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  • Latar belakang, Pengenalan ERPGame, Metode Penelitian, WDAG, Semantik Web Service, Agent WS (Multi-Criteria Negotiation)
  • Semantik Web: easier to find, share, agregate and extend informationSemantik WS: easier to discover, use/invoke, compose and monitor.
  • Menggunakan metadata semantik (faktor kunci: representasi metadata)Ceritakan tentang penelitian sebelumnyaSalah satu yang paling banyak digunakan adalah ontology (OWL)Shg, Nyambung ke slide berikutnya tentang wDAG

Transcript

  • 1. Proposal Thesis
    Agent-Based Semantic Web Service Using Weighted Directed Acyclic Graph On ERP Game Simulation
    Oleh:
    ANANG KUNAEFI (5110 201 008)
  • 2. 2
    Agenda
    Backgrounds
    Semantic Web Service
    Weighted Directed Acyclic Graph (wDAG)
    ERP Game Simulation
    Research Methodology
    Summary
  • 3. 3
    Latar Belakang
    The semantic web technology has been widely used for many fields like search engine, content-based application, e-commerce, e-learning, and many others.
    On the other hand, web service has been widely accepted in the field of business to process daily operation.
    The needs of semantic web technology to be implemented in the fields of web services in order to promote dynamically integrated application environment.
    Semantic Web & Semantic WS
  • 4. Semantic Web dan Semantic WS
    4
    Semantics
    Semantic Web
    Easier to find, share, aggregate, and extend of content.
    Semantic Web Service
    Easier to discover, invoke, compose, and monitor application.
    Reference: www.w3c.org/2004/Talks/0612-sb-wsswapps/slide3-0.html
    Accessed on August 13, 2011
    Semantik WS
    4
  • 5. Semantik Web Service
    5
    Request
    Service Repository
    Matchmaking with all WS
    Discoverer
    Data Mediator
    uses
    uses
    Composer
    If: directly usable
    If: composition needed
    Communication
    Conformance
    Process Mediator
    Semantic WS can do the following automatically
    Service Discovery
    Service Composition
    Service Enactment & Monitoring
    Service Negotiation & Contracting
    uses
    If: directly compatible
    Executor
    If: succesful
    else: try other WS
    Reference: University of Innsbruck, Austria (www.uibk.ac.at)
    Lecture Material, accessed on August 14, 2011
  • 6. 6
    Semantic Web Service Metadata
    Key factor of semantic web service is how to represent the metadata of web service (Fensel, 2007).
    Several approaches have been proposed:
    OWL-S
    IRS-III
    WSMO
    METADATA
    WEB SERVICE
    OWL-S
  • 7. Ontology Web Language for Services (OWL-S)
    One of the most widely used to represent web service metadata is OWL-S.
    OWL-S divide service information into :
    Service Profile
    Service Grounding
    Service Model
    Tools for using OWL-S areProtégé Editor, OWL-S matcher.
    7
    Sumber: http://www.w3.org/Submission/OWL-S
    diakses pada 13 Agustus 2011
    Keterbatasan OWL-S
  • 8. Limitation ofOWL-S
    Usinglogic-based reasoner in the matchmaking process because OWL-S defines “is a” relationship between objects. (Li dan Horrock, 2003).
    Therefore, in the discovery process, we can’t make preference to a single atribute because all the atribut have the same level of preference.
    8
    wDAG
  • 9. Weighted Directed Acyclic Graph (wDAG)
    An arc-labeled, arc-weighted DAG is constructed from a 6-tuple (V, E, LV, LE, LW, r) of a set of nodes V, a set of arcs E, a set of nodelabels LV, and a set of arc labels LE, a set of arc weights LW = [0,1], and one element r where r ϵV.
    wDAG similarity computation is more eficient then weighted tree similarity because wDAG structure is more efficient.
    This schema can also be used by user/consumer of WS refine the discovery of services by making preferences for some atributes by providing greater weight than other atributes.
    9
    ERPGame
  • 10. ERPGame
    Enterprise Resource Planning (ERP) Game is learning-by-doing-based games to help the players understanding the concept of ERP (Enterprise Resource Planning).
    10
    ERPGame Concept
  • 11. Konsep ERPGame (1)
    ERPGame is a unique business simulation technology that enables the simulation of near-real-life ERP business context of corporate information system.
    It provides the simulation of a market for buyers so that the participants playing the game have a reasonable market that responds just like one in the real world.
    It automates some of the business functions that are more administrative to make the game a little easier to play so the participants focus on the decision making processes.
    It provides simulation of the passing time. It compresses time into short but still create the appearance of time evolving so that the impact of the decisions taken vertime can be evaluated.
    11
    ERPGame Concept 2
  • 12. ERPGame Concept (2)
    ERPGame provides these 3 functions so the game can be played:
    Provides market for buyers that respond just like in the real world.
    Provides some business process automation.
    Provides time simulation.
    12
    ERPGame
    Web service-base ERP System
    ERP Database
    ERPGame run on top of
    Web service-based ERP
    ERPGame dan Web Service
  • 13. WS
    Pembeli/Pasar Virtual
    ERPGame dan Semantik Web Service
    Dalam 1 siklus permainan ERPGame diikuti oleh 2 atau lebih player.
    Tiap player harus menjual produk masing-masing
    Pembeli/Pasar virtual mencari dan memilih service yang paling menguntungkan.
