500" x="62.224" y="53" textLength="144.912" class="fragment" data-fragment-index="3"> Because I guessed </tspan><tspan font-family="Helvetica Neue" font-size="16" font-weight="500" x="0" y="71" textLength="206.592" class="fragment" data-fragment-index="3">‘Computer’ for ‘Department’ </tspan><tspan font-family="Helvetica Neue" font-size="16" font-weight="500" x="0" y="89" textLength="196.16" class="fragment" data-fragment-index="3">on Row ‘3’ of ‘PRODUCTS’</tspan></text>
|
||
</g>
|
||
</g>
|
||
</svg>
|
||
<p class="fragment" data-fragment-index="1">Allow users to <code>EXPLAIN</code> uncertain outputs</p>
|
||
<p class="fragment" data-fragment-index="3">Explanations include reasons given in English</p>
|
||
</section>
|
||
|
||
<section>
|
||
<div style="padding: 30px;">
|
||
<p>$PRODUCTS.DEPARTMENT_{3}$</p>
|
||
<div style="font-size: 2em">⬍</div>
|
||
<p>"I guessed 'Computer' for 'Department' on Row '3'"</p>
|
||
</div>
|
||
<p class="fragment"><b>
|
||
(Generalized) C-Tables are a form of lineage.
|
||
</b></p>
|
||
|
||
</section>
|
||
</section>
|
||
|
||
<section>
|
||
<section>
|
||
<h2>Selection (Filtering)</h2>
|
||
<pre><code>
|
||
SELECT NAME FROM PRODUCTS
|
||
WHERE DEPARTMENT='PHONE'
|
||
AND ( VENDOR='APPLE'
|
||
OR PLATFORM='ANDROID' )
|
||
</code></pre>
|
||
<p class="fragment">Recall, row-level uncertainty is a boolean formula $\phi$.</p>
|
||
<p class="fragment">
|
||
For this query, $\phi$ can be as complex as:
|
||
<small>$$DEPT_{ROWID}='P\ldots' \wedge \left( VEND_{ROWID}='Ap\ldots' \vee PLAT_{ROWID} = 'An\ldots' \right)$$</small></p>
|
||
<p class="fragment"><b>Too many variables! Which is the most important?</b></p>
|
||
</section>
|
||
|
||
<section>
|
||
<h2>What is important?</h2>
|
||
<p class="fragment">Data Cleaning</p>
|
||
<h2 class="fragment">Which variables are important?</h2>
|
||
<p class="fragment">The ones that keep us from knowing everything</p>
|
||
</section>
|
||
|
||
<section>
|
||
<p><small>$$D_{ROWID}='P' \wedge \left( V_{ROWID}='Ap' \vee PLAT_{ROWID} = 'An' \right)$$</small></p>
|
||
<div style="font-size: 2em">⬍</div>
|
||
<p>$$A \wedge (B \vee C)$$</p>
|
||
</section>
|
||
|
||
<section>
|
||
<h3>Naive Approach</h3>
|
||
|
||
<p>Consider a game between a database and an impartial oracle.</p>
|
||
<ul>
|
||
<li>The DB picks a variable $v$ in $\phi$ and pays a cost $c_v$.</li>
|
||
<li>The Oracle reveals the truth value of $v$.</li>
|
||
<li>The DB updates $\phi$ accordingly and repeats until $\phi$ is deterministic.</li>
|
||
</ul>
|
||
<p class="fragment"><b>Naive Algorithm: </b> Pick all variables!</p>
|
||
<p class="fragment"><b>Less Naive Algorithm: </b> Minimize $E\left[\sum c_v\right]$.</p>
|
||
</section>
|
||
|
||
<section>
|
||
<h2>Exponential Time Bad!</h2>
|
||
</section>
|
||
</section>
|
||
|
||
<section>
|
||
<section>
|
||
<h3>The Value of What We Don't Know</h3>
|
||
<p>$$\phi = A \wedge (B \vee C)$$</p>
|
||
<ol>
|
||
<li class="fragment" data-fragment-index="1">Generate Samples for $A$, $B$, $C$</li>
|
||
<li class="fragment" data-fragment-index="2">Estimate $p(\phi)$</li>
|
||
<li class="fragment" data-fragment-index="3">Compute $H[\phi] = -\log\left(p(\phi) \cdot (1-p(\phi))\right)$</li>
|
||
</ol>
|
||
<p class="fragment" data-fragment-index="4"><b>Entropy is intuitive: </b><br/> $H = 1$ means we know nothing, <br/>$H = 0$ means we know everything.</p>
|
||
</section>
|
||
|
||
<section>
|
||
<h3>Information Gain</h3>
|
||
<p>$$\mathcal I_{A \leftarrow \top} (\phi) = H\left[\phi\right] - H\left[\phi(A \leftarrow \top)\right]$$</p>
