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    Semantic Web Technologies

    semantic web.jpg

     The semantic web is not an artificial intelligence, but it can use artificial intelligence technologies.

    technology. This technology reveals smart data that the machine can understand. Machine
    The concept of intelligent data that he can understand is that the machine's ability to solve a well -defined problem by doing well -defined operations on the current well -defined data
    expresses. Instead of asking the machines to understand the language of people, people
    More effort to identify more regularly
    Asking them to show allows the creation of smart data more easily (Maedche and Staab,
    2001).
    Important to make up semantic web technologies
    The elements are expressed schematically in Figure 2. To the system that contains these technologies
    It is called semantic web technologies. Semantics
    Web technologies constitute the structure called Web 2.0 which is put into practice today.
    XML
    XOL SHOE OML RDF (S)
    Oil
    Drop +
    OIL OWL
    Figure 2‑8 using semantic web technology
    search system
    Figure 2‑8 shows the hierarchy of semantic web technologies. This technology
    All steps are interconnected.
    Except for XML, all of them are class model
    available. To briefly mention these technologies; Rdf ie resource description
    Resource Description Framework)
    The basic data model for the semantic web. This
    Model, RDF/ with different format formats
    XML is the basis for N-Triples, N3 and Turtle. The heart of the semantic web
    Ontologies. So too
    OWL, which is the language of web ontology, definitions
    to establish relationships between data and data
    It is used (Çankaya, 2007).
    The Semantic Web is a development like science, just like science
    It seems to be formed at the end of the process. Well,
    In the first place, a perfect and fully functioning
    Starting with a simple and robust system that performs basic functions instead of making a system, then this system is more complex.
    It is aimed to restore the structure. Firstly
    HTML, a form for the demonstration of information
    It was produced and the HTTP protocol was written for the transfer of this information. Then, on top of them, the structural knowledge and meaning of this information
    XML and RDF languages have been added to add (Berners-Lee et al., 2001).
    In the last stage, the marking languages that make up ontology definitions (OIL, DAML+OIL,
    OWL). System by adding new features to the main nuclear system at each stage
    is expanded. However, in advance
    Just like the last added system in each added system
    as it will continue to develop. For example
    While working on the OWL language at the moment,
    RDF language also continues.
    Even OWL "Candidate Recommendation"
    By the way; RDF is still "Working
    Draft ”stage. So in the development process
    it is more reversed. As a result, Figure 2‑9
    As can be seen, a period of approximately 20 years in order to implement the Semantic Web
    It is estimated that it should pass.

    Figure 2‑9 Semantic Web in the years of the schedule of components within the body.
    What is ontology?
    Ontology is the key technology to be used to perform the semantic web.
    The term ontology as a science of being in philosophy
    defined. Ontology of the twentieth century
    At the end, it was used extensively in the field of artificial intelligence. Ontology in a certain area
    sharing and reuse of information
    Providing “conceptualizations formal and
    defined as a clear definition ”and
    used. Recently ontologies
    Intelligent Systems, Electronic Commerce,
    on natural language processing and information management
    is becoming widespread.
    Ontology in computer science
    The definition of accepted Gruber (1993);
    "Clearness of conceptualization"
    as expressed in the form of. Conceptualization, abstract model in a certain design stage
    means creation. Maedche and Staab
    (2001).
    clearly defined in a way that does not leave
    must.
    Another definition of ontology given in Maedche and Staab (2001) is what ontology
    explains that it should include and what models containing should be considered ontology.
    The difference of this definition from others; The word here
    It is the web ontologies of ontologies.
    Each term is identified and the terms found in ontology are finite. These;
    The meanings of terms, between terms
    relationships, synonyms between terms
    And it includes sequential relationships. In conclusion,
    At least in order to have an ontology of a set of concepts, at least have the following qualifications.
    must be:
    • Terim repertoire must be finite and expandable,
    • Relations between classes and terms
    that it is clearly understood by the factors,
    • OWL's use of the class structure.
    In addition to three basic qualifications, in order to increase the expression power of ontologies and get qualified inquiry results,
    • Don't contain samples,
    • Having class qualities,
    • Value comparison criteria,
    • Logical comparison criteria,
    The properties can also be added to the ontology qualities given above. With the inclusion of these logical structures; ontologies, complex
    can model the information and on this information
    They come to a level that can produce results.
    Web ontology language
    Web Ontology Language (OWL), ontologies
    A used to define and diversify
    Language (Wikipedia, 2007). OWL, not only showing the content of information to people, it
    to be processed by computers next to it
    designed to. OWL, XML, RDF and
    Supported by RDF Schema (RDF-S)
    Web content is better by computers
    aims to ensure that it can be interpreted. Languages like OWL, OIL and Daml+Oil
    It is based and now by the W3C institution
    It is a recommended language. OWL, Drop+OIL

