Applications of

1
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Applications of Information Fusion Theory in the
Internet
2
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????????
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????? ?????

• ????? Multi- Sensor Data Fusion ? Information
  Fusion ? ?????? ???? ?? ??????

• ???? ??? ?????? ? ???? ??? ??? ????? ? ? ??????
  ???? ?? Information Fusion

• ?????? Conventional ????? ???????

• ??? ??? ?????? ????? ???????

• ProFusion ? ?? ??? ????? ?????

• Using a Data Fusion Agent for Searching the WWW

• ?????? ????? ????? ??????? ?? ?? ???? ???????

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?? ??????
??? ??? ????? Multi- Sensor Data Fusion ?
Information Fusion ? ?????? ???? ?? ??????

• ?? ??? ??? ?? ????? ????? ??? ?????? ??????
• ????? ?? ?? Data / Information Fusion (?????
  ???? / ???????)
• ?????? ????? ???? ? ????? ???????
• ???? ????? ????? ? ????? ?????
• ??? ????? (Uncertainty) ??? ????? ?????? ??
  ???????
• ??? ??? ???? ?????? ?? ??? ????? ?? ?????
  ???????

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????? ????? ???? ? ????? ??????? ? ?????? ????
?? ??????
????? ?? ?? Data / Information Fusion (?????
???? / ???????)
?????
Data fusion is a process that seeks to improve
the ability to estimate the position,
velocity,... and identity or characteristics of
entities by combining information and data from
multiple sensors and sources (Waltz and Llinas,
D. Hall, and D. Hall and Llinas)
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????????
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?? ??????
????? ????? ???? ? ????? ??????? ? ?????? ????
?? ??????
????? ?? ????? ???? / ??????? ? ????? ???? ???
????? ?? ????? ????? ???? ??????? ?? ???????
?????? ? ?????? ??? . ???? ?? ???? ????? ????
???? ?? ?? ????? ????? ?? ???? ?? ????? ??? ??
?????? ???? ?? ???? ???? ? ?????? (Uncertain) ? ?
???? ????? ?? ?????.
????? ????
????1
????
????2
Fusion
????? ????
n????
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????????
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?? ??????
????? ????? ???? ? ????? ??????? ? ?????? ????
?? ??????

• Sensor Fusion Data Fusion from Multiple Sensors
  (same or different sensor types)
• Data Fusion Combining information to estimate
  or predict the state of some aspect of the world
• Data Fusion Functions
• Data Alignment
• (spatio-temporal,
• data normalization,
• evidence conditioning)
• Data Association
• (hypothesize entities)
• State Estimation
• Prediction

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?? ??????
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?? ??????
Type of Inference
Applicable Techniques
High
- Threat Analysis
- Knowledge-Based Techniques
- Expert Systems- Scripts, Frames, Templating -
Case-Based Reasoning - Genetic Algorithms - etc.
- Situation Assessment
- Decision-Level Techniques
INFERENCE LEVEL
- Neural Nets- Cluster Algorithms - Fuzzy Logic
- Behavior/Relationships of Entities
- Estimation Techniques
- Identity, Attributes and Location of an Entity
- Bayesian Nets - Maximum A Posteriori
Probability (e.g. Kalman Filters, Bayesian), -
Evidential Reasoning
- Existence and Measurable Features of an Entity
Low
- Signal Processing Techniques
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?? ??????
????? ????? ???? ? ????? ??????? ? ?????? ????
?? ??????
?????? ??????? ?? ???? ??? ???????

• ?? ???? ????? ?? ?? ??? ???? ? ???? ???? ?? ??
  ?????? ??? ??? ?? ?? ????
• ???? ?? ??? ???? ??? ???? ???? ??? ? ?????
  ????? ?????? ? ?????? ????? ???
• ?????? ???? ?????? ?? ?????? ???? ?? ?????
  ?????? ????? ?? ???? ???? ?? ????
• ????? ????? ????? (??????? ?? ??? ????? ??????
  ?? ??? ?? ????? ???? ????)
• ????? ?????? ???? ? ?? ???? ??????? ?? ???? ???
  ???????
• ????? ?? ???? ????? ??? ????? ???? ????
  ???????? ???? (?? ???? ???? ? ?? ????? ????? ???)

?????? ??????? ???? - ????? ?????? - ????? ?????
????? ?? - ???? ???? ??? ????? ????
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????????
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?? ??????
????? ????? ???? ? ????? ??????? ? ?????? ????
?? ??????
???? ?? ???? ?? ???? ????/??????? ?? ????
????? ???? ?? (Dasarathy, Belur V. ,
Decision Fusion)

• ???? ??? ???? (Active Sensors)
• ???? ??? ??? ???? (Passive Sensors)
• ???? ??? ???? / ??? ???? (Mixed Active/Passive
  Sensors )

??????? ??? ??? ?? ?????? ??????? ???? ?? Fusion

• ??????? ???? ?? ?? ?????? (?? ???? ??? ????
  ????/???????? ????? ???? ???? ?????? ????? ?????
  ??????? ...)
• ???? ???? ???? ??/??????? ???? ?? ?????? (???
  ??? ???? ???? ?? ????? ?? ?? ?? ???? ?? ?? ?????
  ???? ???? ?? ????? ?????? ??????? ?????? ?? ?????
  ??? ? ??? ???? ?? ?? ????? ?? ?? ????? ????? ??
  ?? ????? ???? ???? ?? ???? ??? ????? ????? ?? ??
  ???? ???? ?????? ?? ????)

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????????
????? ????? ???? ? ????? ??????? ? ?????? ????
?? ??????
????? ????? ???? ? ????? ??????? ? ?????? ????
?? ??????
?????
??????? (Information) ???? ?????? ?????? ??? ????
??? ??? ?? ?? ??? ???? ?? ???? ?? ???.

• ?????? ????? ????? ??????? ? ????? ??????? ? ?
  ????????? ???? ??? ????? ????????? ??????? ?
  ??????? ?? ?? ??? ??? ???? ??? ?? ???? ???? ?????
  ? ???? ????? ??????? ???? ????? ??????? ????? ??
  ????
• ?????? ????? ???? ?? ????? ??????? ???? ??
  ????? ???? ?? ???? ???? ?? ???? ? ?? ???? ??.
• ????? ??????? ?? ????? ?? ???? ???? ? ????? ??
  ??? ??????? ????? ? ?? ???? ?????? ????? ???? ?
  ???? ????? ????? (Feature Fusion) ? ????? ?????
  (Decision Fusion)
• ????? ??????? ?? ????? ?? ????? ?????? ???????
  ?? ???? ???? ???? (Data Mining) ? ?????? ?????
  (Knowledge Discovery) ?? ??? ????? ???.

