Analyzing and Ranking Multimedia Ontologies for their Reuse
1. ANALYZING AND RANKING MULTIMEDIA ONTOLOGIES FOR THEIR REUSE Date: 27/02/11 Speaker: Ghislain Auguste Atemezing Master Thesis Máster de investigación en inteligencia artificial Author: Ghislain Auguste Atemezing Supervisor: Dr. María del Carmen Suárez de Figueroa Baonza
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8. Introduction (VI) Main objective : To search, find, analyze, rank and select suitable multimedia (MM) ontologies to be reused in the development of a multimedia ontology called M3 (Multimedia-Multidominio-Multilingüe) Goal 1 : To o btain a rank of MM ontologies to select the most appropriate ones that will be reused in the development of the M3 ontology. Goal 2 : To d escribe in detail and in a pedagogic way an example of how to apply the methodological guidelines for reusing ontologies in the multimedia domain. Analyzing and Ranking Multimedia Ontologies for their Reuse
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12. MPEG 7 Standard: “Multimedia Content Description” Analyzing and Ranking Multimedia Ontologies for their Reuse Descriptors Components Visual Features Color, Texture, Shape, Motion, Localization, Face recognition. Color Descriptors Color space, Color Quantization, Dominant Colors, Scalable Color, Color Layout, Color-Structure, GoF/GoP Color. Texture Descriptors Homogeneous Texture, Edge Histogram, Texture Browsing Shape Descriptors Region Shape, Contour Shape, Shape 3D Motion Descriptors Camera Motion, Motion Trajectory, Parametric Motion, Motion Activity Localization Descriptors Region locator, Spatio-temporal locator Audio Framework Basic (AudioWaveform, AudioPower), Basic Spectral, Timbral Temporal and Timbral Spectral
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20. Semantic Web Engines (SWEs) Analyzing and Ranking Multimedia Ontologies for their Reuse Semantic Web Engines are applications for finding ontologies where queries are usually written as natural language keywords and results are ranked . RDF-based search engines Ontology-based search engines Hybrid-based search engine
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22. Searching ontologies based on requirements ANALYZING AND RANKING MULTIMEDIA ONTOLOGIES FOR THEIR REUSE ORSD Functional requirements Non Functional requirements
23. Tasks for searching MM ontologies (I) Analyzing and Ranking Multimedia Ontologies for their Reuse Terms translated into English Terms extracted from the ORSD
24. Tasks for searching MM ontologies (II) Analyzing and Ranking Multimedia Ontologies for their Reuse
25. Tasks for searching MM ontologies (III) Analyzing and Ranking Multimedia Ontologies for their Reuse But there are missing ontologies from SoA!! 25 ontologies retrieved with Swoogle
26. Tables of candidate MM ontologies: Unification process Analyzing and Ranking Multimedia Ontologies for their Reuse List of 40 ontologies : SWE + SoA
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28. Analysis based on requirements (I) Analyzing and Ranking Multimedia Ontologies for their Reuse 1-The competency questions (CQs) and one ontology selected from the searching activity. The result is a set of CQs identifiers that cover the given ontology. 3-Open the ontology to analyze in the Neon Toolkit. Open also the document with the list of CQs.
29. Analysis based on requirements (II) Analyzing and Ranking Multimedia Ontologies for their Reuse 4- For each CQs, detect the relevant categories and create a list of "Relevant Categories" (RelevCat). Example : " What are Audio Format ", with the answer: " AVI, MP3 "; RelevCat={Format, Audio, AVI, MP3}. 5- The matching task consists of finding for each term of the relevant categories, its presence in the ontology as a class or an individual . Update (CQ identifier)
30. Assessment table/ ”useful” ontologies Analyzing and Ranking Multimedia Ontologies for their Reuse Heuristic IF ( SimilarScope) OR ( Similar Purpose) OR ( Functional RequirementsCovered ) = No Then NotUseful ( CandidateOntology ) EliminateFromSetCandidate (CandidateOntology) Some wrong situations [Suárez-Figueroa, 2010] 26 “useful” ontologies: 12: SoA 14: SWE
44. ANALYZING AND RANKING MULTIMEDIA ONTOLOGIES FOR THEIR REUSE Date: 27/02/11 Speaker: Ghislain Auguste Atemezing Master Thesis Máster de investigación en inteligencia artificial Author: Ghislain Auguste Atemezing Supervisor: Dr. María del Carmen Suárez de Figueroa Baonza
Hinweis der Redaktion
Analyzing and Ranking Multimedia Ontologies for their Reuse
Mencionar de palabras las Guias Metodológicas NeOn Analyzing and Ranking Multimedia Ontologies for their Reuse
-Mmultimedia is everywhere, with examples. - Definition of MM - Because it is everywhere, it is important to retrieve them efficiently. (need of correct semantic) Analyzing and Ranking Multimedia Ontologies for their Reuse
-Mmultimedia is everywhere, with examples. - Definition of MM - Because it is everywhere, it is important to retrieve them efficiently. (need of correct semantic) Analyzing and Ranking Multimedia Ontologies for their Reuse
Knowledge resources are (ontologies, non-ontological resources, and ontology design patterns) Analyzing and Ranking Multimedia Ontologies for their Reuse
Explain here that it is difficult with such descriptors to identify the objects behind this journalist: Trees, machine, sky, etc. Decir que el fichero Xml tiene otras informaciones: MediaURI, mediaType, SpatialDecomposition Analyzing and Ranking Multimedia Ontologies for their Reuse
