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Weekend Planner

Weekend Planner. CS4244 Group 6. Weekend Planner. Introduction. Introduction. Nitin’s Part. Weekend Planner. Itinerary Planning. Itinerary Planning. Itinerary – sequence of events and travels From start-time to end-time start-location to end-location

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Weekend Planner

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  1. Weekend Planner CS4244 Group 6

  2. Weekend Planner Introduction

  3. Introduction • Nitin’s Part

  4. Weekend Planner Itinerary Planning

  5. Itinerary Planning • Itinerary – sequence of events and travels • From start-time to end-time start-location to end-location • Constraints: budget, time and location • Try to find the best combination of events given the above constraints

  6. Divide and Conquer • Divide and conquer • Recursive tree-search approach • Basic idea: Divide an itinerary into left and right children and plan these itineraries recursively. Merge them to form a complete itinerary

  7. Start-up • Start with root node • Query event-selection interface (defined later) to get n (<=5) best events • Form n child itineraries with one event each • Start recursive itinerary generation

  8. Recursive Process • Select an event for an itinerary • Divide it into left and right children with new constraints • Plan them recursively • Leaf node: no more events possible (run out of money or time) • Start merging up

  9. Merge-up • Generate all combinations of left + right + parent to form new “complete” itineraries • Only complete itineraries take part in merging up process • Stop when merged up to root • Display 5 best itineraries (more on itinerary evaluation later)

  10. Implementation - Classes • Class EVENTS_SELECTED • (slot id) • (slot ready) • (slot start_time) • (slot end_time) • (slot start_location) • (slot end_location) • (slot budget) • (multislot already-chosen) • (multislot event-list) • Class Itinerary: • (slot parent) (slot child) • (slot complete (default FALSE)) • (multislot event-list) • (multislot travel-list) • (slot preference-rating (default 0)) • (slot total-cost) • (slot start-time) • (slot end-time) • (slot start-location) • (slot end-location) • (slot budget) ;;Some other flags required for processing

  11. Implementation - Rules • Rules: The search process is mainly guided by the following rules: • EVENT_QUERY • CREATE_CHILD_NODES • MERGE • MARK_READY

  12. Implementation - Rules • EVENT_QUERY • LHS: new itinerary is formed • RHS: • create EVENTS_SELECTED object • Set the start-end time, location, budget etc. • Set “ready” flag to false

  13. Implementation - Rules • CREATE_CHILD_NODES • LHS: EVENTS_SELECTED object with “ready” attribute = TRUE • RHS: • For each event in the event-list create a child node • If event list is empty then this is a leaf itinerary hence add travel

  14. Implementation - Rules • MERGE • LHS: left and right child itineraries with the same parent • RHS: • Merge the left and the right child with the parent to form a “complete” itinerary • Compute preference rating (more on this later)

  15. Weekend Planner Events Selection

  16. Events Selection • Component • Receive the request from itinerary • Budget, time slot, start location, end location • Make event instances involving selection mechanism • Sort and return

  17. Events Selection • Make Event Instances • Event types • Event instance • (defclass EVENT_INSTANCE (is-a USER) • (role concrete) • (slot start_time (default [start])) (slot end_time (default [end])) (slot duration) • (slot event_type) (slot description) • (slot location (default [nus])) • (slot expense (default 0)) (slot preference(default 0)

  18. Events Selection • Selection Mechanism • Hard constraints • Weather for parks • Adult certification for movies • Temporal and budget possibility • Fix-time events • Non-fix-time events

  19. Events Selection • Probability-Based Preferences • Events type preference • Classified based on age and gender • Example: shopping for females • Temporal preference • Example: ordinary lunch / dinner time • Event instance preference

  20. Events Selection • Event Instance Preference • Place preference • Based on public comments • Content preference • Preference type: Movie: genre • Preference instance: (Action, Comedy, Animation) • Preference value: (0.5 , 0.8 , 0.5)

  21. Events Selection

  22. Events Selection • Preference Combination • Event instance preference combination (geometric mean) • Client’s event preference (product) Pinstance = pow ( ∏ pi * Pplace , 1/n+1) Pevent = Pinstance * Ptype * Ptemporal

  23. Events Selection • Sort And Return • Sort all the event instances based on Pinstance • Return the best five ones for making itineraries

  24. Weekend Planner Travel Mode Selection

  25. Requirenments • Check Possibility of Event • Travel Mode Selection

  26. Classes • Location • Mode • Travel

  27. Possibility checking • During Event Selection • First case: Time is fixed • Second case: Time is not fixed

  28. Travel mode selection • Leaf Case of Itinerary Planning • Optimize for Cost

  29. Weekend Planner Itinerary Selection

  30. Requirenments on Preference Rating • Containing Events • Travel Time • Waiting Time

  31. Final Preference Rating • Weighted Average over time • Travelling and Waiting have a Negative Preference Rating • Waiting has a Lower Rating than Travelling

  32. Weekend Planner User Interface

  33. User Interface • Amit’s part

  34. Weekend Planner Demo

  35. Thankyou!

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