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????????
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?? ??????
????? ????? ???? ? ????? ??????? ? ?????? ????
?? ??????
?????? Data Fusion ? Information Fusion
????? ????? ?????? ?????????? - ????? ???
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????????
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????????
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?? ??????
????? ????? ???? ? ????? ??????? ? ?????? ????
?? ??????
?????? ?????/????? ?????? Fusion
Data in-Data out Fusion
Data Input
Data Output
Data in-Feature out Fusion
Data Input
Feature Output
Feature in-Feature out Fusion
Feature Input
Feature Output
Feature in-Decision out Fusion
Feature Input
Decision Output
Decision in-Decision out Fusion
Decision Input
Decision Output
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?? ??????
????? ????? ???? ? ????? ??????? ? ?????? ????
?? ??????
???? ????? ????? ? ????? ?????
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????????
??? ??? ??????? ? ?????? ?? ??? ?????
(Uncertainty)
??? ????? (Uncertainty) ?? ??????? ? ???? ??????
?? ??
Uncertainty can come in many forms, including

• Incompleteness

Sensors are likely to leave something out

• Imprecision

Sensors may provide only approximations

• Inconsistency

Sensor data may not always agree

• Ambiguity

Data streams from various sensors may be
indistinguishable from one another
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????????
??? ??? ??????? ? ?????? ?? ??? ?????
(Uncertainty)
???????
Randomness Probability

• ????? ????????

Bayesian Decision Theory
???? ??????
??? ??? ??????? ? ?????? ?? ??? ?????
(Uncertainty)
???????
Imprecision , Belief Ignorance

• ????? ??????? ?????

Evidential Reasoning Theory
???? ??????
???????
Fuzziness, Fuzzy Sets Membership Functions

• ????? ?????? ??? ????

Fuzzy Set Theory
???? ??????
????? ?????? ??? ?????? (Random Set Theory)
????? ????? ?????? ?????????? - ????? ???
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????????
???? ??? ?????? ? ???? ??? ??? ????? ? ? ??????
???? ?? ...
??? ??? ???? ??? ?????? ? ???? ??? ??? ????? ? ?
?????? ???? ?? Information Fusion

• ?? ??? ??? ?? ????? ????? ??? ?????? ??????
• ????? ????
• ????? ??????? ?? ???? ??
• ???? ??? ???? ??
• ????? ??? ??? ????? (Multi Agent Systems)
• ???? ??? ??? ????? ?? ???????

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????????
???? ??? ?????? ? ???? ??? ??? ????? ? ? ??????
???? ?? ...
????? ????
????? ???? ???? ?? ??? ????? ???? ??????? ?? ????
??? ???? ?? ???? ??? ?? ???? ???

• ?? ??? ????? ?? ??? ?????? ?? ?????? ??????????
  ????????? ??????? ?? ???? ?????? ?? ??? ???? ??
  ????? ???? ????? ?? ????? ???? ?????? ???.
• ??? ??? ?? ?? ????? ??? ????? ????? ?????? ??
  ???? ??? ??
• ???? ?????? ?????? ?? ??? ?????? ??? ?? ??
  ????? ????? ?????? ?? ?? ???? ??? ???? ??
  ???????? ???? ????? ????? ????? ???.
• ???? ?????? ??? ?? ?? ??? ???? ?????? ?? ???
  ????? ?? ?? ????? ???? ?? ?? ??????? ????? ?? ???.

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????????
???? ??? ?????? ? ???? ??? ??? ????? ? ? ??????
???? ?? ...
????? ??????? ?? ???? ??? ?????? ??? ??????

• Internet based Information Systems
• Adaptive (Customizable) Software Systems
• Autonomous Mobile Immobile Software Robots
• Data Mining
• Knowledge Discovery
• Smart systems (Smart Automobile , Smart Home, )

• Decision Support Systems
• Intelligent Design
• Data Base Knowledge Base Systems
• Distributed Computing
• Information Retrieval
• Machine Learning

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???? ??? ?????? ? ???? ??? ??? ????? ? ? ??????
???? ?? ...
??? ???? ?? ???? ??? ??????

• ?? ????? ??? ???????? ????? ??? ?? ???? ??? ??
  ????
• ?? ??? ??? ???? ?? ??? ? ?? ????? ?? ?????
  ??????? ???

Advisory (Collaborative Agent Systems)

• ????? ???? ??? ???? ????? ????? ????
• ???? ??? ??????? ?? ???? ????? ????? ????? ???.
  ?? ??? ????? ?????? ???????? ?? ?? ???
• ???? ?????? ????? ????? ??? ??? ?? ?? ?? ?? ??
  ?????. ?? ?? ????? ???? ?? ???? ??? ?? ????

Assistant (Personal Assistants)
Intelligent Agents

• ?? ????? ?? ?? ?????? ?? Intranet ?? ?? ??
  Internet ??? ????? ??? ????? ???? ?????
• ?????? ?? ?? ???? ??? ??? ????? ??? ? ???????
  ?? ???? ????? ? ????? ?? ????? ?? ???

Internet Agent (Mobile Agent)
????? ????? ?????? ?????????? - ????? ???
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????????
???? ??? ?????? ? ???? ??? ??? ????? ? ? ??????
???? ?? ...
??????? ?? ???? ? ??????? ???? ?? ?? ????? ?? ??
?????? ????? ???? ????? ?? ???? ???? ? ??
??????? ??????? ????? ? ?????? ???. Smart
MailBox ???? ??????? ??? ?? ?????? E-mail ?? Fax
?? ?? ???? ?? ???? ? ???? ?? ?? ???? ???? ??
????? ? ?? ???? ????? ????? ???? ?? ?? ?? ?????
?? ??? ? ... . ?????? ????? ??? ????? ? ???? ??
????? ????? ?? ?? ???? ?????? ? ????? ?????
????? ?? ???? ??? ????? ?? ???? ??? ?????? ??
?????. ProFusion ????? ?? ?? ??? ???????? ?????
?? ????
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21
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????????
???? ??? ?????? ? ???? ??? ??? ????? ? ? ??????
???? ?? ...
????? ??? ??? ????? (Multi - Agent)
????? ??? ????? ?????? ??? ?? ?? ?? ?????? ????
????? ?? ????? ? ????? ???? ???? ????? ?? ??????
??? ?????? ???? ????? ?? ?? ?? ??? ??? ?????
???? ?? ????. ???? ???? ??????? ?? ????? ??? ???
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??? ?? ???? ???????? ?? ?????? ?? ????? ??????
???? ?? ?????.
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????????
???? ??? ?????? ? ???? ??? ??? ????? ? ? ??????
???? ?? ...

• ??????? ????? ??? ??? ?????
• ????? ???? ? ?????? ????? ??? ???? ??.
• ???? ?? Coordination Protocl ???? ????? ???????
  ??? ???? ?? (?? ???? ???? ??????? ????? ???? ??)
• ???? ???? ????? ???? ?????? ????? ??? ???? ??
  ?? ?????? ? ?? ?? ?????? ?????
• ????? ??????? ???? ???? ???? ?? ?? ?? ???? ????
  ?? ????? ??? ??????
• ???? ?????? ????? ???? ??? Conflict ??? ?????
  ???? ??

