Music and Audio Information Search System

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Music and Audio Information Search System

• Kiavash Bahreini 055251

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Outline

• Introduction
• Semantic Web
• What is Ontology?
• Domains and ranges
• Ontology Languages (OWL)
• Search on the Web
• Object-oriented Modeling Paradigm
• Adaptable Inference Capabilities
• Background
• The Music Ontology and OWL
• Protégé
• JBuilder 2006
• Jena 2.3 Ontology API

3
Outline (cont)

• RDQL
• Java Server Pages
• Algernon
• Tomcat
• Microsoft SQL Server
• Music and Audio system use case, implementation
  and execution
• Execution of program in Browser
• Running queries in Algernon
• Running queries in SQL Server 2005
• Some source codes for classes in Music and Audio
  ontology
• Comparison of Semantic Search and Regular Search
• Conclusion
• References

4
Introduction

• Internet changed the music industry. At first,
  sharing systems like Napster allowed people to
  share any song they had on their computer with
  millions other people.
• Communities like this ontology started to appear.
  
• The Music Ontology is an attempt to link all the
  information about musical Artists, Albums and
  Tracks together from MusicBrainz to my ontology.

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Introduction (Cont)

• The goal is to express all relations between
  musical information to help people finding
  anything about music and musicians. It is based
  around the use of machine readable information
  provided by any web site or web service on the
  Web.

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Semantic Web

• Common framework
• Allows data
• Sharing
• Reuse
• Across domains
• Application
• Enterprise
• Community boundaries
• Based on Resource Description Framework (RDF)
• XML for syntax
• URIs for naming.

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What is Ontology?

• At the heart of all Semantic Web applications is
  the use of ontologies. A commonly agreed
  definition of an ontology is An ontology is an
  explicit and formal specification of a
  conceptualisation of a domain of interest.

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Domains and ranges
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Ontology Languages (OWL)

• OWL Lite
• OWL DL
• OWL Full

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Search on the Web

• Seeking information on the Web is widely used and
  will become more important as the Web grows.
  Nowadays, search engines browse through the Web
  seeking given terms within web pages or text
  documents without using ontologies.
• Traditional search engines such as Yahoo are
  based on full-text search. These search engines
  are seeking documents, which contain certain
  terms.

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Object-oriented Modeling Paradigm

• In the past decade the object-oriented paradigm
  has become prevalent for conceptual modeling.
• Object-oriented models can easily be visualized,
  thus making understanding conceptual models much
  simpler. Hence, any successful ontology modeling
  approach should follow the object-oriented
  modeling paradigm.

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Adaptable Inference Capabilities

• Inference mechanisms for deduction of information
  not explicitly asserted is an important
  characteristic of ontology-based systems.
  However, systems with very general inference
  capabilities often do not take into account other
  needs, such as scalability and concurrency.
• For example, in the RDFS and OWL ontology
  languages it is possible to make some classes the
  domain or the range of some property. This
  statement can be interpreted as an axiom saying
  that for any property instance in the ontology,
  the source and target instances can be inferred
  to be members of the domain and target concepts,
  respectively.

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Background

• The Music Ontology is an effort of ZitGist LLC.
  to express musical relationships between artists,
  albums and tracks.
• I used OWL and to query that same information
  using the RDQL query language for RDF and OWL.
• The Music Ontology is mainly influenced by the
  MusicBrainz community music metadatabase. Most of
  the properties of this ontology reflect the
  relationships described in that database. Most of
  the relationship descriptions written in this
  document have been taken on the MusicBrainz Wiki

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The Music Ontology and OWL

• The Music Ontology is an application of the
  Ontology Web Language (OWL) because the subject
  area I am describing music albums, artists,
  audio files, audio file formats, encoding audio
  files, genre, instrument, key, note, official,
  resource, rhythm etc has so many competing
  requirements.
• By using OWL, the Music Ontology gains a powerful
  extensibility mechanism, allowing
  Music-Ontology-based descriptions to be mixed
  with claims made in any other OWL and RDF
  vocabulary

