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<!DOCTYPE html><html lang="en-US"><head><meta charSet="utf-8"/><meta name="citation_title" content="A clustering-based approach to detect probable outcomes of lawsuits"/><meta name="citation_author" content="Daniel Lemes Gribel"/><meta name="citation_author" content="Maira Gatti de Bayser"/><meta name="citation_author" content="Leonardo G. 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aria-haspopup="true" aria-expanded="false" aria-label="User Profile"><svg focusable="false" preserveAspectRatio="xMidYMid meet" xmlns="http://www.w3.org/2000/svg" fill="currentColor" width="20" height="20" viewBox="0 0 32 32" aria-hidden="true"><path d="M16 4a5 5 0 11-5 5 5 5 0 015-5m0-2a7 7 0 107 7A7 7 0 0016 2zM26 30H24V25a5 5 0 00-5-5H13a5 5 0 00-5 5v5H6V25a7 7 0 017-7h6a7 7 0 017 7z"></path></svg></button></div></header></div></div><main id="main-content" class="_95E0P"><article class="elg8D"><div class="VkINb"><div class="aVLxf"><header class="yCh87 xMcIn"><div class="uxPqZ"><div class="jmC80"><div class="WgDvq"><div class="nOEv0">Publication</div><div class="_5uNw_">CIKM 2015</div><div class="DRJNG">Conference paper</div></div><h1 class="O2DSC">A clustering-based approach to detect probable outcomes of lawsuits</h1></div><div class="rwWv4"><a class="kzzKE" href="/publications?source-instance=3145">CIKM 2015</a></div><a class="bPr5E fFsRH bx--btn bx--btn--xl bx--btn--secondary" href="https://dx.doi.org/10.1145/2806416.2806640">View publication<svg focusable="false" preserveAspectRatio="xMidYMid meet" xmlns="http://www.w3.org/2000/svg" fill="currentColor" aria-hidden="true" style="--cds-icon-size-01:1.5rem" width="24" height="24" viewBox="0 0 32 32" class="bx--btn__icon"><path d="M10 6L10 8 22.59 8 6 24.59 7.41 26 24 9.41 24 22 26 22 26 6 10 6z"></path></svg></a><div class="_56tdf"><a aria-label="View publication" class="hl3BR fFsRH bx--btn bx--btn--secondary bx--btn--icon-only" href="https://dx.doi.org/10.1145/2806416.2806640"><svg focusable="false" preserveAspectRatio="xMidYMid meet" xmlns="http://www.w3.org/2000/svg" fill="currentColor" aria-hidden="true" aria-label="View publication" style="--cds-icon-size-01:1.5rem" width="24" height="24" viewBox="0 0 32 32" role="img" class="bx--btn__icon"><path d="M10 6L10 8 22.59 8 6 24.59 7.41 26 24 9.41 24 22 26 22 26 6 10 6z"></path></svg></a></div></div></header><section id="abstract" class="fJ2D5 izDYk"><h2 class="DGVSD">Abstract<svg focusable="false" preserveAspectRatio="xMidYMid meet" xmlns="http://www.w3.org/2000/svg" fill="currentColor" width="24" height="24" viewBox="0 0 32 32" aria-hidden="true"><path d="M16 22L6 12 7.4 10.6 16 19.2 24.6 10.6 26 12z"></path></svg></h2><p class="_8GDu3">The numerous lawsuits in progress or already judged by the Brazilian Supreme Court consists of a large amount of non-structured data. This leads to a large number of hidden or unknown information, since some relationships between lawsuits are not explicit in the available data; and contributes to generate non-intuitive influences between variables, which in addition increases the degree of uncertainty on judicial outcomes. This work proposes an approach to identify possible judgment outcomes that considers the use of similarity calculations and clustering mechanisms based on lawsuits patterns. The similarity problem was tackled by analysing metadata manually extracted from lawsuits; and this work also presents an approach to detect clusters and to compile past votes. From the results, it is possible to verify lawsuits most likely outcomes and to detect their degree of uncertainty.