• ?? ?????? ???? ???? ????? ??? ??? ?????
• ????? ??? ?? ?????? ????? (Centralized)
• ????? ??? Leader - Follower
• ????? ??? ?????? (Distributed)

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????????
???? ??? ?????? ? ???? ??? ??? ????? ? ? ??????
???? ?? ...
???? ???? ????? ??? ??? ?????
??? ???? ?? ????? ???? ???? ????? ????? ??
????????? ?? ???. ???? ????? ??? ?? ??? ?? ??
????? ???????? ???.

• ???? Robustness ??
• ?????

?? ???? ???? ????? ?? ?? ?? ??? ????? ??? ????
?????? ????? ?? ??? ??? ??????. ????? FT ?????
????? ????? ????. ???? ??????? ????? ????? ?????
?? ????. ??????? ????? ????? ???? ????? ?? ????
???? ????? ???? ???.

• Fault Tolerance ????
• ? Reliability ?????

• ???? ???? Flexibility ?
• Adaptation

??????? ????? ?? ??? ???? ?????? ???????
(Learning) ???.
?? ??? ???? ????? ????? ???? ??? ????? ??? ??
????? ????? ? ????? ????????? ????? ????. ????
???? ??? ??? ???? ???? ?? ?? ?? ???? ?? ??????
????? (??? ?????? ?????)

• ?????? (Coherent)
• ???? ?????

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24
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????????
???? ??? ?????? ? ???? ??? ??? ????? ? ? ??????
???? ?? ...
???????? ?? ???????? ????? ???? ??? ??? ????? ???
Internet

• (ABE (Agent Building Environment
• ????? ? ???????? ?? ??? ???? ????? ???? ??. ABE
  ?? ??? ???? ???? ????? ??? ??? ?? ???? ????????
  ?????? ?????? ???????? ?????? ? ?Adapter ??? HTTP
  ? FTP ? ? ???? ????????? ????? ?? ????.

• IBM Aglets
• ???????? ????? ? ????? ?? ????? ?? ???? ?? ?????
  ????? ?? ?? ?? ?? ?? ????? ?? ???? ? ?? ?????? ??
  Platform ??? ????? ???? ?????? ? ?? ?? ?????
  ?????? ????.

• JATLite (Java Agent Template Lite )
• ????? ??? ???? ???? ????? ????? ??? ??? ????? ??
  ???? ?????? TCP/IP. ???? ?? ?? ??? ???? ?????
  ??????.

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??????? ????? - ??????? ??? ???? ?????? ??? ?
????????
ProFusion ...
Profusion
Adaptive Agents for Information Gathering from
Multiple Distributed Information Sources
Dr. Susan Gauch Associate Professor, University
of Kansas
????? ????? ?????? ?????????? - ????? ???
?? ?????, 10 ????????, 1380
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??????? ????? - ??????? ??? ???? ?????? ??? ?
????????
ProFusion ...
Nor do they have the time to submit each query to
multiple search engines and wade through the
resulting flood of good information, duplicated
information, irrelevant information and missing
documents.
A Meta Search Engine sends user queries to
multiple underlying search engines in parallel,
retrieves and merges the resulting urls
Users do not have the time to evaluate multiple
search engines to knowledgeably select the best
for their uses !!!
What is a Meta - Search Engine ?
????? ????? ?????? ?????????? - ????? ???
?? ?????, 10 ????????, 1380
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??????? ????? - ??????? ??? ???? ?????? ??? ?
????????
ProFusion ...
SavvySearch Daniel Dreilinger, "Experiences with
Selecting Search Engines using Meta-Search 1996
ProFusion Susan Gauch Yizhong Fan An
Adaptive Multi-Agent Architecture for the
ProFusion Meta Search System " 1997 - 2001
Personal Web Watcher Dunja Mladenic J. Stefan
Text - Learning Intelligent Agents " 1999
Meta Crawler Erik Selberg, Oren Etzioni,
"Multi-Service Search and Comparison Using the
MetaCrawler" 1995
????? ????? ?????? ?????????? - ????? ???
?? ?????, 10 ????????, 1380
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??????? ????? - ??????? ??? ???? ?????? ??? ?
????????
ProFusion ...
ProFusion
?ProFusion Supports nine underlying search
engines.It categorized incoming queries and
routed each query to the best search engines for
the identified category based on hard- coded
confidence factors for each search engine in
each category ...
????? ????? ?????? ?????????? - ????? ???
?? ?????, 10 ????????, 1380
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??????? ????? - ??????? ??? ???? ?????? ??? ?
????????
ProFusion ...

• Agent-Oriented Systems for the Web
• Adaptive Search Agents for the WWW are systems
  which not only search for information of interest
  to their users, but also continuously change
  after every search to improve the quality of
  their search results.
• Agent-Oriented systems usually consist of
  information filtering agents and information
  discovery agents.

• Information filtering agents The information
  filtering agents are responsible for the
  personalization of the system and for keeping
  track of (and adapting to) the interests of the
  user.
• Information discovery agents The information
  discovery agents are responsible for information
  resource handling, adapting to those information
  resources, finding and fetching the actual
  information that the user is interested in.

????? ????? ?????? ?????????? - ????? ???
?? ?????, 10 ????????, 1380
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??????? ????? - ??????? ??? ???? ?????? ??? ?
????????
ProFusion ...
ProFusions Multi-Agent Architecture
ProFusion multi-agent system consists of four
different types of agents, namely, a dispatch
agent, a search agent, a learning agent, and a
guarding agent. Figure shows the control flow
and intercommunication between agents in the
ProFusion system.
????? ????? ?????? ?????????? - ????? ???
?? ?????, 10 ????????, 1380
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Agent Intercommunication and Control Flow Diagram
32
??????? ????? - ??????? ??? ???? ?????? ??? ?
????????
ProFusion ...
The search agent, learning agent, and guarding
agent each consists of a set of identical
competence modules, each of which is responsible
for one of underlying search engines
(task-oriented modules). These competence modules
are self-contained black boxes which handle all
the representation, computation, reasoning, and
execution that is necessary for its particular
search engine (task-specific solutions). Except
for the dispatch agent, all of the competence
modules of the search agent, learning agent, and
guarding agent operate concurrently.
????? ????? ?????? ?????????? - ????? ???
?? ?????, 10 ????????, 1380
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??????? ????? - ??????? ??? ???? ?????? ??? ?
????????
ProFusion ...

• The dispatch agent communicates with the user
  and then dispatches queries to the search agent
  and the learning agent.

• The search agent interacts with the underlying
  search engines and is responsible for reporting
  search results, confidence factors, and time-out
  values of the underlying search engines to the
  dispatch agent, as well as invoking the guarding
  agent when necessary.

• The learning agent is in charge of the learning
  and development of the underlying search engines,
  in particular adjusting confidence factors.

