Semantic Web Communication

1
Semantic Web Communication

• Realizing What Semantic Web Can Be.

Anup Patel - 07305042Sapan Shah
- 07305061Nilesh Padariya - 07305064 Vishal
Vachhani - 07305R01
2
2020 And Beyond ..
Middle Agent
Praffuls Agent ContactsA Middle Agent to find
out some hospital in powaihaving a recently
admittedpatient named Hansa.
Agent Your wife is admitted at New Powai
Hospital Ward No. 9
Agent Your meeting is re-scheduled to tomorrow
500 PM
Phone Your wife had an accident she is admitted
at some hospital in powai
New Powai Hospital
Prafful I still dont know where is she
admitted in powai . I should use my agent .
Prafful I have a meeting with my boss and I am
late .
Prafful I should inform my agent to reschedule
meeting
Praffuls Agent Negotiates WithBosss Agent and
re-schedule meeting to tomorrow.
3
Motivation

• Original driver Automation - Make information
  on the Web more machine-friendly - Origins of
  the Semantic Web are in web metadata
• Short term goal Interoperability- Combining
  information from multiple sources- Web Services
  discovery, composition
• Long term goal Departure from the Tool
  Paradigm- instead of using computers like
  tools, make them work on our behalf- removing
  humans from the loop to the extent possible

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Roadmap

• Semantic Web Introduction
• Semantic Web Agents
• Multi-Agent System Communication
• Agent Communication Language
• SPARQL
• Semantic Web Trust
• Semantic Web Status
• Conclusion
• Bibliography

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1. Semantic Web

• The Semantic Web is an evolving extension of
  the World Wide Web in which web content can be
  expressed not only in natural language, but also
  in a format that can be read and used by
  software agents, thus permitting them to find,
  share and integrate information more easily.
• -- Wikipedia

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1.1 Semantic Web Architecture
Trustworthiness
Reasoning
Knowledge Sharing
Knowledge Representation
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1.2 Tree of Knowledge Technologies
Content Management Languages
Semantic Technology Languages
Process Knowledge Languages
AI Knowledge Representation
Software Modeling Languages
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2. Semantic Web Agents

• Agent in AI is any thing that can be viewed as
  perceiving its environment through sensors and
  acting upon that environment through effectors,
  showing a rational behavior.E.g. A human agent
  has eyes, ears and other organs as as
  sensors, and hands, legs, mouth, and other body
  parts for effectors.
• Agent Architecture Program.
• Semantic Web Agents are agents in the web
  environment.

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2.1 Agent Definition

• The definition of agents has not been agreed upon
  universally but, we can have some good
  characteristic of such agents, which are
  - Autonomy - Reasoning Ability
  - Learning Ability - Mobility
  - Sociability - Cooperation
  - Negotiation

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2.1 Agent Definition (Contd..)

• From semantic web point of view agents can be
  thought of as intelligent software program that
  host a collection of web services.
• Unlike standard Web Services, an agent can reason
  about - How to handle external
  request ? - Order in which to carry
  out the request ?

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2.2 Multi-Agent System (MAS)

• MAS is distributed system which incorporates more
  than one independent agents.
• The collection of agents interact, and solve
  problems that are outside their individual
  capacities.
• Agents in MAS display a dual behavior on the one
  hand they are goal directed programs that
  autonomously solve problems and on the other
  hand have a social dimension when they
  interoperate as part of MAS.
• Semantic web in future will be one large MAS
  containing millions of agents communicating with
  each other.

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2.2 Multi-Agent System (Contd.)

• Ontologies in MAS provide agents - The basic
  representation that allows them to reason about
  interactions with other agents.- Shared
  knowledge that they can use to communicate and
  work together.
• In general we can distinguish between Private
  Ontologies that allow the agent to organize its
  own problem solving and reasoning, and Public
  Ontologies that the agent shares with the rest of
  the agents in the MAS.
• Private ontologies are used to represent Private
  Knowledgewhereas, public ontologies are used to
  represent Public Knowledge of an semantic web
  agent.