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Protégé

• Protégé is
• an ontology editor
• knowledge-base editor
• an open-source, Java tool
• provides extensible architecture to create
  customized knowledge-based applications.
• Developed by Stanford University, USA

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Music and Audio Ontology (Classes)

• Provides information on
• Album
• Artist
• AudioFile
• AudioFileType
• Encoding
• Instrument
• Key
• Live
• Note
• Official
• Resource
• Rhythm
• Signal
• Soundtrack
• Spokenword
• Track
• Type

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Music and Audio Ontology (Data Type and Object
Properties)

• Provides information on
• arranged
• covered
• djmix_of
• duration
• image
• linkto_wikipedia
• medley_of
• member_of
• performed
• similar_to
• trackNum
• translation_of

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Music and Audio Ontology (General structure)
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JBuilder 2006

• The system is written in JBuilder 2006. JBuilder
  is and IDE (Integrated Development Tools) for
  developing new application, web etc software
  based on Java Language. All of the packages and
  classes for using OWL and running queries are
  imported into this IDE.

22
Jena 2.3 Ontology API

• Jena 2.3 Ontology API is a Java framework for
  building Semantic Web applications. Use RDF
  models in your Java applications with the Jena
  Semantic Web Framework.

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RDQL

• RDQL is a query language for RDF in Jena models.
  The idea is to provide a data-oriented query
  model so that there is a more declarative
  approach to complement the fine-grained,
  procedural Jena API.
• It is "data-oriented" in that it only queries the
  information held in the models there is no
  inference being done. Of course, the Jena model
  may be 'smart' in that it provides the impression
  that certain triples exist by creating them
  on-demand.

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Java Server Pages

• JavaServer Pages (JSP) technology allows web
  developers and designers to rapidly develop and
  easily maintain information-rich, dynamic web
  pages that leverage existing business systems. As
  part of the Java family, the JSP technology
  enables rapid development of web-based
  applications that are platform independent.
• In theory, JavaServer Pages technology separates
  the user interface from content generation,
  enabling designers to change the overall page
  layout without altering the underlying dynamic
  content.

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Algernon

• Algernon is a rule-based inference system,
  implemented in Java and interfaced with Protégé
  and it is developed by Micheal Hewett. It allows
  executing queries within the Protégé GUI.
• It performs forward and backward rule-based
  processing of knowledge bases, and efficiently
  stores and retrieves information in ontologies
  and knowledge bases. It has an ability to call
  external Java methods and an internal LISP
  subsystem.

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Tomcat

• Tomcat is the official reference implementation
  of the Java Servlet 2.2 and JavaServer Pages 1.1
  technologies. Developed under the Apache license
  in an open and participatory environment, it is
  intended to be a collaboration of the
  best-of-breed developers from around the world.
• Tomcat is a servlet container and JavaServer
  Pages(tm) implementation. It may be used stand
  alone, or in conjunction with several popular web
  servers
• Apache, version 1.3 or later
• Microsoft Internet Information Server, version
  4.0 or later
• Microsoft Personal Web Server, version 4.0 or
  later
• Netscape Enterprise Server, version 3.0 or later

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Microsoft SQL Server

• Microsoft SQL Server 2005 is a database and data
  analysis platform for large-scale online
  transaction processing (OLTP), data warehousing,
  and e-commerce applications.
• The Database Engine is the core service for
  storing, processing, and securing data. The
  Database Engine provides controlled access and
  rapid transaction processing to meet the
  requirements of the most demanding data consuming
  applications within your enterprise. The Database
  Engine also provides rich support for sustaining
  high availability.