• The guarding agent is invoked when a search
  engine is down and it is responsible for
  preventing the dispatch of future queries to a
  non-responsive search engine as well as detecting
  when the search engine is back online.

????? ????? ?????? ?????????? - ????? ???
?? ?????, 10 ????????, 1380
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(No Transcript)
35
(No Transcript)
36
??????? ????? - ??????? ??? ???? ?????? ??? ?
????????
ProFusion ...
ProFusion Agent's Adaptation Algorithms

• Adapting to Changing Search Engine Performance
  Response time
• search engines frequently went down and/or
  became slow and ProFusion did not detect this and
  route queries to working and/or faster sources of
  information

• Adapting to New and/or Changing Search Engines
  Result Formats
• A dynamic pattern extractor was built to
  interpret the result page formats for each search
  engine. This parser identifies the repeated items
  on the results page and creates the regular
  expression that extracts the individual elements
  within each item (e.g., url, weight, title,
  summary).

????? ????? ?????? ?????????? - ????? ???
?? ?????, 10 ????????, 1380
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??????? ????? - ??????? ??? ???? ?????? ??? ?
????????
Using A Data Fusion Agent for Searching the WWW
Using A Data Fusion Agent for Searching the WWW
Alan F. Smeaton and Francis Crimmins Dublin City
University, Ireland
????? ????? ?????? ?????????? - ????? ???
?? ?????, 10 ????????, 1380
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??????? ????? - ??????? ??? ???? ?????? ??? ?
????????
Using A Data Fusion Agent for Searching the WWW
Using A Data Fusion Agent for Searching the WWW

• As a result of the explosive growth of the WWW
  coupled with our inability to document or
  catalogue the web at a fast enough rate so far,
  navigating the WWW presents a difficult task.

• Fusion is a meta search engine which uses
  existing search engines as an underlying
  implementation layer.

????? ????? ?????? ?????????? - ????? ???
?? ?????, 10 ????????, 1380
39
??????? ????? - ??????? ??? ???? ?????? ??? ?
????????
Using A Data Fusion Agent for Searching the WWW

• Apart from serendipitous browsing (ever more
  difficult given the growth rate of the web and
  the inconsistent and often poor linking
  techniques used), the common way to find
  information on WWW is to use one of the many
  keyword-based search engines available. These
  search engines operate by continually crawling
  through the web seeking new text pages previously
  undiscovered or updated since last visited, and
  adding these to their respective catalogues. As
  new or updated pages are discovered, they are
  indexed, typically by all words which appear in
  these pages, and this information is added to a
  central index. Users queries sent to a search
  engine are matched against this index in order to
  generate pointers or URLs to the original web
  pages and this is the output of a search.

????? ????? ?????? ?????????? - ????? ???
?? ?????, 10 ????????, 1380
40
??????? ????? - ??????? ??? ???? ?????? ??? ?
????????
Using A Data Fusion Agent for Searching the WWW

• The disadvantages with this situation are that
  the sets of pages indexed by the different search
  engines are overlapping yet none is complete, and
  the information retrieval techniques used by the
  current generation of search engines are
  relatively unsophisticated and ineffective.

????? ????? ?????? ?????????? - ????? ???
?? ?????, 10 ????????, 1380
41
??????? ????? - ??????? ??? ???? ?????? ??? ?
????????
Using A Data Fusion Agent for Searching the WWW
Searching the WWW

• The WWW search engines that we use underlying our
  work are AltaVista, Excite, InfoSeek, Lycos,
  OpenText and WebCrawler. All are based on ranking
  documents/pages based on their retrieval status
  values (RSV), a document score computed by
  summing some variant of a tfIDF weighting of
  search terms and it is the term weighting
  variations, as well as the sets of pages in the
  respective indexes, that set the search engines
  apart from each other.

????? ????? ?????? ?????????? - ????? ???
?? ?????, 10 ????????, 1380
42
??????? ????? - ??????? ??? ???? ?????? ??? ?
????????
Using A Data Fusion Agent for Searching the WWW
????? ...
tfIDF weighting is a term weighting function
where the occurrence of search term i in a
document causes that documents RSV to be
incremented by a term weight defined as tf log
(N/ni) where tf is the frequency of occurrence of
the term in the document, N is the total number
of documents and ni is the number of those
documents indexed by term i. Typically, each
engine represents each page in its catalogue by
the words or word stems which appear in the page.
Some allow a user to specify a phrase as part of
a query and the occurrence of a phrase in a page
causes extra weight to be assigned to such a
page.
????? ????? ?????? ?????????? - ????? ???
?? ?????, 10 ????????, 1380
43
??????? ????? - ??????? ??? ???? ?????? ??? ?
????????
Using A Data Fusion Agent for Searching the WWW
????? ????? ?????? ?????????? - ????? ???
?? ?????, 10 ????????, 1380
44
??????? ????? - ??????? ??? ???? ?????? ??? ?
????????
Using A Data Fusion Agent for Searching the WWW
A Data Fusion Agent for Searching the WWW
Overall System Architecture

• The Fusion system was designed and implemented
  using a client-server architecture. The Fusion
  server is a multi-threaded server which receives
  requests from clients known as Fusion applets. It
  creates new threads to deal with each new
  connection request and the architecture of the
  system is shown in Figure

????? ????? ?????? ?????????? - ????? ???
?? ?????, 10 ????????, 1380
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(No Transcript)
46
??????? ????? - ??????? ??? ???? ?????? ??? ?
????????
????? ????? ?????? ?????????? - ????? ???
?? ?????, 10 ????????, 1380
47
??????? ????? - ??????? ??? ???? ?????? ??? ?
????????
??? ??? Conventional ????? ???????
??? ??? ??? ??? Conventional ????? ???????

• ?? ??? ??? ?? ????? ????? ??? ?????? ??????
• ?????????? ????? ????? ????? ???????
• ???? ????? ????? ??? ????? ???????
• ????? ??? ????? ????? ???????
• ????? ????? OWA
• ??????? ?? ?????? ????????? Bayesian ?? ?????
  ???????
• ??????? ?? ????? ??????? ????? ?? ????? ???????

????? ????? ?????? ?????????? - ????? ???
?? ?????, 10 ????????, 1380
48
??????? ????? - ??????? ??? ???? ?????? ??? ?
????????
????? ????? ???? ? ????? ??????? ? ?????? ????
?? ??????
?????????? ????? ????? ????? ???????
??? ???? ?????? ??? ?? ??????? ?? ??
?????? ?????? ?? ??? ? ???? ?? ????? ?????
?? ????? ????? ?? ????
?? ??? ???? ????. ????? ?????
??????? ????? ??? ?? ????? ??? ????? ????????
???? ?? ??? ????? ?? ????? ???? ????? ?? ??
??????? ?????? ????
?? ?? ?? ????? ???? ?? Fuse ??? ???
?????? ???.
????? ????? ?????? ?????????? - ????? ???
?? ?????, 10 ????????, 1380
49
??????? ????? - ??????? ??? ???? ?????? ??? ?
????????
???? ????? ????? ??? ????? ???????
???? ????? ????? ??? ????? ???????

