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A Day In a City

A Day In a City. Academic Advisor: Prof. Ronen Brafman Team Members: Ran Isenberg Mirit Markovich Noa Aharon Alon Furman. Introduction. When most people go on a vacation or a day trip, they usually plan a specific schedule. Planning a day trip isn't always an easy task.

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A Day In a City

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  1. A Day In a City Academic Advisor: Prof. Ronen Brafman Team Members: Ran Isenberg Mirit Markovich NoaAharon Alon Furman

  2. Introduction • When most people go on a vacation or a day trip, they usually plan a specific schedule. • Planning a day trip isn't always an easy task. • “A Day in city“ project strives to make finding the best schedule and the best activities for each user's unique taste as easy as double clicking.

  3. Current Situation Friends Lametayel.co.il Other Sources Lonely Planet

  4. The Problem • The “average Joe” needs to search, plan and integrate many information pieces from numerous sources. • It is not customized to the average Joe’s style or desires. The “average Joe” has to plan the schedule by himself. • It takes a lot of time and sometimes it can be very confusing (contradicting data) and not easy.

  5. Purposed Solution • A system that recommends itineraries of activities for a day trip in a city by using background knowledge & information about the user (Average “Joe”) it obtains during the session in order to suggest an itinerary.

  6. Main Challenges • Find a set of activities the user is likely to prefer. • Find a legal schedule – solve a CSP • Find optimal schedule according to user preferences. • Find the “best” questions to ask the user.

  7. Purposed Solution – How? • Modeling the problem domain and user preferences by creating a corresponding Influence diagram. • User preferences will be determined by answering questions, ranking activities, searching for activities and manual deletion/alteration of activities. • Using an algorithm in order to find the desired schedule. • Usage of a heuristic to find the best questions to ask. • Communication with the user is done via a web interface.

  8. Model example

  9. Algorithm • The solver receives a list of activities and executes the algorithm N times, with a different ordering of the activities in each execution. • Each activity in the algorithm will be represented by an agent, who will choose a time slot in the schedule based on the ordering of the agents. • After the last agent has chosen a time slot, the value of the schedule is computed and the best one so far is saved.

  10. Heuristic • While choosing the order of the activities, the solver will give a preference to activities with higher “likeness” value. • We face 2 problems with this approach: • On the one hand, we are not interested in schedules containing the same activities with highest “likeness”. • On the other hand, a random permutation of the activities is also not good as it completely ignores the “likeness” value. • We solve the above problems by using a heuristic described on the next slide.

  11. Heuristic (Cont.) • In the first round the algorithm will receive the activities ordered by their likeness value. • In each round that follows the solver will change the last order by performing M random swaps. • Activity with likeness value x may be swapped with another activity with likeness value [x,x+1], thus creating a different permutation of activities while still giving some preference to activities with higher “likeness” value.

  12. System Architecture Database

  13. System Architecture - Cont. • GUI interface website – Accessible from an internet webpage • GUI controller –It is the middle man between the projects' core and the user GUI and thus the user himself. • Server Computational unit (SCU) – Runs the various algorithms on the City Model according to the user preferences and input received from the GUI controller and sends the results back to it. • City Model – A predefined influence diagram with all the activities, probabilities, type of activities and user preferences. It is be based on the API of Genie & Smile.

  14. System Architecture - Cont. •  Database – Holds information about the places that the user can visit: name, opening hours, time to get from one place to the other etc. Also holds a set of questions that the program can ask the user. • Final Schedule – The final result of the computational unit. It consists of the top valued activities that fit into a day and takes into account the time needed to travel between them.

  15. Website’s Main Functions 1. Answer a question. 2. Rank an activity 3. Change the duration of an activity in the schedule. 4. Remove an activity from the schedule. 5. View activity’s details. 6. Search for an activity. 7. Change day. 8. Change city.

  16. GUI

  17. Questions?

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