    Web is a research -based version of ontology (Wikipedia, 2007).
    Figure 2‑10 The schematic structure of OWL languages
    An example of the use of the OWL language as RDF is given in Figure 2‑10.
    Connection Between Terms RDF syntax
    is done with. SYLING RULES INFORMATION
    Designed to make sense. This is
    We can explain it with an example. A person
    Apple in the sentence "I use Apple"
    To define the word as RDF
    Apple word; manufacturer, type, model,
    When it defines the operating system, it implies meaning on the word Apple. Computer Apple
    When he reads the word, he will realize that it is a defined computer. This
    Figure 2‑10 is shown with the language of ontology.
    For a single purpose, the information defined by OWL
    unthinkable. This information can be defined or expanded by other ontologies.
    Not misinterpretation of OWL documents and processing by computers
    There is a need for a proper syntax.
    Terminology to be used in OWL documents
    It is the extended version of RDF files (OWL,
    2007).
    OWL has three sub-languages: OWL Lite, OWL DL and OWL full as shown in Figure 2-11.
    These three languages are used by users
    They are specially designed (OWL,
    2007). The sub -languages of the OWL language have been designed to cover each other. Figure 2‑11
    This structure is shown.
    Figure 2‑11 Language Structure that constitutes OWL language
    OWL FULL: RDF and RDF (S) uses all components. All conveniences provided by RDF
    provides. However, it does not support computability.
    For example, the class described in the RDF can express a community as well as defining an individual
    It may also be a class. OWL Full is more important than the calculation information of the definition information
    can be used in cases. OWL FULL
    In some cases, automatic logic can be impossible. OWL full language with RDF
    fully compatible. RDF documents
    Its structure is also OWL Full Documents. One of the disadvantages OWL Full Structures
    is not fully determined. Therefore, concepts
    it cannot make a full and effective logic between it.
    For example, Ahmet Bey get a printer from the techno market that sells a computer material.
    Logically, Ahmet Bey's printer like cartridge, toner or ribon for the printer in the future
    can buy one of the consumables
    Potential customer can be concluded. The type of printer he bought is certain
    Since it is not, the consumables it will use for the printer
    The material can be very diverse. The interest of interest in the logical expression created in this way
    As a result of its weakness, the company can decide which consumables to invest in the material
    There are multiple options.
    As a result, such logical inferences are the only
    It does not create an effective logic in achieving a result.