• ????? ????
• ??????? ( ???? ????? ?????? ??
  
  ???? )
• ??????? ? ??? ????? ????
• ?????? (Neutrality) ???? ???? ?????? ???
  ??
  ?????

???? ????? ??? ????????? ????? ?? ??? ??? ???.
??? ????? ?? ?????? ?? ????? ??????? ?????? ?????
???? ???? ???
????? ????? ?????? ?????????? - ????? ???
?? ?????, 10 ????????, 1380
50
??????? ????? - ??????? ??? ???? ?????? ??? ?
????????
???? ????? ????? ??? ????? ???????

• ???? ????? ???? ???? ????? ???? ????? ?????
  ?? ??? ???????? ?? ???? ????? ?? ??????? ?????
  ??? ???? ???? ?????????? ?????? ??????? ???.

????? ????? ?????? ?????????? - ????? ???
?? ?????, 10 ????????, 1380
51
??????? ????? - ??????? ??? ???? ?????? ??? ?
????????
??? ????? ????? ????? ???????
??? ????? ????? ????? ???????
- ??????? ??????? ??? ????? ???? ???? ?????
??????? ????? ?? ????. ???
??????? ??? ????? ????? ??? ?? ??? ???? ????
????? ?? ?? ???? ??? ??? ?? ????? ??? ????? ??
????. ??? ??? ??? ??????? ?? ?? ??????? ??? ?????
?????? ?? ??? ?? ???? ??? ???
?? ?? ?? ?? ???? ?????? ????? ????? ??
????.?? ???? ?? ????? ??? ???
?? ???? ????? ????? ????? ?? ????? ? ?? ???
? ??????? ??? ?? ?????
???
????? ????? ?????? ?????????? - ????? ???
?? ?????, 10 ????????, 1380
52
??????? ????? - ??????? ??? ???? ?????? ??? ?
????????
??? ????? ????? ????? ???????

• ??????? ?????
• ??? ??????? ?? ???? ??? ????? ?? ???
• ?? ?? ?? ?????? ??? ??? ????? ????? ???? ?????
  ????? ????? ?????? .
• ???? .

????? ????? ?????? ?????????? - ????? ???
?? ?????, 10 ????????, 1380
53
??????? ????? - ??????? ??? ???? ?????? ??? ?
????????
??? ????? ????? ????? ???????
- ??????? ??? ?? ???? ? ??????? ??? ??? ???
??????? ?? ?? ????? ???????? ???? ?? ???? ?
?????? ?? ??????? ??? ? ??????
?? ???? ?? ????.??? ??????? ?? ?? ???? ??? ?????
?? ????   ? ?? ?? ???? ??? ?? ????
???????? ??? ??? ??
????? ????? ?????? ?????????? - ????? ???
?? ?????, 10 ????????, 1380
54
??????? ????? - ??????? ??? ???? ?????? ??? ?
????????
????? OWA
OWA
Decision Fusion
Ordered
Weighted
Averaging
operator
??? ???????
AND
?? ??? ?? ?????
OR
????? ????? ?????? ?????????? - ????? ???
?? ?????, 10 ????????, 1380
55
??????? ????? - ??????? ??? ???? ?????? ??? ?
????????
????? OWA
????? ????? ?????? ?????????? - ????? ???
?? ?????, 10 ????????, 1380
56
??????? ????? - ??????? ??? ???? ?????? ??? ?
????????
????? OWA
Measure Definition

• Orness characterizes the degree to which the
  aggregation is like an or (Max) operation.
• Dispersion how much of the information in the
  arguments is used during an aggregation based on
  W.

????? ????? ?????? ?????????? - ????? ???
?? ?????, 10 ????????, 1380
57
??????? ????? - ??????? ??? ???? ?????? ??? ?
????????
????? OWA
Learning OWA Operators

• OHagan method generate the OWA weights that
  have a predefined degree orness ? and maximize
  the entropy.

????? ????? ?????? ?????????? - ????? ???
?? ?????, 10 ????????, 1380
58
??????? ????? - ??????? ??? ???? ?????? ??? ?
????????
????? OWA
Learning OWA Operators From Observationsavailable
information m samples (observations)
aggregated value Looking for a vector of
OWA weights by minimizing the instantaneous error
ek with respect to weights wi where
????? ????? ?????? ?????????? - ????? ???
?? ?????, 10 ????????, 1380
59
??????? ????? - ??????? ??? ???? ?????? ??? ?
????????
????? OWA

• ConstraintsTransformation

????? ????? ?????? ?????????? - ????? ???
?? ?????, 10 ????????, 1380
60
??????? ????? - ??????? ??? ???? ?????? ??? ?
????????
????? OWA
Unconstrained minimization problem

• Minimize the instantaneous error ek with respect
  to the parameters ?I
• Gradient descent method

????? ????? ?????? ?????????? - ????? ???
?? ?????, 10 ????????, 1380
61
(No Transcript)
62
??????? ????? - ??????? ??? ???? ?????? ??? ?
????????
????? OWA
Example
????? ????? ?????? ?????????? - ????? ???
?? ?????, 10 ????????, 1380
63
(No Transcript)
64
??????? ????? - ??????? ??? ???? ?????? ??? ?
????????
????? OWA
Exponential OWA Operators

• UsefulnessGeneration of OWA weights satisfying a
  given degree of orness.
• Optimistic Exponential OWA Operators
• Definition
• Identities

????? ????? ?????? ?????????? - ????? ???
?? ?????, 10 ????????, 1380
65

• Examples ? 0 W 0 0 ... 1 T , orness
  0 ? 1 W 1 0 0 T , orness 1
• Properties
• Wn w1 w2 ... wn T, Wn 1 v1 v2 vn 1
  T
• - vi wi i 1,2, ,n-1
• - vn ?wn w1wn
• - vn 1 (1-?)wn (1-w1)wn

66
??????? ????? - ??????? ??? ???? ?????? ??? ?
????????
????? OWA

• -
• -
• - Orness function is a monotonically increasing
  function of parameter ? .
• - As the number of arguments increases this
  aggregation becomes more and more orlike.