    13
    Team A
    (role as company A)
    Mencari service yang sesuai dengan harga yang paling menguntungkan
    (automatis)
    WS 1
    Sell Product A, PriceX
    WS 2
    Sell Product A, PriceY
    Menggunakan
    Semantik Web Service
    Berbasis agen
    Team B
    (role as company B)
    Metode Penelitian
  • 14. Metode Penelitian
    14
    Service
    Service
    Langkah-langkah dalam pengembangan metode, meliputi:
    WSDL-S Mining
    Pembangkitan wDAG
    Pembuatan wDAG Registry
    Perhitungan wDAG Similarity
    Multi-criteria Negotiation
    WSDL-S Mining
    WSDL-S Mining
    (Elgazzar et al., 2010)
    Pembangkitan WDAG
    Pembangkitan WDAG
    (Jin, 2006)
    wDAG
    Registry
    (Nugroho & Sarno, 2011)
    WDAG
    Similarity
    (Jin, 2006)
    (Mei, 2006) dan
    (Rao, 2004)
    Multi-criteria
    Negotiation
    Service Agreement
    WSDL-S Mining
  • 15. WSDL-S Mining
    Ekstraksi fitur-fitur dari web service, yaitu:
    Service Content
    Service types
    Messages
    Ports
    Service Name
    Proses ekstraksi terdiri dari
    Parsing WSDL
    Tag Removal
    Stemming
    Function word removal
    Content word recognition
    15
    • Pada penelitian ini akan digunakan WSDL-S sebagai pengganti WSDL.
    • 16. WSDL-S adalah WSDL ditambah anotasi semantik.
    Pembangkitan wDAG
    Referensi: Elgazzar et al., 2010
  • 17. Pembangkitan wDAG
    16
    Service
    Service
    Profile
    Service
    Grounding
    Service
    Model
    Profile
    Profile
    Service
    Desc
    Service
    Desc
    Grounding
    Category
    Desc
    Category
    Desc
    Process
    Operation
    Desc
    Operation
    Desc
    Desc Text
    Desc Text
    Input Type
    Precondition
    Type
    Category
    Category
    Desc Text
    Output Type
    Operation
    Explaination
    Text
    WSDL
    Operation
    Effect
    Taxonomy
    Code
    CatName
    Operation
    Name
    Type
    Text
    Operation
    Explaination
    Taxonomy
    URI
    Port Type
    Text
    Reference
    Text
    Text
    Operation
    Name
    Reference
    Text
    Reference
    Reference
    Text
    Text
    Reference
    Text
    Hasil dari ekstraksi fitur WSDL-S selanjutnya dimasukkan dalam skema wDAG
    ReferenceDesc
    URI
    Domainmodel
    Text
    Text
    wDAG Similarity
    Referensi: Jin et al., 2006
  • 18. wDAG Similarity
    17
    Service Operation
    Service Desc
    Service Operation
    Service Desc
    0.5
    0.5
    0.5
    0.5
    getInvoice
    Get Invoice By Distributor
    getInvoice
    Get Invoice By Factory
    Perhitungan kemiripan dari Jin, akan divariasi dengan perhitungan cosine similarity dan wordnet.
    “Get Invoice By Distributor” dan “Get Invoice By Factory” dengan cosine similarity menghasilkan similarity = 0.336 (bukan 0).
    Dengan cosine sim “Distributor “ dan “Factory” dianggap memiliki kemiripan sama dengan nol (0). Agar lebih akurat digunakan wordnet untuk mengetahui jarak kemiripan antara kata-kata tersebut. Dengan wordnet ternyata antara “Distributor” dan “Factory” kemiripannya = 0.462.
    Sehingga gabungan antara cosine dan wordnet menghasilkan similarity yang lebih baik yaitu 0.377.
    Multi-criteria negotiation
  • 19. Multi-criteria Negotiation
    18
    Agent
    Behaviour Manager
    Rule Engine
    Rule Set
    Sensor
    Actuator
    Web Services
    Setelah semantik web service menemukan web service yang dicari dengan wDAG Sim, selanjutnya agent negosiator sebagai perantara buyer-seller melakukan negosiasi, untuk menemukan service yang paling menguntungkan.
    Negosiasi dilakukan atas 3 atribut, yaitu:
    Harga produk
    Lokasi
    Kecepatan layanan
    Uji coba
    Referensi: Mei et al., 2006
  • 20. Uji coba
    Uji coba terhadap framework yang dibangun meliputi 2 hal, yaitu:
    Pengujian discovery of service menggunakan precision, recall dan F-Measure (Baeza-Yates, 1999) serta ROC (Receiver Operating Characteristic) Curve.
    Pengujianapakah service yang terpilihmelaluiprosesmulti-criteria negotiationbenar-benar service yang terbaikdan paling menguntungkan.
    19
  • 21. Penutup
    Tujuan dari penelitian ini adalah untukmendapatkansebuahmetodesemantik web service berbasisagenmenggunakan Weighted Directed Acyclic Graph (wDAG) dalamskema buyer-seller dilingkunganbisnis yang kompetitifpadaERPGame.
    Manfaat penelitian iniadalahuntukmemudahkanconsumer web service dalammenemukan web service yang paling sesuaidengankebutuhanmerekasecaraotomatisbaikdalamkonteksindividumaupunkonteksbisnisdalamperusahaan.
    Kontribusi dari penelitian ini adalah:
    menyediakanskema metadata semantik web service menggunakanweighted directed acyclic graph (wDAG) dengantingkatpenghitungankemiripan yang lebihbaik
    menyediakan framework untuksemantik web service dalamlingkungan yang kompetitifdenganmulti-criteria negotiationmenggunakan agent web service
    20
  • 22. Terima Kasih