1 cs 566 web semantics e-commerce and semantic web professor antoniou grigoris june 2003 antonis...

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CS 566Web Semantics

E-Commerce and Semantic Web

ProfessorAntoniou Grigoris

June 2003

Antonis [email protected]

Athina [email protected]

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Introduction

The growth of a wide range of e-commerce services is contributing to the increasing international trading of products and services

The ability to find, interrogate and exchange knowledge is fundamental for Business-to-Business (B2B) and Business-to-Customer (B2C) e-commerce

Semantic Web brings structure to the content of Web pages Semantic Web is extension of the current Web, in which information

is given a well-defined meaning It will be able to support automated electronic services using

semantics-based descriptions Ontologies and metadata are becoming increasingly prevalent and

important in a wide range of e-commerce applications

RDF is the technical foundation of the Semantic Web which provides a generic core data model

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When Semantic Web Approaches E-Commerce

Semantic Web will enable automated agents to describe and carry out more intelligent tasks on behalf of the user

Tim Berners-Lee, the inventor of the WWW, has conceived a five-layer architecture for Semantic Web: The syntax layer – XML allows to markup arbitrary content by

means of nested, attributed elements The data layer – RDF allows the encoding, exchange and

reuse of structured metadata. Contrary to XML, RDF allows assigning global identifiers to resources and allows referring and extending statements made in other documents

The ontology layer describe structurally heterogeneous and distributed information sources of interest

The logic layer consists of rules that enable inferences The proof layer allows the explanation of given answers

generated by automated agents. This will require the translation of agents internal reasoning mechanisms into some unifying proof representation language.

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Ontologies

While e-service approaches to e-commerce is to become widespread, standarisation of ontologies, message content and message protocols will be necessary

Because of the great XML-like modelling languages release, the challenge is to create small standards for communities to describe information with meaning

Ontologies can be seen as metadata that explicitly represent semantics of data in machine-processable way

Ontology-based reasoning services help people and computers to access the information they need, and effectively communicate with each other

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Semantic E-Commerce Lifecycle (1/10) Lifecycle Stages:

Matchmaking: A trader locates other traders that it could potentially do business with.

This is done by some traders placing advertisements, and others making queries over these advertisements

Negotiation: The trader enters into negotiation with one or more of these potential business partners, to see if they can agree mutually acceptable terms of business.

This is done through an interchange of negotiation proposals describing constraints on an acceptable deal. The outcome of this is an agreement.

Contract Formation: The agreement is transformed into a legally binding contract

Contract Fulfilment: The parties carry out the agreed transaction, within the parameters specified in the contract

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Semantic E-Commerce Lifecycle (2/10) Matchmaking

Matchmaking is the process whereby potential trading partners become aware of each other’s existence

Provides an associated partially specified service description that defines the set of possible services the provider can offer which are of the interest to the buyers

Despite different architectures and communication protocols: we can identify clear roles which are common to all of them. we have a repository of information about services or service

requirements, which is maintained by the repository host. agents adopting advertiser role are willing to advertise descriptions of

services in the repository. They may be buyers, advertising a service request, or may be marketplaces offering environments where such services can be traded.

agents adopting the seeker role similarly wish to locate appropriate advertisers. Seekers can query a repository, via the repository host, and may be able to browse the repository.

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Semantic E-Commerce Lifecycle (3/10)

Negotiation

Negotiation stage of the e-commerce interaction lifecycle refines the abstract service specification from the matchmaking phase to a concrete agreement between two parties

Negotiation can be one-to-one, one-to-many or many-to-many Negotiation protocols determine the interchange of messages which

take place during the negotiation, and the roles by which the negotiation must abide

In each case there are at least two negotiation participants trying to make a deal with each other

There is at least one (possible more) negotiation host, responsible for enforcing the rules of the negotiation and ensuring it goes normally

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Negotiation

Before negotiation can begin, the parties have already agreed roughly what the negotiation is about. So, this places a restriction on the parameters and values to be negotiated, which is called negotiation template

The negotiation template refers to a common ontology accepted by all participants in the negotiation.

It defines a schema for valid negotiation proposals that participants submit to each other

The result of the negotiation process is an agreement

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Standardization take place at 3 levels:

Standards for business-specific ontologies which describe goods, services and contracts being traded

Standards for specifying the format of advertisements, proposals, contracts and other constructs which are used during B2B interactions

Standards that specify the protocols which traders use to interact with each other during different phases of the B2B lifecycle

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Description Language for B2B E-Commerce Lifecycle

Requirements:

Description should offer a high degree of flexibility and expressiveness

Descriptions need to share a common semantics Descriptions should easily lend themselves to performing

the operations described in the negotiation and matchmaking sections

Descriptions should express restrictions and constraints

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Description Language for B2B E-Commerce Lifecycle Why DAML+OIL is a good candidate?

