Partner, Data analyst, software developer
Ciapple
Total years of experience :2 years, 4 Months
Ciapple is a company specialized in search engines, recommendation engines, and data analysis.
Currently I hold the team leading position, in which I lead the software development process, defining requirements, designing and architecting software systems, managing and participating in software development.
Projects:
Personalized search and recommendation engine for BlueKangaroo.com :
BlueKangaroo.com is a company that provides thousands of shopping offers for its users.
We made a search and recommendation engine that is responsible for retrieving the best offers that matches each user's interests and search queries as well as recommending the offers that a user would care about the most. With this engine the website users experience became very great, as it became very easy for the users to find the offers they are looking for from thousands of different offers.
Some of the techniques used in this project to achieve highly accurate results are, text processing, feature extraction, collaborative filtering, and ranked information retrieval.
In this period in participated in the development of a variety of software systems, using many programming languages.
projects:
Business Intelligence for ClearTrip.com:
In this project we analyzed the transactional data of ClearTrip, which is an online flights booking company
We delivered statistical analysis reports, and discovered some patterns in the data (what items are usually bought together), and used those discoveries for cross-selling.
SkyFire data analysis:
SkyFire is a popular web browser mobile phones.
In this project we analyzed very large data sets from the logs of SkyFire, we used text processing and statistical analysis to discover users interest in e-commerce websites.
University Registration Recommendation Engine:
A recommendation engine that helps university students choose which courses to register by recommending the best courses suited for them.
We analyzed very large registration data sets from ALQUDS university, we used three different methods for recommendation, they are: collaborative filtering, sequence item mining, and frequent item mining, then combined the results form those different methods to get very accurate results.
In this period, I was studying and researching in the fields of data analysis and machine learning.
projects
Optical Character Recognition:
This was my graduation project, using many image processing and cleaning algorithms, and Feed Back Neural networks, I was able to recognize text from any normal camera taken photo.