Design and development of a collaborative search engine

• Main Author: Low, Shu Juan.
• Other Authors: Sun Aixin
• Format: Final Year Project
• Language: English
• Published: 2009
• Subjects: DRNTU::Engineering::Computer science and engineering::Information systems::Information storage and retrieval
• Online Access: http://hdl.handle.net/10356/17008
• Institution: Nanyang Technological University

The success of modern Web search created many challenges nowadays and current search engine technology is struggling to fulfill the needs of today’s searchers. Users become more and more difficult to find the correct information on the Web at the right time. It is very hard for users to define the correct queries with the term-matching technology which is adopted at the heart of all Web search engines. One of the key problems of designing a search engine is trying to implement a correct way to order the results so that more relevant documents are displayed on the top to the most users. Thus, the objective of this project is to create a collaborative search system to display search results based on user search history and interaction with those results. In order to have a better understanding of search engine, the current issues and problems have been studied. Research was also carried out on similar existing collaborative search engine in order to develop a comprehensive and user-friendly Web search system. The strengths and weaknesses obtained from the research were noted and taken into consideration in the design of the system. Additional two types of search have been implemented as well as the collaborative search. Therefore, there are total three search services for this project. They are default traditional search whose functions are similar to current search engine, personalized search history based on past individual user’s queries and personalized ranking, and collaborative community search which displays results based on overall community ranking. The implementation of this system can assist users to retrieve more relevant results for a query. This in turn definitely improves the entire search process and reduces the wasted time for continuing searching the same query.