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Implementation and Web Mounting of the WebOMiner_S Recommendation System

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  • Tue, 05/09/2017 - 2:30pm - 4:00pm




Implementation and Web Mounting of the WebOMiner_S Recommendation System

MSc Thesis Defense by:

Amrutraj Chachad

Date:  May 9th, 2017
Time:  2:30 p.m. – 4:00 p.m.
Location: 3105, Lambton Tower

Abstract: The ability to quickly extract information from a large amount of heterogeneous data available on the web from various Business to Consumer (B2C) or Ecommerce stores selling similar products (such as Laptops) for comparative querying and knowledge discovery remains a challenge because different web sites have different structures for their web data and web data are unstructured. For example comparative querying is: Find the cheapest price for Dell Laptop in BestBuy.ca and Amazon.com based on the following product features: Model: Inspiron 15 series, ram: 16gb, processor: i5, Hdd: 1 TB. The “WebOMiner” and “WebOMiner_S” systems perform automatic extraction by first parsing web html source code into a document object model (DOM) tree before using some pattern mining techniques to discover heterogeneous data types (eg: text, image, links, lists) so that product schemas are extracted and stored in a back-end data warehouse for querying and recommendation. These systems do not currently properly integrate all extracted product table schemas and data from different B2C websites into a consistent data warehouse table for querying. They also lack a graphical user interface (GUI) web application for easy access and use for purpose of web recommendation.

This thesis proposes a Web Recommendation System called the WebOMiner_SRec which extends the capabilities of the WebOMiner_S data extractor by adding: (1) Web GUI, (2) integration of extracted product schemas from different sources into a historical data warehouse and (3) comparative querying of multiple B2C web sites with some recommendation. The integration of the web data consists of all the product features such as Product model name, product description, market price obtained from the extraction process. Implementation is done using “Java server pages (JSP)” as the GUI designed in HTML, CSS, JavaScript and the framework used for this application is “Spring framework” which forms a bridge between the GUI and the data warehouse. SQL database is implemented to store the extracted product schemas for further integration, querying and knowledge discovery. All the technologies used are compatible with UNIX system for hosting the required application.

Thesis Committee:
Internal Reader: Dr. Yung H. Tsin
External Reader: Dr. Animesh Sarker
Advisor: Dr. Christie Ezeife
Chair: Dr. Alioune Ngom

 

 



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