<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/"><channel><title>Semantic-Mapping on The Probability Engine</title><link>https://carlosdanieljimenez.com/tags/semantic-mapping/</link><description>Recent content in Semantic-Mapping on The Probability Engine</description><generator>Hugo -- 0.147.3</generator><language>en-us</language><lastBuildDate>Wed, 07 Jan 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://carlosdanieljimenez.com/tags/semantic-mapping/index.xml" rel="self" type="application/rss+xml"/><item><title>Literary Mapping of Christmas Novels: A Vector Narrative Arc Approach</title><link>https://carlosdanieljimenez.com/post/2026-01-07-literary_mapping/</link><pubDate>Wed, 07 Jan 2026 00:00:00 +0000</pubDate><guid>https://carlosdanieljimenez.com/post/2026-01-07-literary_mapping/</guid><description>&lt;h2 id="post-objective">Post Objective&lt;/h2>
&lt;ul>
&lt;li>Data cleaning and preliminary analysis process&lt;/li>
&lt;li>Understanding the emotional charge or plot development of texts through semantic archaeology based on PCAs&lt;/li>
&lt;li>Understanding the connections and most representative ideas within the document set&lt;/li>
&lt;/ul>
&lt;h2 id="intention">Intention&lt;/h2>
&lt;p>Understanding a story&amp;rsquo;s behavior at the level of its variance is a challenge addressed by attentional engineering. Therefore, using lesser-known methods such as the &lt;strong>vector narrative arc&lt;/strong> combined with a &lt;strong>literary map&lt;/strong> constitutes an interesting route to address increasingly common problems.&lt;/p></description></item></channel></rss>