????? ????? ?????? ?????????? - ????? ???
?? ?????, 10 ????????, 1380
67

• Pessimistic Exponential OWA Operators
• Definition
• Identities
• Examples ? 0 W 0 0 ... 1 T , orness
  0 ? 1 W 1 0 0 T , orness 1
• Properties Wn w1 w2 ... wn T, Wn 1 v1
  v2 vn 1 T
• - vi 1 wi i 2, ,n
• - v2 wnw1 - v1 (1- wn ) w1

68
??????? ????? - ??????? ??? ???? ?????? ??? ?
????????
????? OWA
- Orness function is a monotonically
increasing function of parameter ? . -
Orness function is a monotonically decreasing
function of parameter n. - As the number of
arguments increases this aggregation becomes
more and more andlike.
????? ????? ?????? ?????????? - ????? ???
?? ?????, 10 ????????, 1380
69
??????? ????? - ??????? ??? ???? ?????? ??? ?
????????
????? OWA
????? ????? ?????? ?????????? - ????? ???
?? ?????, 10 ????????, 1380
70
??????? ????? - ??????? ??? ???? ?????? ??? ?
????????
????? OWA

• Given a value of n and a desired degree of orness
  one can simply obtain from Figures a or b the
  associated ? . Then the OWA weights can easily be
  genereted.
• Examplen 5, orness 0.6 gt OWA weights ?n
  5, orness 0.6, Fig.b gt ? 0.8 gt W
  0.41 0.10 0.13 0.16 0.20T gt
  Orness(W) 0.5904n 5, orness 0.9 gt OWA
  weights ?n 5, orness 0.9, Fig.a gt ?
  0.7 gt W 0.70 0.21 0.06 0.02 0.01T
  gt Orness(W) 0.8137

????? ????? ?????? ?????????? - ????? ???
?? ?????, 10 ????????, 1380
71
??????? ????? - ??????? ??? ???? ?????? ??? ?
????????
??????? ?? ?????? ????????? Bayesian ?? ?????
???????
??????? ?? ?????? ????????? Bayesian ?? ?????
??????? ?????? ?? ?????? ??? ????? ???????? ?
????? ?? ????? ??? ?? ?????. ???? ???? ???? ?????
??? ?? ??? ??? ?? ???? ?? ?????? ????? ?????
?? ?? ????? ?? ????? ?? ???? ???? ??
????? ?? ???.
??? ???? ????? ????? ??? ?? ????? ????? ???????
??? ???? ?? ??????? ??????? ?? ????? ?
??????? ???? ????. ?? ??? ????
?????? ?????? ????? ???? ????? ?? ???? ??
????? ?? ????? ????? ????. ?? ?? ??? ????
??? ?????? ? ??? ????? ???????? ?? ???? ?????
?????? ???? ???? ? ? ????? ????? ??
?????? ?????? ????? ???? ????? ?? ????
?????? ???? ???? ????? ?? ?????? ?? ??????
??? ? ???? ?? ?????? ???.
????? ????? ?????? ?????????? - ????? ???
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??????? ????? - ??????? ??? ???? ?????? ??? ?
????????
??????? ?? ?????? ????????? Bayesian ?? ?????
???????
?? ??? ????? ?????? ?? ??????? ?????
?????? ?? ???? ??
?????? ???? ????? ? ?? ????? ??? ???? ?? ???
?? ??? ????? ?????? ?? ????? ???? ??? ?? ?? ????
?? ?????? ??????? ??? ????? ?? ?? ????? ??
??????? ?? ???? ? ?? ??? ???? ?????? ??? ????
?? ??? ?????? ??? ?????? ?? ???
????.
????? ????? ?????? ?????????? - ????? ???
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73
??????? ????? - ??????? ??? ???? ?????? ??? ?
????????
??????? ?? ?????? ????????? Bayesian ?? ?????
???????
????
????? ????? ?????? ?????????? - ????? ???
?? ?????, 10 ????????, 1380
74
??????? ????? - ??????? ??? ???? ?????? ??? ?
????????
??????? ?? ?????? ????????? Bayesian ?? ?????
???????
?? ?????
????? ????? ?????? ?????????? - ????? ???
?? ?????, 10 ????????, 1380
75
??????? ????? - ??????? ??? ???? ?????? ??? ?
????????
??????? ?? ????? ??????? ????? ?? ????? ???????
??????? ?? ????? ??????? ????? ?????? - ???? ??
????? ???????
????? ?????? - ???? ?? ?? ???? ???? ????? ?? ??
??? ????? ??????? ???? ?? Uncertainty ??? ?? ????
???? ????? ?? ????

• ??? ????? ???? ?????? ???? ? ????? ????
  ???????? ??? ????? ?? ???? ????? ??? (Ignorance)
  ????? ?? ????? ?? ??? ??? ?? ???? ?? ?? ?????
  ???????? ?? ??????.

• ??? ????? ????? ?? ?? ??? ????? ?????? ????
  ????? ??????? ???? ?? ??? ????? (Dempsters Rule
  of Combination) ????? ?? ?????. ???? ??? ????
  ????? ???? ????? ??????? ?? ????.

????? ???? ?? ??? ??? ????? ?????? ?? ?????
????? ????? ?????? ?????????? - ????? ???
?? ?????, 10 ????????, 1380
76
??????? ????? - ??????? ??? ???? ?????? ??? ?
????????
??????? ?? ????? ??????? ????? ?? ????? ???????
????? ??????
????? ????? ?????? ?????????? - ????? ???
?? ?????, 10 ????????, 1380
77
??????? ????? - ??????? ??? ???? ?????? ??? ?
????????
??????? ?? ????? ??????? ????? ?? ????? ???????
????? ???? ??????
????? ????? ?????? ?????????? - ????? ???
?? ?????, 10 ????????, 1380
78
??????? ????? - ??????? ??? ???? ?????? ??? ?
????????
??????? ?? ????? ??????? ????? ?? ????? ???????
?????? ??????? ??? ?????? ????? ? ???? ???????
????? ????? ?????? ?????????? - ????? ???
?? ?????, 10 ????????, 1380
79
??????? ????? - ??????? ??? ???? ?????? ??? ?
????????
??????? ?? ????? ??????? ????? ?? ????? ???????
????? ????? ??????
????? ????? ?????? ?????????? - ????? ???
?? ?????, 10 ????????, 1380
80
??????? ????? - ??????? ??? ???? ?????? ??? ?
????????
??????? ?? ????? ??????? ????? ?? ????? ???????
???? ??? ???? ?? ????? ???? ????? ?? ?? ?????
???? ?? ????? ? ???? ?? ?????
???? ??? ?? ????. ????? 2
??? ???? ? ????? 1
??? ????
??? ??? ?? ???? ?? ???? ?? ?????? ?? ??? ??? ????
?? ????? ? ??????. ???? ??
???? ?? ?? ???? ?? ??? ??? ???? ??? ????? (????
?????? ?? ??? ??? ???? ?? ???? ??? ??????) ???
?????? ??? ?? ?????.????? ??? ?????? ????
???? ????? 1 ???
??? ???? ??? ????
???? ????? 2 ???
??? ???? ??? ????
????? ??? ?????? ??? ?????? ?? ??? ???? ?? ?????
? ?? ????.
????? ????? ?????? ?????????? - ????? ???
?? ?????, 10 ????????, 1380
81
??????? ????? - ??????? ??? ???? ?????? ??? ?
????????
??????? ?? ????? ??????? ????? ?? ????? ???????
?????? ?? ????? ???? ?? ?? ?????
?????? ????? ???? ?? ?? ?????
?????? ????? ???? ????? ?? ?????
????? ??? ?? ????? ??????? ?? ????? ?? ?? ??????
?????? ?? ??? ???? ?? ??????? ?? ?? ????? ?????
???? ?????? ????? ??? ?? ?? ???? ??????? ?????
? ?????? ???? ?? ????.
????? ????? ?????? ?????????? - ????? ???
?? ?????, 10 ????????, 1380
82
??????? ????? - ??????? ??? ???? ?????? ??? ?
????????
??? ??? ?????? ????? ???????
??? ??? ?????? ????? ???????