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2.2 Multi-Agent System (Contd.)

• Example to illustrate use of private and public
  knowledge.

Private Knowledge
Private Knowledge
Public Knowledge
Public Knowledge
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3. MAS Communication

• In MAS communication we are effectively seeking
  to mimic the process of (verbal) communication
  between humans, which by itself is very ambitious
  task.
• At the lowest level, there are two main
  techniques that facilitate communication-
  Message Passing The agents communicate by the
  direct exchange of messages that encapsulate
  knowledge.- Shared State The Agents communicate
  by asserting and retracting facts in a shared
  knowledge base.
• The web uses a message passing approach (TCP
  UDP) so, semantic web communication also have
  based on message passing approach (HTTP XML).

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3. MAS Communication (Contd.)

• For communication on semantic web some issues
  must bepromptly addressed, like- Automatic
  discovery of agents.- Effectively manage the
  shared knowledge.- It must be coordinated,
  correct, and robust to failure.
• To solve the problem of automatic discovery of
  agents we have Middle-Agent architectures.
• To solve the problem of managing shared knowledge
  wehave network architectures.

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3.1 Middle Agent Architecture

• Middle-agents assist in locating service
  providers, and connecting service providers with
  service requesters.
• A variety of middle agent types based on privacy
  considerations of service providers capabilities
  and requesters preferences are possible.
• Middle Agent Architectures are techniques to
  solve problem of automated discovery of agents
  in MAS.

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3.1 Middle Agent Architecture (Contd.)

• Two important types of middle-agent have been
  identified.
• Service Matchmaker The Matchmaker serves as
  a "yellow pages" of agent capabilities, matching
  service providers with service requestors
  based on agent capability descriptions. The
  Matchmaker system allows agents to find each
  other by providing a mechanism for registering
  each agent's capabilities.For each query it
  searches its dynamic database of
  "advertisements" for a registered agent that can
  fulfill theincoming request.

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3.1 Middle Agent Architecture (Contd.)
Service Matchmaker
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3.1 Middle Agent Architecture (Contd.)

• Service Broker Service Broker is similar to
  matchmaker, but also processes the requests.

Service Broker
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3.1 Middle Agent Architecture (Contd.)

• A variety of middle agent types based on privacy
  considerations of service providers capabilities
  and requesters preferences are possible.

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3.2 Network Architecture

• Network Architectures so far, mainly assumed some
  kind of centralized client/server architecture.
  But Service Oriented Architectures can equally
  well be decentralized.
• Network Architectures are techniques to
  effectively storeand retrieve shared knowledge
  of all agents in MAS.
• We can three types of architectures possible
  here - Centralized (Client-Server) -
  Decentralized (Peer-to-Peer) - Hybrid
  (Client-Server and Peer-to-Peer)

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3.2 Network Architecture (Contd.)

• Centralized (Client-Server)

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3.2 Network Architecture (Contd.)

• In Client-Server system, a centralized server is
  used to manage the shared resources.
• Servers works as central repository of the
  shared resources or the shared knowledge.
• It is very easy to adapt current knowledge
  representation like owl and rdf for
  client-server system.
• There are hard limits to number of clients that
  can be servedfrom a single server or a cluster
  of servers. This limits are primarily a function
  of available network bandwidth.

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3.2 Network Architecture (Contd.)

• Decentralized (Peer-to-Peer)

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3.2 Network Architecture (Contd.)

• P2P is a self-organizing system of equal,
  autonomous entities (peers) which aims for the
  shared usage of distributed resources in a
  networked environment avoiding central
  services.
• Peers interact directly with each other, usually
  without central coordination. Each peer has
  autonomy over its own resources.
• Peers can act as both clients and servers i.e.,
  no intrinsic asymmetry of role.
• The network saturation problem does not occur
  todecentralized P2P network.

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3.2 Network Architecture (Contd.)