</p></section></div><div class="IrjA7"><nav aria-label="breadcrumbs" class="g9di5 r3uz9"><ol><li><a class="bx--link" href="/">Home</a></li><li><span class="aEWzI" aria-hidden="true">↳ </span><a class="bx--link" href="/publications">Publications</a></li></ol></nav><section class="_8PIse izDYk"><h2 class="DGVSD">Date<svg focusable="false" preserveAspectRatio="xMidYMid meet" xmlns="http://www.w3.org/2000/svg" fill="currentColor" width="24" height="24" viewBox="0 0 32 32" aria-hidden="true"><path d="M16 22L6 12 7.4 10.6 16 19.2 24.6 10.6 26 12z"></path></svg></h2><time dateTime="2015-10-17T00:00:00.000Z">17 Oct 2015</time></section><section class="Yh30P izDYk"><h2 class="DGVSD">Publication<svg focusable="false" preserveAspectRatio="xMidYMid meet" xmlns="http://www.w3.org/2000/svg" fill="currentColor" width="24" height="24" viewBox="0 0 32 32" aria-hidden="true"><path d="M16 22L6 12 7.4 10.6 16 19.2 24.6 10.6 26 12z"></path></svg></h2><a class="bx--link" href="/publications?source-instance=3145">CIKM 2015</a></section><div class="xRbfW"></div><div class="WotuJ HpoGw"><div class="yJoMR"><section id="authors" class="izDYk"><h2 class="DGVSD">Authors<svg focusable="false" preserveAspectRatio="xMidYMid meet" xmlns="http://www.w3.org/2000/svg" fill="currentColor" width="24" height="24" viewBox="0 0 32 32" aria-hidden="true"><path d="M16 22L6 12 7.4 10.6 16 19.2 24.6 10.6 26 12z"></path></svg></h2><ul class="XBsQU qcmp9 _1PgYZ uvfUZ _0CM3a o0Z_b" style="--gap-sm:0.5rem;--gap-md:0.5rem;--gap-lg:0.5rem;--gap-xlg:0.5rem;--gap-max:0.5rem"><li class="iHbnT X4Y7w mBUmN FbtRo _8UAmi bL2oU"><a class="bx--tag ZvHdV undefined _7_FxK _9ckLP bx--tag--gray bx--tag--interactive" id="author-40019" href="/publications?author=40019"><span title="Daniel Lemes Gribel">Daniel Lemes Gribel</span></a></li><li class="iHbnT X4Y7w mBUmN FbtRo _8UAmi bL2oU"><a class="bx--tag ZvHdV undefined _7_FxK _9ckLP bx--tag--blue bx--tag--interactive" id="author-14935" href="/publications?author=14935"><span title="Maira Gatti de Bayser">Maira Gatti de Bayser</span></a></li><li class="iHbnT X4Y7w mBUmN FbtRo _8UAmi bL2oU"><a class="bx--tag ZvHdV undefined _7_FxK _9ckLP bx--tag--blue bx--tag--interactive" id="author-20136" href="/publications?author=20136"><span title="Leonardo G. Azevedo">Leonardo G. Azevedo</span></a></li></ul><div id="author-is-ibm-affiliated" role="presentation" class="sBunA"><svg width="16" height="16" viewBox="0 0 16 16" fill="none" role="presentation"><circle cx="8" cy="8" r="8" fill="#edf5ff"></circle><circle cx="8" cy="8" r="2" fill="#0f62fe"></circle></svg><span>IBM-affiliated at time of publication</span></div></section></div><section id="share" class="TLVcm izDYk"><h2 class="DGVSD">Share<svg focusable="false" preserveAspectRatio="xMidYMid meet" xmlns="http://www.w3.org/2000/svg" fill="currentColor" width="24" height="24" viewBox="0 0 32 32" aria-hidden="true"><path d="M16 22L6 12 7.4 10.6 16 19.2 24.6 10.6 26 12z"></path></svg></h2><div class="gSf0j n7jWd"><button type="button" aria-label="Share on Facebook" class="iu7Pg"><svg focusable="false" preserveAspectRatio="xMidYMid