• ????? ??????? ?? ??????? ?? ??????? ????

• ????? ??????? ?? ??????? ?? ???? ??? ????

????? ????? ?????? ?????????? - ????? ???
?? ?????, 10 ????????, 1380
83
??????? ????? - ??????? ??? ???? ?????? ??? ?
????????
??????? ???? ? ?????? ?? ?? ????? ???????
??????? ???? ? ?????? ?? ?? ????? ???????

• ??????? ??????? ???? ????? ??? ???? Sugeno ??
  ??? 1979 ????? ??

• ??? ??????? ? ?? ??? ?????? ??? ???? ???? ??
  ?????? ?? ?? ???? ??????? ?? ???? ????? ??
  ???????? ????? ???? ? ????? ?? ????.

• ?????? ???? ?????? ?????? ????? ?????? ???? ??
  ????? ?????? ????.

• ?? ???? ???????? ??? ????? ? ?? ??????? ??
  ????? ????? ??? .

????? ????? ?????? ?????????? - ????? ???
?? ?????, 10 ????????, 1380
84
??????? ????? - ??????? ??? ???? ?????? ??? ?
????????
??? ????? ????? ????? ???????
?????? ????? ??????? ????
????? ????? ?????? ?????????? - ????? ???
?? ?????, 10 ????????, 1380
85
??????? ????? - ??????? ??? ???? ?????? ??? ?
????????
??? ????? ????? ????? ???????
?????? ????? ??????? ????
????? ????? ?????? ?????????? - ????? ???
?? ?????, 10 ????????, 1380
86
??????? ????? - ??????? ??? ???? ?????? ??? ?
????????
??? ????? ????? ????? ???????
?????? ????? ??????? ????
????? ????? ?????? ?????????? - ????? ???
?? ?????, 10 ????????, 1380
87
??????? ????? - ??????? ??? ???? ?????? ??? ?
????????
??? ????? ????? ????? ???????
?????? ????? ??????? ????
??????? ??? ???? Sugeno ? Choquet ?? ?? ?????
????? ?????.???? ??????? ???? Sugeno ?? ????
??????? ??? ??? ??? Min ? Max ??? ????? ??? ???.
?? ????? ?? ??????? ???? Choquet ?? ??????? ???
??? ????? ???? ?? ???.
????? ????? ?????? ?????????? - ????? ???
?? ?????, 10 ????????, 1380
88
??????? ????? - ??????? ??? ???? ?????? ??? ?
????????
??? ????? ????? ????? ???????
????? ??????? ???? ?? ??????? ??? ?????? ?????
???????
?? ??????
????? ????? ?????? ?????????? - ????? ???
?? ?????, 10 ????????, 1380
89
??????? ????? - ??????? ??? ???? ?????? ??? ?
????????
??? ????? ????? ????? ???????
????? ??????? ???? ?? ??????? ??? ?????? ?????
???????

• ?????? ? ??????? ??? ??? ????? ???? ?? ??
  ??????? ???? Sugeno ?????

????? ????? ?????? ?????????? - ????? ???
?? ?????, 10 ????????, 1380
90
??????? ????? - ??????? ??? ???? ?????? ??? ?
????????
??? ????? ????? ????? ???????
????? ????? ?????? ?????????? - ????? ???
?? ?????, 10 ????????, 1380
91
??????? ????? - ??????? ??? ???? ?????? ??? ?
????????
??? ????? ????? ????? ???????
????? ??????? ?? ??????? ?? ???? ??? ????

• An artificial neural network can be explained
  as a web-like, information processing structure
  that emulates the human brains own learning and
  decision making process.

• A neural network uses many simple elements
  called neurons (or processing nodes) to collect
  and correlate information.These neurons are
  connected by synapses that ascribe a weight to
  each neurons output and then forward it, in a
  unidirectional path, to the next set of neurons.
  A neuron may have many inputs, but it has only a
  single output (Concept of Fusion)

????? ????? ?????? ?????????? - ????? ???
?? ?????, 10 ????????, 1380
92
??????? ????? - ??????? ??? ???? ?????? ??? ?
????????
??? ????? ????? ????? ???????
????? ????? ????? ?? ???? ????

• ?The neurons characteristics

The equations that define what a neuron will do.

• The learning rule

The guide as to how the weights between various
neurons will change according to the stimuli they
receive.

• ?The network topology

The manner in which the neurons are connected
????? ????? ?????? ?????????? - ????? ???
?? ?????, 10 ????????, 1380
93
??????? ????? - ??????? ??? ???? ?????? ??? ?
????????
?????? Information Fusion ?? ?? ???? ???????
?????? Data/Information Fusion ?? ?? ???? ???????
B. Moshiri , A. Moghaddasi , A.
Eydgahi   Associate prof.
Ph.D. student Associate
prof.    Dept. of Electrical Eng., Univ.
Tehran, Tehran, Iran and School of Intelligent
Systems (S.I.S), Institute for Studies in
Theoretical Physics and Mathematics(I.P.M) P.O
Box 19395-5746, Tehran, Iran. moshiri, amoghadd
_at_karun.ipm.ac.ir   Dept. of Engineering and
Aviation Sciences, University of Maryland Eastern
Shore, Princess Anne, MD 21853,
USA aeydgahi_at_mail.umes.edu
Presented at EuroFusion99   5th - 7th October
1999   Stratford-upon-Avon, U.K.
????? ????? ?????? ?????????? - ????? ???
?? ?????, 10 ????????, 1380
94
??????? ????? - ??????? ??? ???? ?????? ??? ?
????????
?????? Information Fusion ?? ?? ???? ???????
Layout
Introduction
Design Implementation
TAHAB Agents
Implementing OWA Information Fusion
Numerical Example
Conclusion
????? ????? ?????? ?????????? - ????? ???
?? ?????, 10 ????????, 1380
95
??????? ????? - ??????? ??? ???? ?????? ??? ?
????????
?????? Information Fusion ?? ?? ???? ???????
Introduction
TAHAB is a business intelligence solution
developed for Bank Melli Iran in order to analyze
the data generated by its daily activities, and
to describe the performance of the intelligent
agents utilized in that system. The purpose of
TAHAB is to convert the huge amount of
line-of-business and historical data into useful
knowledge that can help the managers and experts
make informal decisions. The proposed solution
will resolve the centralization vs.
decentralization issue in dealing with data
throughout the organization, and provides a
powerful tool for generating and managing
knowledge within Bank Melli Iran.
????? ????? ?????? ?????????? - ????? ???
?? ?????, 10 ????????, 1380
96
??????? ????? - ??????? ??? ???? ?????? ??? ?
????????
?????? Information Fusion ?? ?? ???? ???????
Design Implementation
????? ????? ?????? ?????????? - ????? ???
?? ?????, 10 ????????, 1380
97
??????? ????? - ??????? ??? ???? ?????? ??? ?
????????
?????? Information Fusion ?? ?? ???? ???????
Implementing OWA Information Fusion
????? ????? ?????? ?????????? - ????? ???
?? ?????, 10 ????????, 1380
98
??????? ????? - ??????? ??? ???? ?????? ??? ?
????????
?????? Information Fusion ?? ?? ???? ???????
Get Decisions D(i) From All Agents, i 1n
Sort D(i), Name it A(i)
is the Fused Value ( Decision ), t is the time
- Implementation of OWA operator
Save F(t)
????? ????? ?????? ?????????? - ????? ???
?? ?????, 10 ????????, 1380
99
??????? ????? - ??????? ??? ???? ?????? ??? ?
????????
?????? Information Fusion ?? ?? ???? ???????
Items / Subjects A B C
D . . .
User Modeler Agent 2
User Modeler Agent 1
. . .
Profile 1
Profile 2
Managers Level Managers
Level ---------------------------
---------------------------
Item Interest Deg.
Item Interest Deg.
---------------------------
--------------------------- A
much A
normal B a few
B at all C
very much C
much .
.
 
