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Invite: Event Recommendation & Ticket Search System

A web recommendation system recommends nearby events according to users' favorite events, also allows users to search events and purchase tickets.

1. Project Description

  • Frontend: an interactive web page with AJAX technology implemented with HTML, CSS, and JavaScript. This web application supports three key implementations:

    • Auto-Search events around users based on geolocation
    • Favorite events when the user likes and save them in the history records
    • Show recommendation of events around based on their favorite history.

  • Backend: create Java servlet with RESTful APIs in Apache Tomcat to handle HTTP requests and responses

    • Utilized relational and NoSQL databases (MySQL/MongoDB) to store real business data, such as name, description, location, and price, from TicketMaster API

    • Design content-based recommendation algorithm for event recommendation

    • Deployed server to Amazon EC2 to handle 160 QPS tested by Apache JMeter

2. Architecture

  • 3-tier architecture

    • Presentation tier: HTML, CSS, JavaScript
    • Data tier: MySQL, MongoDB
    • Logic tier: Java

3. Java Servlet Design

  • Logic tier(Java Servlet to RPC)
    • Search
      • searchItems
      • Ticketmaster API
      • parse and clean data, saveItems
      • return response
    • History
      • get, set, delete favorite items
      • query database
      • return response
    • Recommendation
      • recommendItems
      • get favorite history
      • search similar events, sorting
      • return response
    • Login
      • GET: check if the session is logged in
      • POST: verify the user name and password, set session time and marked as logged in
      • query database to verify
      • return response
    • Logout
      • GET: invalid the session if exists and redirect to index.html
      • POST: the same as GET
      • return response
    • Register
      • Set a new user into users table/collection in database
      • return response

APIs design

  • TicketMasterAPI

  • Recommendation Algorithms design

    • Content-based Recommendation: find categories from item profile from a user’s favorite, and recommend the similar items with same categories.

    • Present recommended items with ranking based on distance (geolocation of users)

4. Database Implementation

  • MySQL
    • users - store user information.
    • items - store item information.
    • category - store item-category relationship
    • history - store user favorite history

mysql

  • MongoDB

    • users : store user information and favorite history. (= users + history)

    • items : store item information and item-category relationship. ( = items + category)

    • logs : store log information

5. Design pattern

  • Builder pattern: Item.java

    • When convert events from TicketMasterAPI to java Items, use builder pattern to freely add fields.

  • Factory pattern: ExternalAPIFactory.java, DBConnectionFactory.java

    • ExternalAPIFactory.java: support multiple functions like recommendations of event, restaurant, news, jobs, etc., Just link to different public API.
    • DBConnectionFactory.java: support multiple databases like MySQL and MongoDB. Improve extension ability.

  • Singleton pattern: MySQLConnection.java, MongoDBConnection.java

    • Only create one specific instance of the database, and the class can control the instance itself and give global access to the outer class.