Geographical labeling of web objects through density estimator model
Podder Sanjay, G T Raju, B. Eswara Reddy · 2017
Web object search engines provide powerful vertical search facility to the users so that, redundant information in the result can be effectively filtered. Currently, geographical labeling of Web objects have got limited attention. This task is complicated further due to the presence of noise inside Web objects. Recently, geographical labeling was achieved through Gaussian mixture model in [2]. But, there is plenty of scope to improve on the results achieved in [2]. In this work, a new geographical labeling procedure by using density estimator model is introduced. This technique shows better computational efficiency and labeling accuracy than previously proposed technique [2].