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?? ?????, 10 ????????, 1380
100
??????? ????? - ??????? ??? ???? ?????? ??? ?
????????
?????? Information Fusion ?? ?? ???? ???????
Decision output from each Agent
The effect of time is considered in the developed
software
????? ????? ?????? ?????????? - ????? ???
?? ?????, 10 ????????, 1380
101
??????? ????? - ??????? ??? ???? ?????? ??? ?
????????
?????? Information Fusion ?? ?? ???? ???????
Name - - - - Managing Hierarchical Code - - -
-   Item

Interest Level
------------------

---------------------- Compare between US Dollar
and Euro
very much Changes in oil price

much Compare between US
Dollar and Rial
normal Inflation

a
few Discussions related to budget planning in the
parliment at all Rubbery
from bank branches
much News
about other banks

normal
Managers profile, created with user modeler
agent for some items
????? ????? ?????? ?????????? - ????? ???
?? ?????, 10 ????????, 1380
102
??????? ????? - ??????? ??? ???? ?????? ??? ?
????????
?????? Information Fusion ?? ?? ???? ???????
Managers Hierarchical Code Interested Level
A At all
B A few
B Much
C Normal
C Very much
C Very much
D Normal
D Very much
D Much
D Normal
A sample of interested levels from each manager
about Inflation
????? ????? ?????? ?????????? - ????? ???
?? ?????, 10 ????????, 1380
103
??????? ????? - ??????? ??? ???? ?????? ??? ?
????????
?????? Information Fusion ?? ?? ???? ???????
, ,
,
, ,
, ,
,
, , and ,
.   OWA weights
0.0, 0.0, 0.0, 0.2, 0.2, 0.2, 0.2, 0.2, 0.0
and 0.0, respectively.   Final Fused
Decision  
????? ????? ?????? ?????????? - ????? ???
?? ?????, 10 ????????, 1380
104
????? ?????? ?? ???? ?????? ????? ?? ????? ?????
???? ?? ??? ??????? ??????? ?? ???? ??? ????
??????? ????? - ??????? ?????? ??? ? ????????

• Architecture Design of an Intelligent Information
  Fusion Agent for Information retrieving from
  Dynamic Environments

105
??????? ????? - ??????? ??? ???? ?????? ??? ?
????????
????? ?????? ???? ?????? ???? ???
??????? ????? ??????? ?? ??????? ?? ????? ???????
???? ???? ( OWA )

• ?????? ????? ?? ????? ?????? ???? ????? ?????

• ?????? ???????? n-gram ??? ???? ?????
  ?????(????? ???? ? ?????? ?? ???? ?? ????? ??
  ?????? ???)

?? ???? ?????? ??? ??? ?? ?? ??? ?? ????? n-gram
??? ???? ????? ?????? ???? ?? ???? ?? ?? ???????
?? ????? OWA ?? ????? ?? 2 ?????? ????? ??
????? ??? ??? ????? OWA ?? ??????? ?? ????? ????
????? ???? ????? ?? ?????
106
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107
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108
(No Transcript)
109
Papers Published

• 1. B.Moshiri, T.K.Moghaddam , "Symbol Recognition
  in GIS Maps Using Genetic Algorithm (Part 1,
  Pinciples) ", Researches in Geography, No. 34,
  136-156 (1998).
• 2. B.Moshiri , T.K.Moghaddam , "Symbol
  Recognition in GIS Maps Using Genetic Algorithm
  (Part 2, Application) ", Researches in Geography,
  No. 35 , 109-123 (1998).
• 3. M.R. Asharif, R.Hosein Nezhad, B.Moshiri, "
  Environment Mapping for Mobile Robots Navigation
  Using Sensor Fusion A Dempster-Shafer Reasoning
  Theory Approach", Journal Article in Bulletin of
  Faculty of Engineering, University of the
  Ryukyus, No. 60, 127-132 (Sep. 2000).
• 4. B. Moshiri, M.R. Asharif, R. HoseinNezhad, "
  Pseudo Information Measure A new concept for
  extension of Bayesian Fusion in robotic map
  building", Information Fusion, Vol. 3, No.1,
  51-68 (March 2002).
• 5. B. Moshiri, M. Najafi, " Application of sensor
  data fusion on guidance and tracking of
  intelligent ship", Journal of Faculty of
  Engineering, University of Tehran , JFE, Vol. 35,
  No. 4, 463-474 (March 2002).
• 6. B. Moshiri, M. R. Asharif, R. HoseinNezhad, "
  A new approach to self-localization for mobile
  robots using sensor data fusion", IJE
  Transactions B Applications, Vol. 15, No.2,
  145-156 (July 2002).
• 7. M. R. Asharif, B. Moshiri, R. HoseinNezhad, "
  Intelligent mobile robot perception by using a
  new concept for sensor data fusion Pseudo
  Information Measure", ISA Transactions, Vol. 41,
  No. 3, 283-301 (July 2002).
• 8. R.HoseinNezhad, B.Moshiri, M.R. Asharif,
  "Integration of Pseudo Information Measures, A
  New Method for Sensor Data Fusion", Journal of
  Faculty of Engineering, University of Tehran,
  JFE, Vol. 36, No. 3, 321-331 (Dec.2002).
• 9. R. HoseinNezhad, B. Moshiri, M. R. Asharif, "
  Improved pose estimation for mobile robots by
  fusion of odometry data and environment map",
  Journal of Intelligent and