DAML+OIL offers support for types, which greatly enhances the expressiveness and modularity of the descriptions

DAML+OIL offers support for ontologies. It is almost integrated with tools such as OilEd and Protégé which make the generation of new ontologies for service descriptions much easier

All the operations can be expressed in terms of the subsumption operation. DAML+OIL descriptions lend themselves very well

DAML+OIL offers some support for expressing constraints

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Using DAML+OIL

The Description Ontology:Description class is a common superclass for Advertisement, Query, Template and Proposal

The PC Ontology:PC class is a subclass of Product and must have at most one Processor and one amount of memory

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Using DAML+OIL

The Service Ontology:Two services are defined in this ontology: Sales and Delivery

The Participant Ontology:Public information about prospective advertisers and negotiators.

Built from information that individuals or companies are requested to provide at registration time.

Such information is then used at matchmaking and negotiation time to verify compatibility of advertisements and proposals.

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Agreement Instance Example

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E-commerce issues (1/2)

Many consumers do not trust the Internet to provide robust security for online transactions, and many businesses neither trust e-commerce systems nor believe they will be able to evaluate or control their business risk when using them

Lack of automation – human intervention is required for browsing, selecting, ordering and paying for products

Current e-commerce sites do not include semantic representations of data, services, processes, or business models that are readable by software programs (agents)

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E-commerce issues (2/2)

Three technologies will bring e-commerce to the

next generation by increasing efficiency,

compatibility, autonomy, and security:

Mobile Agents: Automate Electronic Transactions Security and Trust: Build a Web of Trust XML: Create a Semantic Web

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Mobile Agents: Automate Electronic Transactions

Mobile software agents are programs that act on behalf of a user or another program and, for a specified mission, are able to migrate from host to host on a network

Numerous applications could benefit from mobile agent technology, such as Internet information retrieval and network management

However, the greatest potential for mobile agents has been e-commerce applications in which the agents automate and facilitate the phases of Brokering of a transaction Negotiation of a transaction Payment of a transaction Delivery of a transaction

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Security and Trust: Build a Web of Trust

Most of the security issues, such as confidentiality, authentication, integrity, and non - repudiation, are addressed by well-known cryptographic algorithms and protocols

However, even if we have a secure channel connecting us to a party whose identity can be verified, we still have no way to confirm the trustworthiness of that party

To meet this challenge, we need a trust management mechanism to manage the histories and reputation of parties involved in the business to create a web of trust

While the mobile agent automates the electronic transactions, it also introduces new security threats

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XML: Create a Semantic Web

Today’s Web is a vast unstructured mass of information HTML was designed to provide a usable interface for humans,

rather than to communicate with other machines. While HTML reflects the structure and limited presentation of a Web page, it conveys nothing about the meaning of the marked document

Search engines and software programs have difficulty using information that is not semantically encoded

Today, several industry-focused initiatives have been formed to work on standards based on XML for interoperable frameworks for e-commerce application domains

Rules range from how to offer items for sale, to making payment choices, delivering products, generating receipts, and resolving problems

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Integration Problems of XML-BasedCatalogs for B2B Electronic Commerce

Electronic marketplaces for Business-to-Business (B2B) electronic commerce bring together many online suppliers and buyers

Each individual participant can potentially use his own format to represent the products in his product catalog

A B2B mediator has to integrate both suppliers’ and buyers’ formats to allow them to do contracting with one another

Given the dominance of XML, e-commerce integration technology must be based on the XML low-level integration architecture provided by the W3C consortium with XSLT and XPath languages

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Product Description Standards (1/2)

xCBL 3.0 developed by Commerce One2, Inc Provides a comprehensive set of standardized XML

document formats, allowing buyers, suppliers and service providers to integrate their existing systems quickly and efficiently in the electronic marketplaces

Internet Open Trading Protocol (IOTP) was developed within the Internet Engineering Task Force (IETF3) consortium Provides the data structures and communication protocols

for payment transactions: purchase, refund, authentication, deposit, and other protocols that occur in electronic commerce

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Product Description Standards (2/2)

Open Applications Group Integration Specification (OAGIS) Provides data structures, messaging formats and protocols for

business integration. OAGIS defines a vocabulary of business terms and more than 90 different types of business documents can be exchanged

