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Neural Network Based Boolean Factor Analysis: Efficient Tool for Automated Topics Search.

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F06%3A00032258" target="_blank" >RIV/67985807:_____/06:00032258 - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Neural Network Based Boolean Factor Analysis: Efficient Tool for Automated Topics Search.

  • Original language description

    The paper describes an automatic document concepts searching metod based on recurrent neural network implementation of Boolean factor analysis procedure. Advantage of this approach is the ability of effective analysis of large natural language databases,with rich vocabulary and easy concepts update. Hoppfield-like associative memory with parallel dynamics was substantionaly modified to fulfill this task. We developed totally new recall procedure that allows for the search of all attractors corresponding to factors (a true attractor). Necessary separation of spurious attractors is based on calculation of their Lyapunov function. Being applied to textual data the procedure allows to reveal groups of highly correlated words (factors) which frequently occur in documents jointly and represent concepts covered by these documents.

  • Czech name

    Neurosíťová booleovská faktorová analýza: efektivní nástroj pro automatické vyhledávání témet

  • Czech description

    Uvedena je nová metoda pro automatické vyhledávání konceptů v textových databázích založená na rekurentní neuronové síti Hoppfieldova typu implementující Booleovou faktorovou analýzu. Výhodou tohoto přístupu je schopnost efektivní analýzi v rozsahlých databázích v přirozeném jazyce , s rozsáhlým slovníkem termů a konceptem snadné aktualizace. Nová asociativní paměť Hoppfieldova typu s paralelní dynamikou byla implementována pro řešení této úlohy

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    BB - Applied statistics, operational research

  • OECD FORD branch

Result continuities

  • Project

    <a href="/en/project/1ET100300419" target="_blank" >1ET100300419: Intelligent Models, Algorithms, Methods and Tools for the Semantic Web (realization)</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>Z - Vyzkumny zamer (s odkazem do CEZ)

Others

  • Publication year

    2006

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Computer Science and Information Technology

  • ISBN

    9957-8592-0-x

  • ISSN

  • e-ISSN

  • Number of pages

    7

  • Pages from-to

    321-327

  • Publisher name

    Applied Science Private University

  • Place of publication

    Amman

  • Event location

    Amman

  • Event date

    Apr 5, 2006

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article