Data mining for personal navigation
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Data Mining for Personal Navigation. Gurushyam Hariharan Pasi Fränti Sandeep Mehta DYNAMAP PROJECT University of Joensuu, FINLAND http://cs.joensuu.fi/pages/franti/dynamap /. Personal Navigation. Location information is used for: Plotting location of user on a map

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Data Mining for Personal Navigation

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Data mining for personal navigation

Data Mining for Personal Navigation

Gurushyam Hariharan

Pasi Fränti

Sandeep Mehta

DYNAMAP PROJECT

University of Joensuu, FINLAND

http://cs.joensuu.fi/pages/franti/dynamap/


Personal navigation

Personal Navigation

Location information is used for:

  • Plotting location of user on a map

  • Navigational guidance to given destination

  • Provide data related to location


Data mining required

Data mining required

  • For retrieval of location-related information from www (Web mining)

  • For Task-oriented data extraction from web documents

  • For user profiling (additional parameters for defining what is relevant)


Overall scheme

Overall Scheme


Traditional definition of r elevance

Traditional definition of relevance

  • Keyword

    • Web-Based Search Engines

  • User Profile

    • Past Behavior of self and community define the profile

    • Automatic suggestions (e.g. Amazon.com proposed other “relevant” books)


Novel approach to data web mining for a mobile user

Novel Approach to Data(Web)-Mining for a MOBILE USER

  • Key is to find RELEVANT information

  • Re-defining Relevance for Mining Web

  • Relevance depends on

    • User request at the moment

    • User preferences

    • Relevance = Traditional Parameters (Keywords, Profile) + LOCATION


Additional relevance factor location

Additional relevance factor: Location

  • Co-ordinates of mobile User  City/Street address

  • Relevance=Location + Keywords (+Profile)

  • For example:

    • Helsinki downtown

    • “Restaurant”

    • “Budget prize” “Vegetarian”


Issues for a personal navigation system with the new definition

Issues for a Personal Navigation System with the NEW Definition

  • Spot the client on the Globe

  • Co-ordinate  Location interconvertion

  • Data Extraction: Task oriented search of web

  • Scalability (in accordance with User’s Mobile Device)

  • User profile learning

  • Pass Relevant Information to the Mobile User


Possible use scenario

Possible use scenario


Scenarion including user profiling

Scenarion including user profiling


We regret

WE REGRET...

... the absence of the authors.

  • Gurushyam did not get VISA to USA

  • Pasi is busy elsewhere and could not change his plans in such short notice:


T hank you

THANK YOU !

For more information, contact:

  • [email protected]

  • http://cs.joensuu.fi/pages/franti/dynamap/


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