meet" xmlns="http://www.w3.org/2000/svg" fill="currentColor" aria-hidden="true" width="32" height="32" viewBox="0 0 32 32"><path d="M26.67,4H5.33A1.34,1.34,0,0,0,4,5.33V26.67A1.34,1.34,0,0,0,5.33,28H16.82V18.72H13.7V15.09h3.12V12.42c0-3.1,1.89-4.79,4.67-4.79.93,0,1.86,0,2.79.14V11H22.37c-1.51,0-1.8.72-1.8,1.77v2.31h3.6l-.47,3.63H20.57V28h6.1A1.34,1.34,0,0,0,28,26.67V5.33A1.34,1.34,0,0,0,26.67,4Z"></path></svg></button><button type="button" aria-label="Share on X" class="iu7Pg"><svg fill="currentColor" xmlns="http://www.w3.org/2000/svg" preserveAspectRatio="xMidYMid meet" style="padding:4px" aria-hidden="true" width="32" height="32" viewBox="0 0 1200 1226.37" focusable="false"><path style="stroke-width:0" d="m714.16,519.28L1160.89,0h-105.86l-387.89,450.89L357.33,0H0l468.49,681.82L0,1226.37h105.87l409.63-476.15,327.18,476.15h357.33l-485.86-707.09h.03Zm-145,168.54l-47.47-67.89L144.01,79.69h162.6l304.8,435.99,47.47,67.89,396.2,566.72h-162.6l-323.31-462.45v-.03Z"></path></svg></button><button type="button" aria-label="Share on LinkedIn" class="iu7Pg"><svg focusable="false" preserveAspectRatio="xMidYMid meet" xmlns="http://www.w3.org/2000/svg" fill="currentColor" aria-hidden="true" width="32" height="32" viewBox="0 0 32 32"><path d="M26.2,4H5.8C4.8,4,4,4.8,4,5.7v20.5c0,0.9,0.8,1.7,1.8,1.7h20.4c1,0,1.8-0.8,1.8-1.7V5.7C28,4.8,27.2,4,26.2,4z M11.1,24.4 H7.6V13h3.5V24.4z M9.4,11.4c-1.1,0-2.1-0.9-2.1-2.1c0-1.2,0.9-2.1,2.1-2.1c1.1,0,2.1,0.9,2.1,2.1S10.5,11.4,9.4,11.4z M24.5,24.3 H21v-5.6c0-1.3,0-3.1-1.9-3.1c-1.9,0-2.1,1.5-2.1,2.9v5.7h-3.5V13h3.3v1.5h0.1c0.5-0.9,1.7-1.9,3.4-1.9c3.6,0,4.3,2.4,4.3,5.5V24.3z"></path></svg></button></div></section></div></div></div><footer class="r3d6q"><div class="ZS8pD"><section id="related" class="RmiXj izDYk"><h2 class="DGVSD">Related<svg focusable="false" preserveAspectRatio="xMidYMid meet" xmlns="http://www.w3.org/2000/svg" fill="currentColor" width="24" height="24" viewBox="0 0 32 32" aria-hidden="true"><path d="M16 22L6 12 7.4 10.6 16 19.2 24.6 10.6 26 12z"></path></svg></h2><div class="eHeTk"><article class="E8N0J _9GOJO"><div class="_2AUU"><div class="rndoq"><svg focusable="false" preserveAspectRatio="xMidYMid meet" xmlns="http://www.w3.org/2000/svg" fill="currentColor" aria-hidden="true" width="24" height="24" viewBox="0 0 32 32" class="CjjQi"><path d="M25.7,9.3l-7-7C18.5,2.1,18.3,2,18,2H8C6.9,2,6,2.9,6,4v24c0,1.1,0.9,2,2,2h16c1.1,0,2-0.9,2-2V10C26,9.7,25.9,9.5,25.7,9.3 z M18,4.4l5.6,5.6H18V4.4z M24,28H8V4h8v6c0,1.1,0.9,2,2,2h6V28z"></path><path d="M10 22H22V24H10zM10 16H22V18H10z"></path></svg><div class="sXPlN"><div tabindex="0" class="L4C9a" aria-label="Abstract excerpt" role="region"><svg focusable="false" preserveAspectRatio="xMidYMid meet" xmlns="http://www.w3.org/2000/svg" fill="currentColor" aria-hidden="true" width="24" height="24" viewBox="0 0 32 32"><path d="M17 22L17 14 13 14 13 16 15 16 15 22 12 22 12 24 20 24 20 22 17 22zM16 8a1.5 1.5 0 101.5 1.5A1.5 1.5 0 0016 8z"></path><path d="M16,30A14,14,0,1,1,30,16,14,14,0,0,1,16,30ZM16,4A12,12,0,1,0,28,16,12,12,0,0,0,16,4Z"></path></svg></div></div></div><div class="UTCr9"><div class="c9tVS">Conference paper</div><h3 class="sa_bq"><a href="/publications/microservice-architecture-for-multistore-database-using-canonical-data-model">Microservice architecture for multistore database using canonical data model</a></h3></div><footer class="SIZ95"><p>Luís Henrique Neves Villaça, Leonardo G. Azevedo, et al.