Real Estate Data Interchange Standard (RETS) Defines a protocol for implementing transactions, and

incorporates an XML specification for general-purpose interchange. It also provides a compressed data interchange format and specification to allow the interchange of machine-interpretable property information

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Catalog Integration (1/3)

If a marketplace mediates between n suppliers and m buyers, then it must be able to map each of the n suppliers’ catalogs into m buyers’ formats performing nxm mappings

The numbers n and m may be high enough to make the problem of creating and maintaining these catalog integration rules nontrivial

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Catalog Integration (2/3) Unified Catalog (the UC), only

requires the marketplace to perform mapping between each supplier or buyer catalog and the UC, and therefore requires only n+m mappings

There are two opposing strategies for selecting the elements for inclusion in the UC:

a) The unified catalog stores the minimum core number of attributes for each product

b) The unified catalog stores the maximum possible number of attributes

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Catalog Integration (3/3)

In both strategies the UC can change if we add a newcatalogue In strategy (a)

The addition of a more detailed catalog will not change the UC The addition of a less detailed catalog will reduce the granularity

level of the UC. As a result, this strategy bounds the granularity level of the UC to the less detailed catalog, which is unacceptable for most B2B systems

In strategy (b) The addition of a new catalog that is less detailed than the UC

will not influence the latter The addition of a more detailed catalog will require updates to

the UC so that it will not be less detailed than the former

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Integration at the XML Catalog Level (1/5)

Four types of mapping between the attributes of C1 and

C2 are possible: one-to-one mapping (1:1)

It occurs when the element of C1 has a semantic equivalent in C2, i.e. element StateOrRegion in IOTP standard is equivalent to Province in the UC. If the element is encoded by an XML attribute in C1 and by an XML element in C2 then the rule can be expressed as follows (from IOTP to UC):

<xsl:for-each select="PostalAddress">…<Province><xsl:value-of select="@StateOrRegion"/></Province>…</xsl:for-each>

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one-to-many mapping (1:n) It occurs when an element in C1 has to be translated into

several elements in C2. For example, ADDRLINE in OAGIS semantically corresponds to the pair of attributes Street and House in the UC

XSLT rules must be extended with small XPath expressions (element parsers) that will split the elements as required

<ADDRESS><ADDRLINE><STREET>De Boelelaan</STREET><HOUSE>1081a</HOUSE></ADDRLINE>…</ADDRESS>

<STREET><xsl:variable name="addrline" select="ADDRLINE"/><xsl:value-of select="substring-before($addrline,',')"/></ STREET ><HOUSE><xsl:variable name="addrline" select="ADDRLINE"/><xsl:value-of select="substring-after($addrline,', ')"/></ HOUSE >

<ADDRLINE>De Boelelaan, 1081a</ADDRLINE>

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many-to-one mapping (n:1) It occurs when two or more elements from C1 have to be

translated into one element in C2. For example, the Street and House elements in the UC must be translated into the element ADDRLINE in OAGIS. This can be done by means of XSLT in the following way:

<xsl:for-each select="address"><ADDRLINE><xsl:value-of select="Street"/>, <xsl:value-of select="House"/></ADDRLINE>…</xsl:for-each>

<ADDRLINE>De Boelelaan, 1081a</ADDRLINE>

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Many to-many mapping (n:n) It occurs when a piece of a description is spread over several

elements without evident partitioning of information between them. For example, Street, House, and PObox elements of the UC correspond to the pair (AddressLine1, AddressLine2) in IOTP without any indication where street, house, and postbox information should be stored within these two address lines. Mapping of a structured UC record into a less structured IOTP record can be done straightforwardly:

<xsl:for-each select="address"><AddressLine1><xsl:value-of select="Street"/><xsl:value-of select="House"/></AddressLine1><AddressLine2>P.O. Box <xsl:value-of select="PObox"/> </AddressLine2>…</xsl:for-each>

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If an element was mapped into the UC with one 1:n mapping then the reverse mapping will require one n:1 mapping

Most of the rules (89%) represent one-to-one mappings, while the other types only appear in special cases, once or twice for each catalog standard

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Existing Frameworks and Applications

MOMIS SEMANTICEDGE KAON ONTOWEB ONTOKNOWLEDGE

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MOMIS Architecture MOMIS (Mediator envirOnment for Multiple Information Systems) is a mediator-based system aiming to extract and integrate information from heterogeneous data sources, such as relational, object, semi-structured sources (XML)