• In this approach information is copied and
  distributed throughout network. Thus, when a
  client wish to obtain some information it can
  retrieve it from multiple sources and thereby
  avoid overloading at one node.For Example Bit
  Torrent, DC
• Construction of P2P architecture for semantic web
  has important design implications - The
  communicative process must be adapted to work
  with specific P2P technique.- The reasoning
  process must make decisions on what
  information to share and how to retrieve
  information required for reasoning.

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3.2 Network Architecture (Contd.)

• Hybrid (Client-Server and Peer-to-Peer)

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4. Agent Communication Language

• Abbreviated as ACL for short.
• In agent communication our source of inspiration
  in human communication.
• We try to mimic human communication in ACL.
• The foundation of ACL lies in the Speech Act
  Theory.

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4.1 Speech Act

• Proposed by John Austin extended by John Searle.
• How language is used by people everyday to
  achieve their goals and intentions.
• Certain natural language utterances have the
  characteristics of physical actions.
• Certain performative verbs in speech act changes
  the state of the world like physical actions.

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4.2 Types of Speech Acts

• Representative which commits the speaker to the
  truth of what is being asserted. e.g. inform
• Directive attempts to get the hearer to do
  something e.g., please make the tea
• Commisives which commit the speaker for doing
  something, e.g., I promise to
• Expressive whereby a speaker expresses a mental
  state, e.g., thank you!
• Declarative effect some change on the state of
  affairs.e.g. declaring war.

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4.3 Components of Speech Act

• In general Two Components
• Performative Verb (e.g., request, inform,
  promise, )
• Propositional Content (e.g., the door is
  closed)
• More Examples
• performative request
• content the door is closed
• speech act please close the door
• performative inquire
• content the door is closed
• speech act is the door closed ?

32
4.4 ACL Examples

• Communication is performed by exchanging messages
  where each message has an associated
  performative-message types.
• Agent Communication Languages define common sets
  of performatives.
• Two Popular ACLs
• - KQML
• - FIPA-ACL.

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4.5 FIPA-ACL Performative Ontology
34
4.6 Basic Problem of FIPA-ACL

• Semantics Verification Problem
• Sincerity Assumption agent always acts in
  accordance with their intentions.
• Too restrictive in open environment web.
• Despite these FIPA-ACL remained popular
• - e.g. JADE multi agent platform performatives
  are used to facilitate the exchange of message
  but compliance with formal model is not enforce.
  

35
4.7 Dialogue

• Communication rarely consists of a single act of
  speech in isolation.
• It typically consists of sequence of messages
  exchanges between participants such as
  Conversation.
• This type of communication is termed as Dialogue.

36
4.8 Categories of Dialogues
37
4.9 Dialogue frames

• Key construct Dialogue Type
• identifies dialogue type kind of values over
  which it operates.
• Different Dialogues can take different kind of
  values.
• e.g. Beliefs, Contract, Plans
• Frame F is a tuple with four elements ( T, V , t,
  U)
• T Dialogue Type
• V Value over which the dialogue operates
• t Topic of the Dialogue
• U list of utterances which define the actual
  dialogue steps between the participants x
  y e.g. U

38
4.10 Protocols in FIPA-ACL

• It refers to the stereotyped pattern of
  conversation between the agents.
• The protocols are generally pre-specified by the
  agent designer agents needs to discover which
  protocols to follow during Dialogue.
• Choice of protocols to be followed can be
  negotiated by the agents.
• In FIPA-ACL the convention is to put the name of
  the protocol in the protocol parameter of the
  message.

39
4.11 FIPA-Query-Protocol
40
4.12 ACL in MAS

• Reduce the complexity to pair wise interaction
  between agents. Has limitations in terms of
  multicast broadcast communication.
• As the size of the MAS increases, the ability to
  communicate reliably deteriorates. MAS operating
  over web has to face some basic problems such as
  delay in message passing, messages may be lost.
  So Asynchronous agents are required.
• An open MAS is designed to enable
  interoperability between agents from many
  different sources. These may introduce problems
  like malicious, untrustworthy agents.

