Data Mining for Personal Navigation Gurushyam Hariharan Pasi Fränti Sandeep Mehta DYNAMAP PROJECT University of Joensuu, FINLAND

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Presentation transcript:

Data Mining for Personal Navigation Gurushyam Hariharan Pasi Fränti Sandeep Mehta DYNAMAP PROJECT University of Joensuu, FINLAND

Personal Navigation Location information is used for: 1.Plotting location of user on a map 2.Navigational guidance to given destination 3.Provide data related to location

Data mining required 1.For retrieval of location-related information from www (Web mining) 2.For Task-oriented data extraction from web documents 3.For user profiling (additional parameters for defining what is relevant)

Overall Scheme

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 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 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 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

Scenarion including user profiling

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:

THANK YOU ! For more information, contact: