Towards measuring the complexity of introducing semantics into a company

Alvarez de Mon Rego, Inmaculada and Barbosa Santillán, Liliana Ibeth (2013). Towards measuring the complexity of introducing semantics into a company. In: "2013 IEEE Systems and InformationEngineering Design Symposium : SIEDS'13", 26/04/2013 - 26/04/2013, Charlottesville, Virginia, USA. ISBN 978-1-4673-5662-6. pp. 86-91. https://doi.org/10.1109/SIEDS.2013.6549499.

Description

Title: Towards measuring the complexity of introducing semantics into a company
Author/s:
  • Alvarez de Mon Rego, Inmaculada
  • Barbosa Santillán, Liliana Ibeth
Item Type: Presentation at Congress or Conference (Article)
Event Title: 2013 IEEE Systems and InformationEngineering Design Symposium : SIEDS'13
Event Dates: 26/04/2013 - 26/04/2013
Event Location: Charlottesville, Virginia, USA
Title of Book: Systems and Information Engineering Design Symposium (SIEDS), 2013 IEEE
Date: 2013
ISBN: 978-1-4673-5662-6
Subjects:
Freetext Keywords: Information management
Faculty: E.U.I.T. Telecomunicación (UPM)
Department: Lingüistica Aplicada a la Ciencia y a la Tecnología
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

The Semantics Difficulty Model (SDM) is a model that measures the difficult of introducing semantics technology into a company. SDM manages three descriptions of stages, which we will refer to as ?snapshots?: a company semantic snapshot, data snapshot and semantic application snapshot. Understanding a priory the complexity of introducing semantics into a company is important because it allows the organization to take early decisions, thus saving time and money, mitigating risks and improving innovation, time to market and productivity. SDM works by measuring the distance between each initial snapshot and its reference models (the company semantic snapshots reference model, data snapshots reference model, and the semantic application snapshots reference model) with Euclidian distances. The difficulty level will be "not at all difficult" when the distance is small, and becomes "extremely difficult" when the the distance is large. SDM has been tested experimentally with 2000 simulated companies with arrangements and several initial stages. The output is measured by five linguistic values: "not at all difficult, slightly difficult, averagely difficult, very difficult and extremely difficult". As the preliminary results of our SDM simulation model indicate, transforming a search application into integrated data from different sources with semantics is a "slightly difficult", in contrast with data and opinion extraction applications for which it is "very difficult".

More information

Item ID: 26519
DC Identifier: http://oa.upm.es/26519/
OAI Identifier: oai:oa.upm.es:26519
DOI: 10.1109/SIEDS.2013.6549499
Official URL: http://www.sys.virginia.edu/sieds13/
Deposited by: Memoria Investigacion
Deposited on: 29 Aug 2014 18:08
Last Modified: 22 Sep 2014 11:41
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