Modeling Synonymy

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F17%3A00094426" target="_blank" >RIV/00216224:14330/17:00094426 - isvavai.cz</a>

Result on the web

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DOI - Digital Object Identifier

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Result language

angličtina

Original language name

Modeling Synonymy

Original language description

Standard text retrieval methods underestimate the semantic similarity between documents that use synonymous terms. Latent semantic indexing (lsa) tackles the problem by clustering frequently co-occuring terms at the cost of the periodical reindexing of dynamic document collections and the suboptimality of cooccurences as a measure of synonymy. In this paper, I develop a term similarity model that suffers neither of these flaws. I analyze the associated computational complexity, show how the model can be implemented into existing ir systems, and evaluate its performance on the semantic text similarity task.

Czech name

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Czech description

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Type

V_souhrn - Summary research report

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

<a href="/en/project/TD03000295" target="_blank" >TD03000295: Intelligent software for semantic text search</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2017

Confidentiality

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

Number of pages

28

Place of publication

Brno

Publisher/client name

Technologická agentura České republiky

Version

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