Academic Advisor: Prof. Ronen Brafman Team Members: Ran Isenberg Mirit Markovich Noa Aharon Alon Furman.

Slides:



Advertisements
Similar presentations
CRM project. Agenda Introduction About Project Modules.
Advertisements

Short introduction to the use of PEARL General properties First tier assessments Higher tier assessments Before looking at first and higher tier assessments,
MIDDLE EAST TECHNICAL UNIVERSITY COMPUTER ENGINEERING DEPARTMENT CENG 491 – COMPUTER ENGINEERING DESIGN I DSK4BRM.
Problem Statement Key Project Requirements Input Page Schedule & Resources Output Page System Testing Conclusion The general problem lies with residents.
Web E’s goal is for you to understand how to create an initial interaction design and how to evaluate that design by studying a sample. Web F’s goal is.
Write Your Project Title Here VU Logo Here Group Members Introduction Write your group members introduction here with names and VU Id.
WEST Presented By 3s. Introduction Project Overview Project Overview Use Case Diagram Use Case Diagram Domain Model Diagram Domain Model Diagram UI for.
INVESTMENT GAME IN SOCIAL NETWORK Academic Advisor: Dr. Yuval Alovici Professional Advisor: Dr. Mayer Goldberg Team Members: Ido Bercovich Dikla Mordechay.
Technical Advisor : Mr. Roni Stern Academic Advisor : Dr. Meir Kalech Team members :  Amit Ofer  Liron Katav Project Homepage :
SOCIAL NETWORK INFORMATION CONSOLIDATION Developers:  Klasquin Tomer  Nisimov Yaron  Rabih Erez Advisors:  Academic: Prof. Elovici Yuval  Technical:
1 A Vehicle Route Management Solution Enabled by Wireless Vehicular Networks Kevin Collins and Gabriel-Miro Muntean IEEE INFOCOM 2008.
Electrical and Computer Engineering Vitaly Gordievsky Alex Trefonas Scott Richard Matt Beckford Final Project Review.
Academic Advisor: Prof. Ronen Brafman Team Members: Ran Isenberg Mirit Markovich Noa Aharon Alon Furman.
Business trip scheduler ARD Lital Badash Yanir Quinn Eran Banouz.
Two main requirements: 1. Implementation Inspection policies (scheduling algorithms) that will extand the current AutoSched software : Taking to account.
People Technical AdvisorsAcademic AdvisorFinal Project By Prof. Shlomi Dolev Prof. Ehud Gudes Boaz Hilemsky Dr. Aryeh Kontorovich Moran Cohavi Gil Sadis.
Academic Advisor: Prof. Ronen Brafman Team Members: Ran Isenberg Mirit Markovich Noa Aharon Alon Furman.
1 Chapter 9 Rules and Expert Systems. 2 Chapter 9 Contents (1) l Rules for Knowledge Representation l Rule Based Production Systems l Forward Chaining.
SOCIAL NETWORK INFORMATION CONSOLIDATION Developers:  Klasquin Tomer  Nisimov Yaron  Rabih Erez Advisors:  Academic: Elovici Yuval  Technical: Lesser.
Business Trip Scheduler Application Design Document Lital Badash Eran Banous Yanir Quinn Academic Advisor: Prof. Ehud Gudes amdocs.
Electrical and Computer Engineering PeopleFinder Vitaly Gordievsky Alex Trefonas Scott Richard Matt Beckford Comprehensive Design Review.
(NHA) The Laboratory of Computer Communication and Networking Network Host Analyzer.
Multi-criteria infrastructure for location-based applications Shortly known as: Localization Platform Ronen Abraham Ido Cohen Yuval Efrati Tomer Sole'
SmartSQL AlfaTech Software Solutions Application Requirements Document  Radi Bekker  Vladimir Goldman  Marina Shaevich  Alexander Shapiro Team Members:
Generic Simulator for Users' Movements and Behavior in Collaborative Systems.
Santa Clara University School of Law
1 Develop a large software with IBM Rational ® Software Engineering Semester Project Chih-Hong Jeng & Farn Wang fall 2006.
Final Year Project Presentation E-PM: A N O NLINE P ROJECT M ANAGER By: Pankaj Goel.
Prof. Vishnuprasad Nagadevara Indian Institute of Management Bangalore
Project Proposal: Academic Job Market and Application Tracker Website Project designed by: Cengiz Gunay Client: Cengiz Gunay Audience: PhD candidates and.
Research on cloud computing application in the peer-to-peer based video-on-demand systems Speaker : 吳靖緯 MA0G rd International Workshop.
Genetic Algorithm.
Chapter 6 System Engineering - Computer-based system - System engineering process - “Business process” engineering - Product engineering (Source: Pressman,
CP Summer School Modelling for Constraint Programming Barbara Smith 1.Definitions, Viewpoints, Constraints 2.Implied Constraints, Optimization,
