Transcript AgentService Mobile

Università degli Studi di Genova
Facoltà di Ingegneria Informatica
l . i . d . o . – DIST
AgentSeeker
An agent-based semantic search engine for scalable
enterprise applications
Andrea Passadore, Alberto Grosso
e Antonio Boccalatte
Amsterdam, 8 of June 2009
What is AgentSeeker?
• AgentSeeker is a multi-agent system aimed to
index textual documents coming from…
– … a local hard disk
– ... an intranet
– … Internet
• AgentSeeker is especially targeted to enterprise
applications
• AgentSeeker exploits ontologies…
– … in order to model the enterprise business
domains
– … to enrich user queries.
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AgentSeeker and AgentService
• AgentSeeker
– Based on the AgentService framework
• AgentService
–
–
–
–
C# and .NET Framework 3.5
(Mono: the open-source development framework)
LGPL License.
Developed by the l.i.d.o. staff (University of
Genova)
– www.agentservice.it
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AgentService
Behaviours
Knowledges
APX
Wizards
Development
Agent model
Design tools
Storage
Maintenance
Messaging
Platform
infrastructure
Tools
Core systems
Persistence
Services
Logging
AMS
Roles code
generator
Monitoring
Ontologies
Agent mobility
DF
MTS
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The agent model
• An agent is…
– … an autonomous entity
– … proactive and reactive
– … a part of a collaborative society of peers
• Coordination
• Cooperation
• Interaction
• In AgentService an agent is…
– Information
– Business activities
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BB
B
K
K
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K
The AgentService ecosystem
External application
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Internet
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AgentService federation
• Federating multi-agent platforms means…
– … to automatically route messages to remote
agents
– … to coordinate the local discovery services.
– … to move agent instances among machines.
• Benefits:
– Delocalize the agent services
– Distributed computing
– Load balancing
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The AgentSeeker platform
Directory Facilitator
Indexers
html
Pdf
Office Suite
txt
Manager
Ontology Agent
Central Index
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Query Agent
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Expanding the platform
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Load balancing
A free indexer?
There is Agent#2
Index www.lintar.disco.unimib.it/ONTOSE07/
Remove me
A free indexer?
There is Agent#1
Index conf.ifit.uni-klu.ac.at/ontose/
Remove me
Subscribe me
Subscribe me
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The ontology agent
• The ontology agent…
– ... supports owl – rdf ontologies
– ... maintains ontologies
• From the official company knowledge base
• Uploaded by end users
– ... classifies documents by arguments.
– ... receives the user query from the query
agent...
• ... suggesting an automatic classification of results
• ... adding more details to the query
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Classifying documents
Clean stop
words
Word
Stemming
Count
occurrences
mechanics.owl: 0.32
automotive.owl: 0.09
energy.owl: 0.0002
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Classifying documents
• The a priori classification…
– … is useful to first privilege the on topic
documents in the results of a user query.
– … is useful to descrease the number of false
positive hits.
– Running during the index sessions…
• Supports only the ontologies currently in the
repository.
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Clustering results
car
coupe
Automotive.owl
coupe
convertible
car
“Costs”
station wagon
convertible
Station wagon
Costs AND car
Costs AND coupe
motor
Electric motor
Costs AND convertible
Costs AND station wagon
Costs AND motor
Costs AND electric motor
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Clustering results
• The ontological clustering…
– … is useful to self organize the query results…
• … in folders reflecting the conceptual organization of
an argument
– … is useful to orientate oneself into a relatively
new argument.
– … can be based on imported ontologies
– … requires more resources and process time.
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Query expansion
properties
Extend by:
Automotive.owl
subclasses
synonyms
piston
“Ferrari motor”
motor
valve
“Ferrari motor” OR
“Ferrari piston” OR
“Ferrari valve”
engine
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Query expansion
• The query expansion…
– … allows users to find more documents
• Documents are ordered by relevance
– By the internal ranking of Apache Lucene
– By the a priori classification.
• The query expansion supports also
ontologies directly imported by the user.
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Some evaluations
• The query expansion: +250% of found
documents
– in the first 60 documents:
• 11% of documents are off topic (with query
expansion)
• 35% of document are off topic (without query
expansion)
• A priori classification and ontological
clustering do not present significant issues.
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An AgentSeeker deployment
Intel XEON
dual core 2 GHz
1,5 GB of RAM
Intel Pentium 4
2 GHz
512 MB of RAM
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AMD Athlon
2 GHz
960 MB of RAM
Indexing Agents: 10
Merger Agents: 2
Manager Agent: 1
Query Agent: 1
Ontology Agent: 1
Rate: 6000 web pages per hour
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Conclusions
• AgentSeeker…
– … is a multi-agent society
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•
•
•
Scalable
Flexible
Robust
Open
– … supports ontologies in order to model…
• … the company business domains.
• … the skills of the users.
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Future works
• Ontological wiki
– To create a social collaboration for building
semantic models
• A centralized administration interface
– To manage the distributed environment
• To improve the usability of the system in
term of user’s interactions.
• To improve the ontological support
– By introducing reasoners
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The end
Thank you for your attention!
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Some evaluations
• To build an ontology for supporting users to
find documents…
– … is a complex task
– … is a time-consuming job
– … requires a lot of enterprise resources.
• Solution:
– To develop a sort of wikipedia for constructing
ontologies.
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Ontological wiki
Add concept
Modify concept
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• Add concepts and
relations
• Modify concepts
• Track changes
• Evaluate user’s activities
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