41
5. SPARQL

• Simple Protocol And Rdf Query Language
• SPARQL Query Language Protocol XML Results
  Format
• Its a Query language for RDF Data, and it
  involves- Basic graph pattern matching. - No
  inference in the query language itself.
• As a Protocol it uses- HTTP binding - SOAP
  binding
• XML Results Format are- Easy to transform
  (XSLT, XQuery)

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5.1 Its Turtles all the way down
Turtle (Terse RDF Triple Language ) - An RDF
serialization - The RDF part of N3 -
Human-friendly alternative to RDF/XML
0.1/name Nilesh
_at_prefix person
. _at_prefix foaf
. person A foafname Nilesh" . person A
foafmbox . person
B foafname Sapan" . _b foafname Vishal" .
_b foafmbox .
------------- name Nilesh
Sapan Vishal -------------
Blank Node
A "hello world" of queries SELECT ?name WHERE
?x foafname ?name
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5.2 Matching RDF Literals
_at_prefix dt .
_at_prefix ns . _at_prefix
. _at_prefix xsd
. x nsp
"cat"_at_en . y nsp "42"xsdinteger . z nsp
"abc"dtspecialDatatype .
--------- v
----------------------------------
v http
//example.org/nsx ----------------------------
------
----------------------------------
V http
//example.org/nsz -----------------------------
-----
----------------------------------
V http
//example.org/nsy -----------------------------
-----
SELECT ?v WHERE ?v ?p "cat"
SELECT ?v WHERE ?v ?p "cat_at_en
SELECT ?v WHERE ?v ?p 42
SELECT ?v WHERE ?v ?p "abc"/datatypespecialDatatype
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5.3 Filter
_at_prefix dc
. _at_prefix stock
. _at_prefix inv
. stockbook1 dctitle "SPARQL Query Language
Tutorial" . stockbook1 dcedition
First stockbook1 invprice 10 . stockbook1
invquantity 3 . stockbook2 dctitle "SPARQL
Query Language (2nd ed)" . stockbook2 invprice
20 invquantity 5 . stockbook3 dctitle
"Applying XQuery dcedition Second
. stockbook3 invprice 20 invquantity 8 .
--------------------------------------------------
------------------- book title

stockbook1 "SPARQL Query Language
Tutorial" --------------------------------------
-------------------------------
PREFIX dc PREF
IX stock PREFIX inv
SELECT ?book
?title WHERE ?book dctitle ?title . ?book
invprice ?price . FILTER ( ?price invquantity ?num . FILTER ( ?num 0 )
45
5.4 Other Solution Modifiers
PREFIX dc
SELECT ?title ?edition ?x dctitle ?title
. OPTIONAL ?x dcedition ?edition
PREFIX foaf SELECT
?name WHERE ?x foafname ?name ORDER BY
?name
PREFIX foaf SELECT
DISTINCT ?name WHERE ?x foafname ?name
ORDER BY ?name LIMIT 5 OFFSET 10
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5.5 CONSTRUCT
_at_prefix foaf . _a
foafgivenname "Alice" . _a foaffamily_name
"Hacker" . _b foaffirstname "Bob" . _b
foafsurname "Hacker" .
PREFIX foaf PREFIX
vcard
CONSTRUCT ?x vcardN _v . _v
vcardgivenName ?gname . _v vcardfamilyName
?fname WHERE ?x foaffirstname ?gname
UNION ?x foafgivenname ?gname . ?x
foafsurname ?fname UNION ?x foaffamily_name
?fname .
_at_prefix vcard .0 . _v1 vcardN _x . _x
vcardgivenName "Alice" . _x vcardfamilyName
"Hacker" . _v2 vcardN _z . _z
vcardgivenName "Bob" . _z vcardfamilyName
"Hacker" .
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5.6 DESCRIBE
PREFIX books PREFIX
dc DESCRI
BE ?book WHERE ?book dctitle "Harry Potter
and the Prisoner Of Azkaban"
rdfabout"http//example.org/book/book3"


JoannaGiven
Rowling
J.K.
Rowling
Harry Potter and the Prisoner
Of Azkaban rdfRDF
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5.7 XML Result Set
--------------------------------------------------
---------------------- name
mbox