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Music and Audio system use case, implementation
and execution
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Music and Audio system use case, implementation
and execution

• Execution of program in Browser

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Music and Audio system use case, implementation
and execution

• Execution of program in Browser

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Music and Audio system use case, implementation
and execution

• Running queries in Algernon
• 1) Find all artist names that their age45,
  nationality"Turkish", country "Turkey", and
  numberOfAlbums50

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Music and Audio system use case, implementation
and execution

• Running queries in Algernon
• 2) Find all WebSites Address for artists

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Music and Audio system use case, implementation
and execution

• Running queries in Algernon
• 3) Find all album names which are not
  linkto_wikipedia site

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Music and Audio system use case, implementation
and execution

• Running queries in SQL Server 2005
• 1) Find all artist names that their age45,
  nationality"Turkish", country "Turkey", and
  numberOfAlbums50

35
Music and Audio system use case, implementation
and execution

• Running queries in SQL Server 2005
• 2) Find all WebSites Address for artists

36
Music and Audio system use case, implementation
and execution

• Running queries in Algernon
• 3) Find all album names which are not
  linkto_wikipedia site

37
Music and Audio system use case, implementation
and execution

• Some source codes for classes in Music and Audio
  ontology

38
Comparison of Semantic Search and Regular Search

• In relational database management systems
  (RDBMS), there is no class relationship. It means
  sub classes cannot inherit all properties from
  their super classes and also there is no
  instantiation.
• Extra work will be required to define class
  relations and all properties separately.
• In semantic databases there are domains and
  ranges which can apply for each property but in
  an RDBMS it is impossible.
• There is no object property for these systems.
• In relational database Vastly coding
  implementation for returning data is need.
• There is no way for using and importing
  ontologies, and for returning objects data types.

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Comparison of Semantic Search and Regular Search

• By using OWL, the Music Ontology gains a powerful
  extensibility mechanism, allowing
  Music-Ontology-based descriptions to be mixed
  with claims made in any other OWL or RDF
  vocabularies. I can re-use other ontologies to
  describe different relationship between classes.
• OWL provides the Music Ontology with a way to mix
  together different descriptive vocabularies in a
  consistent way. Vocabularies can be created by
  different communities and groups as appropriate
  and mixed together as required, without needing
  any centralized agreement.
• On the other hand, many existing SW tools are
  still file-oriented and also mine. This limits
  the size of ontologies that can be processed, as
  the whole ontology must be read into main memory.
  Further, the multi-user support and transactions
  are typically not present, so the whole
  infrastructure realizing these requirements must
  be created from scratch but my project is web
  based and it is able support multi-user
  transactions.

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Conclusion

• The Music Ontology is an application of the
  Ontology Web Language (OWL) because the subject
  area are music artists, albums and tracks etc
  -- has so many competing requirements that a
  standalone format would not capture them or would
  lead to trying to describe these requirements in
  a number of incompatible formats. By using OWL,
  the Music Ontology gains a powerful extensibility
  mechanism, allowing Music-Ontology-based
  descriptions to be mixed with claims made in any
  other OWL vocabulary.
• OWL provides the Music Ontology with a way to mix
  together different descriptive vocabularies in a
  consistent way. Vocabularies can be created by
  different communities and groups as appropriate
  and mixed together as required, without needing
  any centralized agreement.
• In summary then, OWL is self-documenting in ways
  which enable the creation and combination of
  vocabularies in a devolved manner. This is
  particularly important for an ontology which
  describes communities, since online communities
  connect into many other domains of interest,
  which it would be impossible (as well as
  suboptimal) for a single group to describe
  adequately in non-geological time.

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References

• 1- http//purl.org/
• 2- Multimedia Content and the Semantic Web
  METHODS, STANDARDS AND TOOLS Edited by
  Giorgos Stamou and Stefanos Kollias Both of
  National Technical University of Athens, Greece.
  John Wiley Sons Ltd.
• 3- T. Berners-Lee, J. Hendler, O. Lassila, The
  Semantic Web. Scientific American, 284(5),
  3443, 2001.
• 4- O. Lassila, R.R. Swick, Resource Description
  Framework (RDF) Model and Syntax Specification,
  http//www.w3.org/TR/REC-rdf-syntax/.
• 5- D. Brickley, R.V. Guha, RDF Vocabulary
  Description Language 1.0 RDF Schema,
  http//www.w3.org/TR/rdfschema/.
• 6- M. Kifer, G. Lausen, J. Wu, Logical
  foundations of object-oriented and frame-based
  languages. Journal of the ACM, 42, 741843, 1995.
• 7- D. Fensel, I. Horrocks, F. van Harmelen, S.
  Decker, M. Erdmann, M. Klein, OIL in a nutshell.
  In Knowledge Acquisition, Modeling, and
  Management, Proceedings of the European
  Knowledge Acquisition Conference (EKAW-2000),
  October, pp. 116. Springer-Verlag, Berlin,
  2000.
• 8- P.F. Patel-Schneider, P. Hayes, I.
  Horrocks, F. van Harmelen, Web Ontology Language
  (OWL) Abstract Syntax and Semantics,
  http//www.w3.org/TR/owl-semantics/, November
  2002.
• 9- C. Davis, S. Jajodia, P. Ng, R. Yeh (eds),
  Entity-Relationship Approach to Software
  Engineering Proceedings of the 3rd International
  Conference on Entity-Relationship Approach,
  Anahein, CA, 57, October. North- Holland,
  Amsterdam, 1983.
• 10- M. Fowler, K. Scott, UML Distilled A Brief
  Guide to the Standard Object Modeling Language,
  2nd edn. Addison-Wesley, Reading, MA, 1999.

