Abstract
In this paper, a different Web personalized service (PS) based on dual genetic algorithms (Dual GAs) has been presented. Firstly, to distinguish the importance of each keyword to a user, we have introduced a new concept called influence-gene and a user profile model UP=(I, C), which includes not only the user’s keyword-weights vector I but also a user’s influence-genes vector C. Secondly, based on C, we have introduced a w-cosine similarity, which is an improver of the traditional cosine similarity. Finally, we have discussed how to design our Dual GAs to automatically discover and adjust the UP. The comparison tests show that the Dual GAs can discover the user profile more accurately and improve the precision of information recommendation.
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Zhu, Z., Xie, Q., Chen, X., Zhu, Q. (2005). A Web Personalized Service Based on Dual GAs. In: Wang, L., Chen, K., Ong, Y.S. (eds) Advances in Natural Computation. ICNC 2005. Lecture Notes in Computer Science, vol 3612. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11539902_7
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DOI: https://doi.org/10.1007/11539902_7
Publisher Name: Springer, Berlin, Heidelberg
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