1. Team Members: Brian Leung Glenn Musa Min Sock Park Jihyeon Seo -Your Local Past, Present and Future-

2. Introduction RegionTrend is a web-based service that provides microeconomic data analysis within a region (Arizona) Objective: To provide visual data representation of various correlations between cities and states through web mining techniques that help users gain better understanding of local commercial activities Features include: Job growth Housing analysis Service related activities within cities Sales activities within cities

3. Business Model Freemium Model – Free users have access to limited datasets (3 months historical data) – Paid users have full access to all historical data and predictive analysis for $3.99/month Display Ads – As the website expands, display ads will be an alternative approach to generate revenue

4. Functionalities Visualizations Regression Analysis Top 10 Jobs per city or Arizona Top 10 Services Jobs trend and analytics Housing value data and forecast Apartment Rental value trends Local Commerce expected average values Temporal Motion Chart for local Economic activities

5. Competitors City-Data.com No Intuitive UI No Region by Region analysis Lack analytics No links to Social Media CNN Moneys Not at a micro-economic scope No city ranking Does not reflect micro activities

6. System Architecture APIs 1.Facebook login 2.Facebook comment 3.Facebook like 4.Facebook connect 5.Twitter Tweet 6.Google Maps 7.Google Visualization 8.Google Fonts (web fonts) 9.Google Translate 10.Paypal 11.Indeed Jobsearch 12.Nivo Slider 13.J-Pop up 14.Flickr 15.Apache Common Math Collected Data (Demo 1) : Phoenix: 242,760 Tucson: 112,282 Yuma: 12,555 Mohave: 17,603 Sierra Vista: 8,900 Flagstaff: 17,282 Prescott: 20,178 Show Low: 3,957 Total: 435,517 Collected Data (Demo 2) : Phoenix: 552,754 Tucson: 254,790 Yuma: 23,511 Mohave: 30,499 Sierra Vista: 14,405 Flagstaff: 36,452 Prescott: 33,969 Show Low: 6,880 Total: 953,260

7. Screen Shots: Home Page

8. Screen Shots: Analytics

9. Screen Shots: Analytics Cont.

10. Group Contribution Glenn Musa Jihyeon Seo Brian Leung Min Sock Park Front End Design, API implementation, Data Mining Web Mining, API Implementation, Data Visualization, Middleware Implementation Web Mining, DM Algorithm, Data Visualization, Predictive Analysis Database Development, API implementation, Back End Design

11. Future Better Accuracy – Collecting more data will increase the accuracy on our regression analysis Additional Features: – More in-depth data analytics – Auto Spidering by using script and scheduler Expand Data Sources: – Collect data from other data source such as City-Data, IRS data Expandability: – Expand this service nation wide for every cities minable on Craigslist – Expand internationally The More Data We Have, The More Powerful We Get!

12. “Our goal is to provide analytics to the cities and regions around our users, so that they could understand them better and make better decisions” - AZRegionTrend