Mining temporal features of exploratory search for supporting collaborative information seeking

• Main Author: Toh, Yee Teng.
• Other Authors: Sun Chengzheng
• Format: Final Year Project
• Language: English
• Published: 2010
• Subjects: DRNTU::Engineering::Computer science and engineering::Information systems
• Online Access: http://hdl.handle.net/10356/42396
• Institution: Nanyang Technological University

Choosing the best web-based information are many people‟s difficulties. If collaboration is implemented in the search engine, user who uses it later can benefit from the work of earlier collaborators which will result in efficient and effective search. Therefore, this project focuses on investigating on what kind of exploratory searches that users can collaborate in real-time and how users can be benefited from the collaborative search. The data mining application was developed in C++ and was responsible for performing query clustering on AOL dataset and producing mining results. The mined results on the features of exploratory search identified can help to support and enhance the collaboration in information seeking process. Experiment was also done on each clustering algorithms and they can be further improved by expanding using a thesaurus (e.g. WordNet) which will take in the semantic similarity into account.