Abstract—Enhancements in data mining for effective information retrieval is an emerging trend. This growth in turn has motivated researchers to seek new techniques for knowledge extraction. This research paper, induce the need for an incremental data mining approach based on data structure called the Bookshelf tree. The provoked approach is shown to be effective for solving problems related to efficiency of handling data updates, accuracy, processing input transactions, and answering user queries. This paper proposes a Branch and Bound Bookshelf Tree incorporated with association mining for self organization of the results retrieved from the RFDDb. This research work focus on the new techniques for keyword search over a mass of tables, and show that they can achieve substantially higher relevance than solutions based on a traditional search engine using Referenced attribute Functional Dependency Database (RFDDb). Branch and Bound is for best optimized result and the bookshelf tree is for organizing result for effective and efficient Information Retrieval (IR).B3-Vis Technique is proposed for visualizing the results retrieved from the Branch and Bound Bookshelf Tree. The relevant queries are arranged in each frame of Book Shelf for effective Information Retrieval. Finally, the search results are presented in visual mode, which allows a user to navigate between extracted schemas.
Index Terms—Book Shelf Data structure, B3-VIS technique, information retrieval, referenced attribute functional dependency database (RFDDb), visualization, web-mining.
S. K. Jayanthi is with Computer Science Department, Vellalar College for Women (Autonomous), Erode, Tamilnadu, India.
S. Prema is with Computer science Department, K.S.R. College of Arts and Science,Tiruchengode-637215, Namakkal district, Tamilnadu, India(e-mail: prema_shanmuga@yahoo.com).
Cite:S. K. Jayanthi and S. Prema, "Web Search Results Visualization Using Enhanced Branch and Bound Bookshelf Tree Incorporated with B3-Vis," International Journal of Machine Learning and Computing vol.2, no. 5, pp. 644-647, 2012.