Ads Searching is a multi-billion dollar business. In this project, we will implement a simplified search ads stack which selects ads for a given query and returns sorted ads based on some ranking criteria.
Basic process flow: Query understanding -> Select Ads Candidates -> Rank Ads ->Filter Ads -> Pricing -> Allocate Ads
*This is an open-ended challenge. Do your best to come up with your own implementation
- User can input keywords and search whatever he want to search
- All ads should list in a the page and ranked
| Stage | Start | End | Goals |
|---|---|---|---|
| 0 Week | 12/29/16 | 01/11/17 | Finish the amazon crawler and user query/click log and stored crawlled data into mysql |
| 1st Week | 01/11/17 | 01/16/17 | Finish basic ads search server v1.0, including ads business logic, user query preprocessing, ads keywords inverted index, similarity algorithm |
| 2nd Week | 09/12/16 | 09/18/16 | Finish front-end and start back-end |
| 3rd Week | 09/19/16 | 09/25/16 | Back-end and connection to twitter API |
| 4th Week | 09/26/16 | 10/02/16 | Go over whole process and fix bugs |
| 5th Week | 10/03/16 | 10/09/16 | Fix bug and prepare presentation |
- Front-end: AngularJS Bootstrap
- Backend: Spring MVC Jetty Lucene Memcached Mysql
- NLP algorithm
- Previous Project Examplelink
- Apache Lucenelink
- Memcached Tutoriallink
- Spring in actionlink
- Bittiger project tutoriallink
- Common logginglink
- slf4jlink
- jsouplink
- HttpComponentslink
- junitlink
- commons-langlang3link
See the LICENSE file for license rights and limitations (MIT).