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References (Cont1)

• 11- A. Evans, A. Clark, Foundations of the
  Unified Modeling Language. Springer-Verlag,
  Berlin, 1998.
• 12- http//pingthesemanticweb.com/ontology/mo/s
  ec-externalsec- external
• 13- http//www.w3.org/2001/sw/, no pagination,
  verified on Oct 17, 2002.
• 14- http//www.w3.org/2001/sw/, no pagination,
  verified on July 1st, 2003.
• 15- Tim Berners-Lee, James Hendler, and Ora
  Lassila. The semantic web. Scientific American,
  2001(5), 2001.
• 16- Ubbo Visser Intelligent Information
  Integration for the Semantic Web Springer.
• 17- Semantic Web Technologies Trends and
  Research in Ontology-based Systems John Davies
  BT, UK Rudi Studer University of Karlsruhe,
  Germany Paul Warren BT, UK John Wiley Sons
  Ltd.
• 18- http//www.w3.org/2004/OWL/
• 19- http//www.w3.org/RDF/
• 20- The Semantic Web A Guide to the Future of
  XML, Web Services, and Knowledge Management
  Michael C. Daconta Leo J. Obrst Kevin T. Smith
• 21- I. Horrocks, DAMLOIL A Description Logic
  for the Semantic Web. Bulletin of the IEEE
  Computer Society Technical Committee on Data
  Engineering, IEEE, Vol. 25, No. 1, pp. 4-9,
  2002.
• 22- Protégé overview, URL http//protege.stanfo
  rd.edu, last visited June 2006

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References (Cont2)

• 23- N. F. Noy, M. Sintek, S. Decker, M.
  Crubezy, R. W. Fergerson, M. A. Musen.
  Creating Semantic Web Contents with
  Protege-2000, IEEE Intelligent Systems
  16(2)60-71, 2001
• 24- J. Gennari, M. A. Musen, R. W. Fergerson,
  W. E. Grosso, M. Crubézy, H. Eriksson, N. F.
  Noy, S. W. Tu, The Evolution of Protégé An
  Environment for Knowledge-Based Systems
  Development, 2002, URL http//smi-web.stanford.
  edu/pubs/SMI_Reports/SMI-2002-0943.pdf
• 25- Erhan Gayde Thesis Eastern Mediterranean
  University September 2006, Gazimagusa, North
  Cyprus
• 26- http//www.Borlan.com/
• 27- Jena A Semantic Web Framework for Java,
  URL
• http//jena.sourceforge.net/.
• 28- HP Labs Semantic Web Research, URL
• http//www.hpl.hp.com/semweb/.
• 29- http//jena.sourceforge.net/tutorial/RDQL/
• 30- Borland JBuilder 2006 Documentation Files.
• 31- http//algernon-j.sourceforge.net/
• 32- http//www.hewettresearch.com/mikehewett.htm
  l
• 33- http//jatha.sourceforge.net/
• 34- http//jakarta.apache.org/site/binindex.html
  
• 35- Microsoft SQL Server 2005 Documentation

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Thank you

• Any Questions?