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SemanticEdge (1/2)

SemanticEdge has developed a state of the art multilingual natural language (text and voice) dialog system capable of handling dialogs with humans wanting to access information, for example, to purchase products and services

The technology extends naturally to Customer Relations Management (CRM) and other e-business functions

This technology depends on several distinct technology areas within Artificial Intelligence: natural language processing, including deep language processing and statistical analyses; machine learning, including inductive learning; speech recognition; automated dialog generation, both user and content specific; and knowledge representation and ontologies

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SemanticEdge (2/2) The system mediates between humans and information. That is, it mediates between an information space and a

human’s conceptualization of that information space; for example, between a product space and a customer’s conceptualization of that product space, and how they will consequently go about searching and querying that product space

Users hold negotiations with the system, which is mediating access to the product spaces, and it will ask questions of them.

This requires the system to have the ability to guide those dialogs according to a representation of that product space.

This ability to a large extent is supported by ontologies

Financial Application demo

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References[1] Semantic Web Support for Business-to-Business E-Commerce Lifecycle David Trastour, Claudio

Bartolini and Chris Preist. Trusted E-Services Laboratory, HP Laboratories Bristol. April 5 th 2002[2] Towards a Semantics for the Web Christopher Welty. Vassar College Computer Science Dept.

Poughkeepsie, NY 12604-0462, USA[3] A Semantic Web Approach to Service Description for Matchmaking of Services David Trastour,

Claudio Bartolini and Javier Gonzalez-Castillo. HP Labs, Filton Road, Bristol BS34 8QZ, UK[4] Reduction of price dispersion through Semantic E-Commerce: A Position Paper Tanya Gupta

and Abir Qasem[5] An Analysis of Integration Problems of XML-Based Catalogs for B2B Electronic Commerce. B.

Omelayenko, D. Fensel. In: Proceedings of the 9th IFIT 2.6 Working Conference on Database Semantics (DS-9), April 25-28, Hong-Kong, 2001.

[6] A Data Integration Framework for E-commerce Product Classification. S. Bergamaschi, F. Guerra and M. Vincini.CSITE-CNR viale Risorgimento 2, 40136 Bologna, Italy.

[7] A Layered Integration Approach for Product Descriptions in B2B E-commerce. Borys Omelayenko and Dieter Fensel.

[8] Next-Generation E-Commerce: XML+Mobile Agent+Trust. CG topics 4/2000. Dr. Jian Zhao, Thomas Blum.

[9] Enterprise-standard ontology environments for intelligent e-business. Alan Flett, Mike Brown[10] Syntactic-Level Ontology Integration Rules for E-commerce. Borys Omelayenko. In: Proceedings

of the 14th International FLAIRS Conference (FLAIRS-2001), Key West, FL, May 21-23, 2001. [11] A Two-Layered Integration Approach for Product Information in B2B E-commerce. Borys

Omelayenko and Dieter Fensel. In: Proceedings of the Second International Conference on Electronic Commerce and Web Technology (EC WEB-2001), Munich, Germany, September 4-6, 2001.

[12] http://www.semanticedge.com/

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Related Papers

[1] The Contract Net protocol: High-level communication and control in a distributed problem solver R.G. Smith. In Proceedings Computing Systems, pages 186-192, Washington, DC, 1979. IEEE Computer Society.

[2] UDDI. Universal Description Discovery Integration Technical White Paper, 2000 [3] Auction theory: a guide to the literature P. Klemperer. Journal of Economic Surveys,

13(3): 227-286, 1999[4] OilEd: a reason-able ontology editor for the semantic web S. Bechhofer, I.Horrocks,

C.Goble, and R.Stevens. In Working Notes of the 2001 Int. Description Logics Workshop (DL-2001), pages 1-9, 2001.

[5] Knowledge Modeling at the Millenium – The Design and Evolution of Protégé W. Grosso, H. Eriksson, R. Fergerson, J. Gennari, S. Tu, and M. Musen. In Proceedings of the 12th International Workshop on Knowledge Acquisition, Modeling and Management (KAW ’99), 1999.

[6] Proceedings of the International Workshop on Description Logics (DL'99) I.Horrocks. FaCT and iFaCT. In P. Lambrix, A. Borgida, M. Lenzerini, R. Möller, and P. Patel-Schneider.

[7] Description logics for matchmaking of services J. González-Castillo, D. Trastour, and C. Bartolini. In Proceedings of the KI-2001 Workshop on Applications of Description Logics, 2001.

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