Shiran Alush Shai Kerer Dor Altshuler Academic instructor: Prof. Ronen Brafman The Decider Group Decision Making A Application D Design D Document.
Automatically Capturing Data from SCADA to the Maintenance System
Implicit An Agent-Based Recommendation System for Web Search Presented by Shaun McQuaker Presentation based on paper Implicit:
Project 3 Cookie Cutters Kevin Huynh Sean Tsusaki Jordaniel Wolk.
A Genetic Solution to the Travelling Salesman Problem Ryan Honig.
Professional IT Roles Investigate IT professional roles. Find out what each role involves, what the job entails. Identify what personal qualities are needed.
Online Friends’ Community Presented by: Stuart Monaghan HND in Computing th May 2002.
Network Monitoring Through Mobile (MOBTOP) Developed By : Akanksha Jain. (102199) Deepika Reddy (102210) Team Name: Beans Guided By: Prof. Robert Zhu SUBMITTED.
BTS Business Trip Scheduler Lital Badash Eran Banous Yanir Quinn Academic Advisor: Prof. Ehud Gudes Technical Advisor: Mr. Eugene Kovalyov (Amdocs) Mr.
Problem Statement: Users can get too busy at work or at home to check the current weather condition for sever weather. Many of the free weather software.
Graphing and statistics with Cacti AfNOG 11, Kigali/Rwanda.
Search Engines.
$aveZone Milestone 3 $aveZone Milestone 3 Fifth team: Dima Reshidko Oren Gafni Shiko Raboh.
Course Conclusion. Agenda Summing up by Tom Handing over to Ellen Your presentations Typo3 // css stuff Information about exam.
T Iteration demo T Iteration Demo Team Balboa I1 - Iteration
Interrelationship Digraphs
CSA Revision Session Introduction to the exam Exam length is 2 hours You will have a total of 120 minutes to: read the questions, choose which ones to.
Chapter 4 Decision Support System & Artificial Intelligence.
Management System For Graduate Students Projects Day Presentation – June 2011.
Systems design for scheduling: Open Tools Patrick De Causmaecker, Peter Demeester, Greet Vanden Berghe and Bart Verbeke KaHo Sint-Lieven, Gent, Belgium.
The Information School at the University of Washington INFO 440: Information System Design * Fall 2004 UW Majors Guide Design Process and Results Pei-Wen.
D R A T D R A T ABSTRACT Every semester each department at Iowa State University has to assign its faculty members and teaching assistants (TAs) to the.
Consultant Presentation Group B5. Presentation Outline Introduction How to design by Group A5 Future Data Structure Interface Future Conclusion.
Biologically Inspired Computation Ant Colony Optimisation.
Data Consolidation: A Task Scheduling and Data Migration Technique for Grid Networks Author: P. Kokkinos, K. Christodoulopoulos, A. Kretsis, and E. Varvarigos.
Uniform Resource Locator URL protocol URL host Path to file Every single website on the Internet has its own unique.
LOGO Song Identification System Team members: Nguyen Ngoc Tan Ho Vinh Thinh Nguyen Huu Duy Nguyen Hoang Diep Nguyen Trong Dai Le Thanh Tung Supervisor:
Ranking: Compare, Don’t Score Ammar Ammar, Devavrat Shah (LIDS – MIT) Poster ( No preprint), WIDS 2011.
Proposal for Term Project
A fully self-contained Rubik’s Cube solver
Computer Science cpsc322, Lecture 14
Senior Project, 2018, Spring To-do List Optimizer 1.0
CIS 488/588 Bruce R. Maxim UM-Dearborn
Case Study 1 By : Shweta Agarwal Nikhil Walecha Amit Goyal
NOTICE! These materials are prepared only for the students enrolled in the course Distributed Software Development (DSD) at the Department of Computer.
DIAGRAM IT!.
Presentation transcript:

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. “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.

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

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.

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.

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.

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.

Model example

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.

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.

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.

System Architecture Database

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.

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. System Architecture - Cont.

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.

GUI

Questions?