|
||
<p><b>Information gain of</b> $v$: The reduction in entropy from knowing the truth value of a variable $v$.</p>
|
||
</section>
|
||
|
||
<section>
|
||
<h3>Expected Information Gain</h3>
|
||
<p>$$\mathcal I_{A} (\phi) = \left(p(A)\cdot \mathcal I_{A\leftarrow \top}(\phi)\right) + \left(p(\neg A)\cdot \mathcal I_{A\leftarrow \bot}(\phi)\right)$$</p>
|
||
<p><b>Expected information gain of</b> $v$: The probability-weighted average of the information gain for $v$ and $\neg v$.</p>
|
||
</section>
|
||
|
||
<section>
|
||
<h3>The Cost of Perfect Information</h3>
|
||
<p>Combine Information Gain and Cost</p>
|
||
<p>$$f(\mathcal I_{A}(\phi), c_A)$$</p>
|
||
<p class="fragment"><b>For example: </b>$EG2(\mathcal I_{A}(\phi), c_A) = \frac{2^{\mathcal I_{A}(\phi)} - 1}{c_A}$</p>
|
||
<p class="fragment"><b>Greedy Algorithm: </b> Minimize $f(\mathcal I_{A}(\phi), c_A)$ at each step</p>
|
||
</section>
|
||
|
||
<section>
|
||
<h3>Experimental Data</h3>
|
||
|
||
<ul>
|
||
<li>Start with a large dataset.</li>
|
||
<li>Delete random fields (~50%).</li>
|
||
</ul>
|
||
</section>
|
||
|
||
<section>
|
||
<h3>Experimental Queries</h3>
|
||
|
||
<p>Simulate an analyst trying to manually explore correlations.</p>
|
||
<ul>
|
||
<li>Train a tree-classifier on the base data.</li>
|
||
<li>Convert the decision tree to a query for all rows where the tree predicts a specific value.</li>
|
||
</ul>
|
||
</section>
|
||
|
||
<section>
|
||
<h3>Cost vs Entropy: Credit Data</h3>
|
||
<img src="graphics/credit_entropy.png" height=400 />
|
||
<p><small>
|
||
<b>EG2:</b> Greedy Cost/Value Ordering<br/>
|
||
<b>NMETC:</b> Naive Minimal Expected Total Cost<br/>
|
||
<b>Random:</b> Completely Random Order
|
||
</small></p>
|
||
</section>
|
||
|
||
<section>
|
||
<h3>Cost vs Entropy: Product Data</h3>
|
||
<img src="graphics/product_entropy.png" height=400 />
|
||
<p><small>
|
||
<b>EG2:</b> Greedy Cost/Value Ordering<br/>
|
||
<b>NMETC:</b> Naive Minimal Expected Total Cost<br/>
|
||
<b>Random:</b> Completely Random Order
|
||
</small></p>
|
||
</section>
|
||
|
||
</section>
|
||
|
||
<section>
|
||
|
||
<section>
|
||
<h2>Demo</h2>
|
||
|
||
<p><a href="http://demo.odin.cse.buffalo.edu"><img src="https://odin.cse.buffalo.edu/assets/logos/mimir_logo_final.png" height="400"/></a></p>
|
||
</section>
|
||
|
||
<section>
|
||
|
||
<h2>Intuitive Uncertainty</h2>
|
||
|
||
<p><b>UB</b>: Ying Yang, Niccolo Meneghetti, <br/> Arindam Nandi, Vinayak Karuppasamy</p>
|
||
<p><b>Oracle</b>: Zhen-Hua Liu, Dieter Gawlick</p>
|
||
<p><b>Airbus</b>: Ronny Fehling <b>IIT</b>:Boris Glavic</p>
|
||
|
||
<h4>Thanks to Oracle for multiple gifts that made this research possible</h4>
|
||
</section>
|
||
</section>
|
||
|
||
</div></div>
|
||
|
||
<script src="../reveal.js-3.1.0/lib/js/head.min.js"></script>
|
||
<script src="../reveal.js-3.1.0/js/reveal.js"></script>
|
||
|
||
<script>
|
||
|
||
// Full list of configuration options available at:
|
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// https://github.com/hakimel/../reveal.js#configuration
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Reveal.initialize({
|
||
controls: false,
|
||
progress: true,
|
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history: true,
|
||
center: true,
|
||
slideNumber: true,
|
||
|
||
transition: 'fade', // none/fade/slide/convex/concave/zoom
|
||
|
||
// Optional ../reveal.js plugins
|
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|
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|