"Johnny Lee Outlaw"

---------------------
--------------------------------------------------
-
ts" namename"/
distinct"false" namename"Johnny Lee
Outlaw namembox"mailtojlow_at_example.comnding
mailtopeter_at_example.or
g

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5.8 ASK
_at_prefix foaf . _a
foafname "Alice" . _a foafhomepage
. _b foafname
"Bob" . _b foafmbox
.
Yes
PREFIX foaf ASK
?x foafname "Alice"
3.org/2005/sparql-results"
true

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5.9 More Features

• RDF Dataset
• - Collection of RDF Graphs
• - use FROM
  FROM NAMED rdf
• Inbuilt functions for testing values
• - IsLiteral
• - IsBlank
• - str
• - regex

51
5.10 Limitation of SPARQL

• No nested queries
• No Insert, Update, Delete queries
• No aggregation functions

52
6. Semantic Web Trust

• Some of the important questions for the Semantic
  Web Communication are - How trust worthy is
  the information found on semantic web ?- How
  do I decide that an agent is trust worth ?
• To answer this questions we have semantic web
  trustin action.

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6.1 Basic Terms

• Security A goal, bad things don't happen
• Privacy A goal, personal information is not
  disclosed or abused
• Policy Rules for behavior
• Provenance Information (metadata) about the
  source of some piece of data
• Trust Belief in (expectation of) the behavior
  of a party for some given purpose

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6.2 Trust Security in Data Transfer
55
6.3 Basic Roles

• Information Providers
• - Want that their information is used / believed.
• - Might want to state their publishing intend
  (assertion, quote).
• Information Consumers
• - Want to use the information for different
  tasks.
• - Have different views of the world.
• - Have different subjective trust requirements.
• - Have different subjective preferences for
  certain trust
• mechanisms.

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6.4 Trust Policies

• We use a wide range of trust policies in everyday
  life
• - We might trust Andy on restaurants but not on
  computers.
• - Buy only from sellers on eBay who have more
  than 100
• positive ratings.
• - Regard literature as irrelevant, when it is
  older than 5 years,
• - Trust professors on their research field,
  believe foreign news only when they are reported
  by several independent sources.
• Goal Allow a similar wide range of trust
  policies on the Semantic Web.

57
6.5 Trust Situation on Semantic Web
58
6.6 Requirements Of SW Trust Layer

• Use of all trust relevant information available
• - WWWWW who, what, where, when and why
• Support different, subjective, task-specific
  trust policies
• - Reputation-based
• - Context-based
• - Content-based
• Note many applications dont require total
  trustworthiness.

59
6.7 Trust Mechanisms

• We can classify trust mechanisms into three
  categoriesbased on support to different,
  subjective, and task-specificetrust policies
• 1. Reputation-based trust mechanism
• 2. Context-based trust mechanism
• 3. Content-based trust mechanism

60
6.7 Trust Mechanisms (Contd.)

• Reputation-Based Trust Mechanism- Include
  rating systems and web-of-trust mechanisms are
  a well researched area- Have a general problem
• They require explicit and topic-specific trust
  ratings
• high effort for information consumers

61
6.7 Trust Mechanisms (Contd.)

• Context-Based Trust Mechanism- Use background
  information about the information provider.
• - agents role in the application domain or
  his membership in a specific group
• e.g. policy "Distrust everything a vendor says
  about his
• competitor or Trust all
  members of
• organization A.
• - Information created in the information
  gathering process.
• - publishing and retrieval date and the
  retrieval URL
• - Information whether a signature is
  verifiable or not.
• e.g. policy Trust all information which has
  been signed and is not
  older than a month.

62
6.7 Trust Mechanisms (Contd.)

• Content-Based Trust Mechanism- Use information
  content itself, together related information
  content published by other information
  providers.- Example policies
• Believe information which has been stated by at
  least independent sources.
• Distrust product prices that are more than 50
  below the average price.