    OWL DL: It is a sub -language of OWL Full. OWL
    and used by adding constraints to RDF -forming structures. These constraints define logic
    Provides connection. OWL DL provides convenience in defining the meanings of terms. Reason by making automatic calculations possible
    Make it easier to execute. For example, Ahmet Bey
    Let's assume that you buy a laser printer from the technology market. If we make logical execution; If Ahmet Bey bought a laser printer
    For the future for the printer
    will take a toner. A logically laser printer, a person with a laser printer should get a toner for the laser printer.
    logic is being carried out.
    OWL Lite: uses a single part of the OWL language. Uses the restrictions of OWL DL. OWL
    Lite can only be defined as the upper class. Decision structures are used in the upper classes. Between classes
    There are equality and subclass relations. OWL Lite
    It sends two values by evaluating the logical consequences. These values are 0 and 1. Especially
    In case of signs; If I have a interest
    1 is accepted. Other cases are considered 0.
    For example, the processor of a computer,
    Motherboard, RAM memory server
    If it has a feature, it sends 1 value, and in other cases 0 value is sent.
    How to create ontology?
    To create ontology, primarily an area
    should be determined. There should be a finite number of terms on this area. The classes of these terms and
    sub -classes should be determined. Individuals of classes
    should be defined. Class definitions may be in a reference class. But the lower classes are reference
    cannot be a class. Sub -class definitions usually
    Used to identify more private individuals.
    For example, the class when creating information ontology
    as a sub -class as a sub -class object -oriented programming languages terms.
    We can write (object, class, function).
    Figure 2‑12 Class structure representation
    A very important definition in creating ontology is to indicate the characteristics of the classes. Each class has its own specific feature. While making characteristics to classes
    Data types and object properties can be specified. Fig.
    is determined. This upper class is called domain.
    The connection address is called range. In addition, the concept of domain is between programming types
    Used to control marlling. Ranking
    The concept determines the connection points of the term. At the same time the concept of domain from classes
    It can be used in information inference. Your every class
    There is a domain area. This Domain is a URI
    can be the address. Semantic in creating ontology
    Bonds are reflected in the classes. This reflection belonging
    performs the action. The individual specifies his belonging to the class only with an action. These actions
    with ownership suffix.
    Simply exemplary an example ontology scheme
    And the creation of ontology language:
    Theoretical to create an ontology so far
    as we explained. We will try to show how to create an ontology. The area where we will create an example ontology
    Informatics terms. After the field is determined
    The classes of the terms of informatics and these classes
    Let's group the terms according to their interests. We
    As class:
    Network Terms
    (DNS, IP, RJ45,…)
    • Software Terms
    (Object, function, condition,…)
    • Terms of the frost
    (Network Card, Processor, Memory,…)
    Let's define three classes, including. After determining these definitions schematically
    It is time to use ontology creation tools
    income. Protégé as a means of creating ontology
    3.3.1 version can be used. Protégé program,
    It is distributed free of charge. After determining the classes of terms; if necessary
    We need to determine the subclasses of classes.
    For example, the subclasses of hardware terms
    MIB TERMS
    (Cape memory, CPU, RAM memory,…)
    • Memory Terms (Static Memory,
    Dynamic memory, swap memory,…)
    • I/O Terms
    (Printer, browser, monitor,…)
    We can divide it into lower classes.
    After the lower classes are defined, the terms
    Features and relationships are determined. Later
    The actions of these relationships are defined. For example;
    “Processor uses memory. The memory of the graphics card
    has. Uses C ++ memory. Game software
    Dynamic memory and the memory of the graphics card
    We can make connections on the term memory term as a term. Once the definitions and relationships are determined, ontology is created using ontology language.
    starts. Classes as shown in Figure 2‑3
    and sub -classes were determined. Subclasses
    Types and connections of terms as code
    given.
    Connections of Terms In the code
    Is written in the form of URI. Connection shape
    We can examine it by looking at the sample code (Code: 2.1).
    Figure 2‑13 Creation Classes and Sub -classes
    Code: 2-1
    <? xml version = ”1.0”?>
    <RDF: RDF XML: Base = ”http://ww.owlontologies.com/unnamed.
    OWL ”xmlns =” http: // www.
    Owl-ontologies.com/unnamed.
    OWL#”XMLNS: OWL =” http: //
    www.w3.org/2002/07/owl# ”
    XMLNS: RDF = ”http: // www.
    w3.org/1999/02/22-rdf-syntaxns# ”XMLNS: RDFS =” http: // www.
    w3.org/2000/01/RDF-schema# "
    xmlns: xsd = ”http: //
    www.w3.org/2001/xmlschema#”>
    <OWL: Ontology RDF: About = ””/>
    <OWL: Class
    RDF: ID = ”Hardimathers”/>
    <OWL: Class
    RDF: ID = ”memory for”>
    <rdfs: subclassof
    “RDF: Resource
    = ”#Hardware
    </uwl: class>
    <OWL: Class
    RDF: ID = ”Networkterimleri”/>
    <OWL: Class
    RDF: ID = ”Databasers”>
    <rdfs: subclassof>
    <OWL: Class
    RDF: ID = ”softwareterimations”/>
    </dfs: subclassof>
    </uwl: class>
    <OWL: Class
    RDF: ID = ”Algorithmaterials”>
    <rdfs: subclassof
    rdf: resource = ”#software
    Terms ”/>
    </uwl: class>
    <Webterims RDF: ID = ”ipdns”/>
    <Webterims
    RDF: ID = ”ipipx-SPX”/>
    <database
    RDF: ID = ”Join”/>
    <database
    RDF: ID = ”innergoin”/>
    <database
    RDF: ID = ”Function”/>
    <rdf: description
    RDF: ID = ”Knowledge_
    Instance_6 ”>
    <RDF: Type> CLS (: Instanceannotionion,
    FRAMEID (0: 1020 0))
    <programmatic
    RDF: ID = ”Java”/>
    <database
    RDF: ID = ”Leftjoin”/>
    <database
    RDF: ID = ”update”/>
    <Algorithmaterials
    RDF: ID = ”WHile”/>
    <programmatic
    RDF: ID = ”C”/>
    <programmatic
    RDF: ID = ”OWL”/>
    </ rdf: rdf>
    Code: When we examine 2.1, Parenthesis 1 XML
    Name Space Definitions, 2.
    Place where parenthesis classes are defined, 3rd parenthesis
    where lower classes are defined. 4. It can be examined as the place where parentheses are defined.
    Conclusion
    Ontologies work conceptually with the logic of algorithm. From the structure of the algorithm
    Unlike the connection between objects
    It is determined by action. These actions are in the form of terms in ontology. In addition, the sentence that makes the action; Subject, object
    and in the form of predicate. For example,
    Cats like fish. Old people are usually a
    He has a cat. So old people buy fish for their cats.Nowadays, ontology creation is usually done by computer software developers.
    The creation of ontology shortens the definition and results of the works to be done. In the structural transformations of institutions with the spread of ontology in the future,
    In task definitions and business shares
    The decision -making mechanisms of institutions are more
    It is expected to work fast.
    According to Cimiano (2006), the most popular ontologies today, Wordnet ontology, Wiki ontology, Eclips ontology, Medical Ontology,
    Gene ontology. These ontologies are
    Common feature; to be accepted as standard
    and in accordance with open source code principles
    distributed.

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