The document proposes the design of a Select Input Recommender (S.I.R.) System that allows users to easily create recommendation systems for specific niches at low cost. It will use a hybrid filtering approach, combining content-based and collaborative filtering. The web application will have five subsystems: a user interface, web server, recommendation algorithm, database, and web crawling utilities. It will be hosted on Amazon Web Services and implemented using Struts, Spring, and Java Persistence API frameworks. The team of five students will each have responsibilities for different aspects of the project and meet regularly to collaborate.

1. Select Input Recommender
(S.I.R) System
Hilary Aben, Seth Brady, Christopher Trask,
Kang Du, Yiming Chen

2. Contents
● Problem and goals
● Research
● Design
● Project Management

3. Problem Background
● Most current recommendation systems are
general in scope
● In addition, many others require much time
to set up

4. Needs Statement
There is a need for an recommendation
systems that cover specific niches and are
easy to set up

5. Goal
Create an application that allows users to
create recommendation systems for specific
niches at low time and financial costs.

6. Research
• Content-based filtering
• Recommends based upon qualities of product
• Pandora
• Collaborative filtering
• Recommends based upon similar user preferences
• Amazon
• Hybrid
• Recommends based upon both content and users
• Netflix

7. Alternative Solutions
● Personally hosted web server
● Crawling the web in real time
● Using a python based web server framework
● Android Application
● Collaborative Recommender
● Content-Based Recommender

8. Proposed Design
● Web application
● Hosted by Amazon Web
Services( AWS )
● Hybrid filtering used for
recommender
● Has 5 primary subsystems:
o UI
o Web Server
o Recommendation algorithm
o Database
o Web Crawling Utilities

9. Proposed Design Cont.
● UI
o essentially the
client side UI for
the web server
o will use:
 HTML5
 CSS
 Javascript
 Spring
framework
● Web Server
○ Model-View-Controller
model
○ based in Java EE
○ will use:
■ AWS SDK
■ Struts
■ Java Persistent
API( JPA)
■ Ajax

10. Frameworks
● Struts 2
Apache Struts is a free, open-source, MVC framework for creating elegant,
modern Java web applications. In this project system...
● Spring
The Spring Framework provides a comprehensive programming and
configuration model for modern Java-based enterprise applications - on any kind
of deployment platform. In this project system...
● Java Persistence API (JPA)
The Java Persistence Architecture API (JPA) is a Java specification for
accessing, persisting, and managing data between Java objects / classes and a
relational database. In this project system...

11. Proposed Design Cont.
● Recommendation Algorithm
o Hybrid filtering system
 keeps the best of both the content-based
filtering and the collaborative filtering
 Will do a weighted average between the two
filtering systems
o Will be able to learn and adjust based on user
ratings of the recommendations
o Vector space model

12. Proposed Design Cont.
● Database
o MySQL
o Will store user profiles
o Persistent Database
stored on AWS
● Web Crawler
○ provides initial
user and
product profiles
○ provides data
for testing
scenarios

13. Design Validation
● Project is a framework: needs specific implementation for testing
● Beer recommender
o Tastes can vary
o Costs of trying new varieties
● Use web crawler to gather product information and use for testing
● Utilizes Unit Testing during development
● Recommender will be evaluated thoroughout development using the
measures precision, recall, F-Score

14. Team Responsibilities
● Hilary Aben
o Team leader, web crawler
● Seth Brady
o Head of technical reporting, head of user interface
● Christopher Trask
o Head of algorithms, web crawler
● Kang Du
o Head of web design, databases
● Yiming Chen
o Head of finances, head of databases, algorithms

15. Teamwork
● Team members record individual notes in
journals; share any necessary information on
the group webpage
● Members will meet at least twice a week for
brainstorming, discussion, and problem
solving

16. Questions?