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6.8 Named Graphs -Introduction

• Extension of RDF Graph
• For a named graph ng ( n, g )
• name(ng) n
• rdfgraph(ng) g
• A set of Named Graphs is collation of RDF graphs,
  each one of which is named with a URI
• Usefulness
• - Foundation for the Trust layer
• - Restring information access
• - Keep tract of provenance Information
• - Signing RDF graphs
• - Information consumer can calculate Trust

64
6.8 Named Graphs (Contd.)
...
...
eggraph2
eggraph1
...
eggraph3
65
6.9 Accepting Graphs

• A set of named graphs N will not give us a single
  meaning.
• Semantics can be determined by a subset A of N.
• There are total 2N subsets of N, hence we have
  2N differentmeanings of N.
• Thus, trust is problem of determining A.

66
6.10 Introduction To TriQL.P

• TriQL.P is a query language, that allows the
  formulation of trust policies within queries
• - uses graph patterns
• - supports set operations and different ranking
  mechanisms
• - returns justification trees together with the
  query results
• Justification trees
• - provide explanations why data should be trusted

67
6.11 Trust Architecture
- Retrieved information is used within an
application context- Functionality to browse
through justification trees
- Handles the actual trust decision using
TriQl.p
- Stores aggregated information- KB without
evaluating their trustworthiness
- Aggregate information from different sources-
Adds provenance metadata information- Digital
signature verification - e.g. ExfoundAtURL,
Exsignatureverifiedby
68
6.11 Algorithm For Trust Evaluation

• K is initial RDF KB (possibly empty or not),
• Input a set of Named Graph N
• Algorithm
• 1. Set A
• 2. choose n ? domain(N) - A, or terminate.
• 3. Set K K U n
• 4. If K is inconsistent then backtrack to 2.
• 5. if K is consistent then apply Trust policies
  
• 6. If it satisfies policies then set K K and
  A A U n, otherwise backtrack to 2.
• 7. Repeat from 2.
• Output a set A a set of Graph on which we can
  trust.

69
7. Semantic Web Status
70
8. Conclusion

• Knowledge representation is very well developed
  insemantic web.
• Agent communication is still an active area of
  research, though we have standardized
  languagelike SPARQL, still lot of research is
  required inapplying languages like FIPA-ACL to
  semantic web.
• Semantic web trust still remains the least
  explored ofall the layers of semantic web. Named
  graphs laidan important foundation in this area.
• All in all semantic web is still a research field
  in academia

71
9. Bibliography

• Introduction- http//www.wikipedia.org/Semantic_
  Web- http//www.cs.cmu.edu/7Esoftagents/middle.h
  tml- Agency and Semantic Web, By Christopher
  Walton, Oxford Press.- Explorers Guide To
  Semantic Web, By Thomas B. P., Manning
  Publication.

72
9. Bibliography (Contd.)

• Agent Communication
• - Agency and Semantic Web, By Christopher
  Walton, Oxford Press.- Explorers Guide To
  Semantic Web, By Thomas B. P., Manning
  Publication. - Lecture Notes of Multi-agent
  Semantic Web Systems, University of
  Edinburgh.
• SPARQL- http//www.w3.org/TR/2007/CR-rdf-sparql-
  query-20070614/- http//www.dajobe.org/2004/01/tu
  rtle/

73
9. Bibliography (Contd.)

• Semantic Web Trust- http//www.w3.org/2004/03/tr
  ix/ (Named Graph Website, Link to TriQL)-
  http//www.hpl.hp.com/techreports/2004/HPL-2004-57
  .html (Named Graphs, Provenance and Trust)-
  http//www.wiwiss.fu-berlin.de/suhl/bizer/TriQLP
  (Named Graphs paper by Carroll Stickler)
  (TriQL.P)- http//citeseer.ist.psu.edu/article/bi
  zer04using.html (C. Bizer and R. Oldakowski.
  Using Context- and Content- Based Trust
  Policies on the Semantic Web. In 13th World
  Wide Web Conference, WWWW2004 (Poster), 2004.)

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Questions ..??
75
Thank You ..