</p><p class="XErfb">SBSI 2020</p></footer><svg focusable="false" preserveAspectRatio="xMidYMid meet" xmlns="http://www.w3.org/2000/svg" fill="currentColor" aria-hidden="true" width="24" height="24" viewBox="0 0 24 24" class="dgEn3"><path d="M14 4L12.9 5.1 18.9 11.2 2 11.2 2 12.8 18.9 12.8 12.9 18.9 14 20 22 12z"></path></svg></div></article><article class="E8N0J _9GOJO"><div class="_2AUU"><div class="rndoq"><svg focusable="false" preserveAspectRatio="xMidYMid meet" xmlns="http://www.w3.org/2000/svg" fill="currentColor" aria-hidden="true" width="24" height="24" viewBox="0 0 32 32" class="CjjQi"><path d="M25.7,9.3l-7-7C18.5,2.1,18.3,2,18,2H8C6.9,2,6,2.9,6,4v24c0,1.1,0.9,2,2,2h16c1.1,0,2-0.9,2-2V10C26,9.7,25.9,9.5,25.7,9.3 z M18,4.4l5.6,5.6H18V4.4z M24,28H8V4h8v6c0,1.1,0.9,2,2,2h6V28z"></path><path d="M10 22H22V24H10zM10 16H22V18H10z"></path></svg><div class="sXPlN"><div tabindex="0" class="L4C9a" aria-label="Abstract excerpt" role="region"><svg focusable="false" preserveAspectRatio="xMidYMid meet" xmlns="http://www.w3.org/2000/svg" fill="currentColor" aria-hidden="true" width="24" height="24" viewBox="0 0 32 32"><path d="M17 22L17 14 13 14 13 16 15 16 15 22 12 22 12 24 20 24 20 22 17 22zM16 8a1.5 1.5 0 101.5 1.5A1.5 1.5 0 0016 8z"></path><path d="M16,30A14,14,0,1,1,30,16,14,14,0,0,1,16,30ZM16,4A12,12,0,1,0,28,16,12,12,0,0,0,16,4Z"></path></svg></div></div></div><div class="UTCr9"><div class="c9tVS">Conference paper</div><h3 class="sa_bq"><a href="/publications/on-the-maintenance-of-a-scientific-application-based-on-microservices-an-experience-report">On the Maintenance of a Scientific Application based on Microservices: An Experience Report</a></h3></div><footer class="SIZ95"><p>Leonardo P. Tizzei, Leonardo G. Azevedo, et al.</p><p class="XErfb">ICWS 2020</p></footer><svg focusable="false" preserveAspectRatio="xMidYMid meet" xmlns="http://www.w3.org/2000/svg" fill="currentColor" aria-hidden="true" width="24" height="24" viewBox="0 0 24 24" class="dgEn3"><path d="M14 4L12.9 5.1 18.9 11.2 2 11.2 2 12.8 18.9 12.8 12.9 18.9 14 20 22 12z"></path></svg></div></article><article class="E8N0J _9GOJO"><div class="_2AUU"><div class="rndoq"><svg focusable="false" preserveAspectRatio="xMidYMid meet" xmlns="http://www.w3.org/2000/svg" fill="currentColor" aria-hidden="true" width="24" height="24" viewBox="0 0 32 32" class="CjjQi"><path d="M25.7,9.3l-7-7C18.5,2.1,18.3,2,18,2H8C6.9,2,6,2.9,6,4v24c0,1.1,0.9,2,2,2h16c1.1,0,2-0.9,2-2V10C26,9.7,25.9,9.5,25.7,9.3 z M18,4.4l5.6,5.6H18V4.4z M24,28H8V4h8v6c0,1.1,0.9,2,2,2h6V28z"></path><path d="M10 22H22V24H10zM10 16H22V18H10z"></path></svg><div class="sXPlN"><div tabindex="0" class="L4C9a" aria-label="Abstract excerpt" role="region"><svg focusable="false" 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The effective integration of symbolic knowledge with non-symbolic content enables richer knowledge representation and reasoning, and more explainable and efficient training of machine learning models used across multiple AI applications. This demo's main goal is to present how the Knowledge Explorer System (KES) multiview architecture enables contextualized ontology modeling over a hybrid knowledge representation by making it easier to create and visualize taxonomies and relationships defined in a specific context. 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