UROP Proceedings 2010-11

An Evaluation Framework for Search Engine PersonalizationAdvisor : NG Wilfred Siu Hung / CSEStudent : WANG Heng / COMP(UROP1000, Summer 2011)In recent years, search engine personalization is one of the hot topics in the industry. It isusually regarded as Search 4.0, aiming at providing customized results for different users.However, due to a lack of evaluation benchmark, evaluating new approaches of search enginepersonalization is time-consuming and requires human judgment. This project targets atcreating such a benchmark that can be used as a test bed for new approaches to search enginepersonalization.RFID Data Processing and Research on GraphAdvisor : NG Wilfred Siu Hung / CSEStudent : ZHANG Zhijun / COMP(UROP1000, Summer 2011)RFID has become a popular topic, and how to mine data using RFID and how to process thedata for more information are worth further studying. At the same time, as RFID data can beeasily and conveniently processed using graph data processing skills, graph data, includingexact graphs and uncertain graphs are studied in this project. Several algorithms are tested todetermine their efficiency in mining useful data from the RFID results.Word PyramidAdvisor : QU Huamin / CSEStudent : CHENG Hao / ELEC(UROP1000, Summer 2011)In the internet era with an explosion of data and information, the amount of new documents,research papers and new data are increasing at an extraordinary speed. Millions of new dataare in the media every day, every second, and people are no longer able to analyze all thearticles by themselves. People need tools to help them process extremely large quantity ofdata and one possible solution is Text Visualization. Different algorithms can be used todecide which type of information is worth reading or noticing. There already exist many kindsof tools for this purpose, such as Word Clouds, Tree Clouds and Wordle. In this project, Ipropose a new plot called Word Pyramid, and it not only shows the keywords in a huge dataset, but also allows people to see how much “larger” one word is compared to the other. Byusing this plot, people can understand the data in a more detailed way.42