MODELING USER INTERESTS FROM WEB BROWSING ACTIVITIES. Team 11. research paper review: author: Fabio Gasparetti publication date: November 1, 2016

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1 research paper review: MODELING USER INTERESTS FROM WEB BROWSING ACTIVITIES author: Fabio Gasparetti publication date: November 1, 2016 Team 11 Angelique Elkins Jim Saeturn Michael Yang

2 BACKGROUND & PROBLEM DEFINITION TECHNICAL HIGHLIGHTS OF PROBLEM SOLVING Search engines aim to find the most relevant sites for user searches using browsing sessions. This becomes difficult with HTML pages that contain noisy data (e.g. ads and nav menus). The project of the report aims to use data mining to find a more successful approach to building profiles for individual user searches. 2 stage approach: 1. Group pages from browser history by common tree structure using Page Clustering based off Document Object Model. Then internally comparing each cluster s text information to find any semantic relationships. 2. Use the knowledge gained from the first step in accordance with the current search. This is done by weighing the semantic relationship of step one with the current search results and weeding out non-relatable pages.

ILLUSTRATION OF THE METHODS INTRODUCED Extraction Method Combined clustering techniques based on Document Object Model(DOM)- based representations of web pages Initial stage: single pages and pairs

3 ILLUSTRATION OF THE METHODS INTRODUCED Extraction Method Combined clustering techniques based on Document Object Model(DOM)- based representations of web pages Initial stage: single pages and pairs visited pages in browsing sessions considered Representing groups of pages with similar template with a common tree structure Finding correlations between contents of text regions on two consecutive pages

4 OPINION ON THE WORK SIGNIFICANCE OF WORK The paper was enlightening on the process and different methods on how to do data warehousing and mining in regards to browsing and related subjects and the difficulties that one must find a way to work around. It also showed us the in depth process of data preprocessing, data clustering, and data analysis that will help us greatly in our own research project. Browsing history can contain relevant information that can be used for representing current user interests. Past browsing activities may lead to more relevant information that the current user has interests in when compared to a whole page content extraction approach because it can overlook advertisements, scroll bars, and ect. Analysis on visited pages allows identification of relationships between text regions and less relevant content. As this knowledge builds up, its statistical analysis improves the accuracy of the extraction of current interests.

5 Angelique Elkins Jim Saetern Michael Yang PROPOSAL: VIDEO GAME SALES

6 BACKGROUNDS / MOTIVATIONS PROPOSAL STATEMENTS / OBJECTIVES / BENEFITS With new technology and growing trends the marketplace for video games are expanding more than ever. From giant publishers to individual developers the opportunity to break into the industry is better than ever. We aim to find how to predict the sales bracket of video games based on the sales of previous video games when factoring variables such as promotions, genre, platform, region, etc. By gathering data on how popular certain games do in the marketplace developers will better predict how their products will do.

7 METHODS SCHEDULE Collecting data of video games into different year brackets for sales comparison (to account for inflation). Collecting specifically the publishers, genres, Entertainment Software Rating Board ratings, critic ratings, and platform releases of said video games. Comparing these data sets to find if any of these data points seem to contribute to the likelihood of a video game falling within a certain range of sales. Week 9: Data Collection & Integration Week 10: Data Integration & Cleaning Week 11: Data Transformation Week 12: Data Mining Week 13: Results Evaluation

8 REFERENCES

INTRODUCTION. Chapter GENERAL

INTRODUCTION. Chapter GENERAL Chapter 1 INTRODUCTION 1.1 GENERAL The World Wide Web (WWW) [1] is a system of interlinked hypertext documents accessed via the Internet. It is an interactive world of shared information through which