The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Next Generation Search Engine for the Result Clustering Technology
Abstract
Result clustering has recently attracted a lot of attention to provide the users with a succinct overview of relevant search results than traditional search engines. This chapter proposes a mixed clustering method to organize all returned search results into a hierarchical tree structure. The clustering method accomplishes two main tasks, one is label construction and the other is tree building. This chapter uses precision to measure the quality of clustering results. According to the results of experiments, the author preliminarily concluded that the performance of the system is better than many other well-known commercial and academic systems. This chapter makes several contributions. First, it presents a high performance system based on the clustering method. Second, it develops a divisive hierarchical clustering algorithm to organize all returned snippets into hierarchical tree structure. Third, it performs a wide range of experimental analyses to show that almost all commercial systems are significantly better than most current academic systems.
Related Content
Hrithik Raj, Ritu Punhani, Ishika Punhani.
© 2023.
31 pages.
|
Divi Anand, Isha Kaushik, Jasmehar Singh Mann, Ritu Punhani, Ishika Punhani.
© 2023.
21 pages.
|
Jayanthi G., Purushothaman R..
© 2023.
10 pages.
|
Anshika Gupta, Shuchi Sirpal.
© 2023.
14 pages.
|
Reet Kaur Kohli, Seneha Santoshi, Sunishtha S. Yadav, Vandana Chauhan.
© 2023.
13 pages.
|
Poonam Tanwar.
© 2023.
14 pages.
|
Monika Mehta, Shivani Mishra, Santosh Kumar, Muskaan Bansal.
© 2023.
16 pages.
|
|
|