“ An ontology is a formal, explicit specification of a shared conceptualization” Studer, Benjamins, Fensel. Knowledge Engineering: Principles and Methods. Data and Knowledge Engineering . 25 (1998) 161-197 Analyzing and Ranking Multimedia Ontologies for their Reuse
M3 es la ontologia que se está desarrollando dentro del proyecto Buscamedia Analyzing and Ranking Multimedia Ontologies for their Reuse
Desarrollo de la red de ontologías según el paradigma de representación de conocimiento basado en Lógica Descriptiva para la formalización utilizando el lenguaje de implementación de ontologías OWL-DL para su implementación y utilizando para ello la herramienta NTK. Analyzing and Ranking Multimedia Ontologies for their Reuse
Analyzing and Ranking Multimedia Ontologies for their Reuse
Analyzing and Ranking Multimedia Ontologies for their Reuse
It is the standard mostly used in the domain of multimedia MPEG 7 is Descriptors (Ds) <---------relationship--- Description Schemes (DSs) Analyzing and Ranking Multimedia Ontologies for their Reuse
Quick presentation of the SoA Analyzing and Ranking Multimedia Ontologies for their Reuse
Quick presentation of the SoA- Elegir MSO: Multimedia Structure Ontology. Analyzing and Ranking Multimedia Ontologies for their Reuse
Elegir Visual Descriptor Ontology (VDO) Analyzing and Ranking Multimedia Ontologies for their Reuse
Quick presentation of the SoA- Elegir Music Ontology with the OR reused. Analyzing and Ranking Multimedia Ontologies for their Reuse
Quick presentation of the SoA- Elegir AEO (Athletic Events Onto) with NORs Analyzing and Ranking Multimedia Ontologies for their Reuse
Punto 2: Objetivo de la ontología M3. Analyzing and Ranking Multimedia Ontologies for their Reuse
Aquí se trata de ver de forma detallada cómo se ha hecho la búsqueda de las ontologias en función de los requisitos que se propone alcanzar la onto. M3. Analyzing and Ranking Multimedia Ontologies for their Reuse
Summary of SWEs- Describe column titles clearly and what they are used for. Swoogle, Watson: ontology –oriented web engines SWSE, Sindice: Triple-oriented Web engines Falcons: Hybrid oriented web engine. Analyzing and Ranking Multimedia Ontologies for their Reuse
Analyzing and Ranking Multimedia Ontologies for their Reuse
Show the files embedded as links if necessary Explicar CQs– CA Analyzing and Ranking Multimedia Ontologies for their Reuse
Decir que es una de tus aportación en el campo—el flujo de trabajo detallado de la búsqueda Analyzing and Ranking Multimedia Ontologies for their Reuse
Explicar que es un proceso iterativo de búsqueda con cada termino. Analyzing and Ranking Multimedia Ontologies for their Reuse
Tabla de las ontologias encontradas con Swoogle. Pero faltan algunas que están en la literatura (un buen número)—Necesidad de unificar los resultados. Analyzing and Ranking Multimedia Ontologies for their Reuse
Emphasis on that those ontologies that were not discovered by Swoogle where completed by others ontologies in the SoA (papers, W3c, projects, etc) Analyzing and Ranking Multimedia Ontologies for their Reuse
Analyzing and Ranking Multimedia Ontologies for their Reuse
Analyzing and Ranking Multimedia Ontologies for their Reuse
4- Those categories are subset of the terms in the &quot;Questions&quot; and &quot;Answers&quot; columns of the CQs document. Analyzing and Ranking Multimedia Ontologies for their Reuse
Explicar que la columna “FRC” sale del proceso anterior Se hace igual Tell something about the wrong situations—Why ? 26, total of “useful” ontologies: SoA—12 + SWE: 14 For the next stage, 23 ontologies: 26 -2 (Nokia) – one intersection (Media Ontology) Analyzing and Ranking Multimedia Ontologies for their Reuse
Analyzing and Ranking Multimedia Ontologies for their Reuse
Adequacy of features and theoretical support: not an upper ontology Knowledge clash: not possible for the lack of comparison Adapatation to the reasoner: a priori constant to every ontology Necessity of bridge terms: absence of explicit constraint in the M3 ontology Analyzing and Ranking Multimedia Ontologies for their Reuse
1- T hus they have very low reuse cost Analyzing and Ranking Multimedia Ontologies for their Reuse
Explain the values of Music ontology and M30. Última tabla: Media Ontology Analyzing and Ranking Multimedia Ontologies for their Reuse
Say something about DIG35, SAPO.. And the final selection of Music ontology Analyzing and Ranking Multimedia Ontologies for their Reuse
They cover 70% of the CQs..Good news for the developer. Analyzing and Ranking Multimedia Ontologies for their Reuse
Analyzing and Ranking Multimedia Ontologies for their Reuse
Analyzing and Ranking Multimedia Ontologies for their Reuse
Analyzing and Ranking Multimedia Ontologies for their Reuse
Analyzing and Ranking Multimedia Ontologies for their Reuse
Explain “multilinguality “ concept in ontology Analyzing and Ranking Multimedia Ontologies for their Reuse
1-Competency Questions are used to query a given Semantic Web Engine. Such an analysis can improve the quality of the analysis of the candidate ontologies. 2-Reason: i t is a time consuming task and to reduce it in domain reuse step, create an API. Therefore, it will reduce the ontology selection process and also improve the quality of the results . Analyzing and Ranking Multimedia Ontologies for their Reuse
Analyzing and Ranking Multimedia Ontologies for their Reuse
Analyzing and Ranking Multimedia Ontologies for their Reuse