Mathematical modeling

Boolean model of information retrieval

The (standard) Boolean model of information retrieval (BIR) is a classical information retrieval (IR) model and, at the same time, the first and most-adopted one. It is used by many IR systems to this day. The BIR is based on Boolean logic and classical set theory in that both the documents to be searched and the user's query are conceived as sets of terms (a bag-of-words model). Retrieval is based on whether or not the documents contain the query terms. (Wikipedia).

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Using Boolean in Python (Python Tutorial #11)

Using Boolean in Python - let's go! This entire series in a playlist: https://goo.gl/eVauVX Also, keep in touch on Facebook: https://www.facebook.com/entercsdojo And Twitter: https://twitter.com/ykdojo

From playlist Python Tutorials for Absolute Beginners by CS Dojo

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Boolean Algebra: Sample Problems

In this video, I work through some sample problems relating to Boolean algebra. Specific, I work through examples of translating equivalences from logical or set notation to Boolean notation, and also a derivation using Boolean equivalences.

From playlist Discrete Mathematics

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Domain Specific Applications

Guest lecture by Sophia Althammer (https://twitter.com/sophiaalthammer) In this lecture we learn how about different task settings, challenges, and solutions in domains other than web search. Slides & transcripts are available at: https://github.com/sebastian-hofstaetter/teaching 📖 Check

From playlist Advanced Information Retrieval 2021 - TU Wien

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Boolean Algebra 2 – Simplifying Complex Expressions

This video follows on from the one about the laws of Boolean algebra. It explains some useful interpretations of the laws of Boolean algebra, in particular, variations of the annulment and distributive laws. It goes on to demonstrate how Boolean algebra can be applied to simplify comple

From playlist Boolean Algebra

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Learning Logically Defined Hypotheses - Martin Grohe, RWTH Aachen University

I will introduce a declarative framework for machine learning where hypotheses are defined by formulas of a logic over some background structure. Within this framework, I will discuss positive as well as negative learnability results (in the "probably approximately correct" learning sense)

From playlist Logic and learning workshop

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The New NIO, aka JSR-203

Google Tech Talks May, 1 2008 ABSTRACT JSR-203 is the NIO update JSR scheduled for release with Java 7. This talk will present an overview of the new NIO features and improvements. Speaker: Alan Bateman Software Engineer at Sun Microsystems. Spec lead on JSR-203. Speaker: Carl Quinn S

From playlist Software Development Lectures

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Rule Based and Pattern Matching for Entity Recognition in Spark NLP

Try Spark NLP here: https://www.johnsnowlabs.com/spark-nlp/ Finding patterns and matching strategies are well-known NLP procedures to extract information from text. Spark NLP library has two annotators that can use these techniques to extract relevant information or recognize entities o

From playlist AI & NLP Webinars

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Francesco Ciraulo: Notions of Booleanization in pointfree Topology

The lecture was held within the framework of the Hausdorff Trimester Program: Types, Sets and Constructions. Abstract: Boolean algebras play a key role in the foundations of classical mathematics. And a similar role is played by Heyting algebras for constructive mathematics. But this is

From playlist Workshop: "Constructive Mathematics"

Related pages

Disjunctive normal form | Bayes' theorem | BitFunnel | Set theory | Bloom filter | Inverted index | Hash table