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Ranking Methods of Web Search using Genetic Algorithm  

Jung, Yong-Gyu (을지대학교 의료IT마케팅학과)
Han, Song-Yi (을지대학교 의료산업학부 의료전산학전공)
Publication Information
The Journal of the Institute of Internet, Broadcasting and Communication / v.10, no.3, 2010 , pp. 91-95 More about this Journal
Abstract
Using artificial neural network to use a search preference based on the user's information, the ranking of search results that will enable flexible searches can be improved. After trained in several different queries by other users in the past, the actual search results in order to better reflect the use of artificial neural networks to neural network learning. In order to change the weights constantly moving backward in the network to change weights of backpropagation algorithm. In this study, however, the initial training, performance data, look for increasing the number of lessons that can be overfitted. In this paper, we have optimized a lot of objects that have a strong advantage to apply genetic algorithms to the relevant page of the search rankings flexible as an object to the URL list on a random selection method is proposed for the study.
Keywords
Artificial Neural Network; Search Ranking; Backpropagation; Genetic Algorithms;
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