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.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Martín-Bautista, M.J., Larsen, H., Vila, M.A.: A Fuzzy Genetic Algorithm Approach to An Adaptive Information Retrieval Agent. Journal of the American Society for Information Science 50(9), 760–771 (1999)
Li, Y.F., Zhong, N.: Web Mining Model and Its Applications for Information Gathering. Knowledge-Based Systems 17, 207–217 (2004)
Bloedorn, E., Mani, I.: Using NLP for Machine Learning of User Profile. Intelligent Data Analysis 2, 3–18 (1998)
Liu, B., Wang, H., Feng, A.: Applying information agent in open bookmark service. Advances in Engineering Softare 32, 519–525 (2001)
Yang, C.C., Chung, A.: Intelligent infomediary for web financial information. Decision Support Systems 38, 65–80 (2004)
Fan, W., Gordon, M.D., Pathak, P.: Effective profiling of consumer information retrieval needs: a unified framework and emPSical comparison. Decision Support Systems (2004) (In Press)
Li, Y., Zhang, C., Swan, J.R.: An information filtering model on the Web and its application in Job Agent. Knowledge-Based Systems 13, 285–296 (2000)
Mostafa, J., Lam, W.: Automatic classification using supervised learning in a medical document filtering application. Information Processing and Management 36, 415–444 (2000)
Cordón, O., Herrera-Viedma, E., López-Pujalte, C., Luque, M., Zarco, C.: A review on the application of evolutionary omputation to information retrieval. International Journal of Approximate Reasoning 34, 241–264 (2003)
López-Pujalte, C., Guerrero-Bote, V.P., Moya-Anegón, F.D.: Genetic algorithms in relevance feedback: a second test and new contributions. Information Processing and Management 39, 669–687 (2003)
Ho, M.H., Cheng, M.C., Chang, Y.S., Yuan, S.M.: A GA-Based Dynamic Personalized Filtering For Internet Search Service on Multi-Serach Engine. In: Canadian Conference on Electrical and Computer Engineering, vol. 1, pp. 271–276 (2001)
López-Pujalte, C., Guerrero-Bote, V.P., Moya-Anegón, F.D.: A test of genetic algorithms in relevance feedback. Information Processing and Management 38, 793–805 (2002)
Vallim, M.S., Adán-Coello, J.M.: An Agent for Web Information Dissemination Based on a Genetic Algorithm. IEEE, Los Alamitos (2003)
Leroy, G., Lally, A.M., Chen, H.: The Use of Dynamic Contexts to Improve Casual Internet Searching. ACM Transactions on Information Systems 21(3), 229–253 (2003)
Martín-Bautista, M.J., Vila, M.A., Sánchez, D., Larsen, H.L.: Fuzzy Genes: Improving the Effectiveness of Information Retrieval. IEEE, Los Alamitos (2000)
Trotman, A.: Choosing document structure weights. Information Processing and Management 41(2), 243–264 (2003)
Salton, G., McGill, M.H.: Introduction to Modern Information Retrieval. McGraw-Hill, New York (1983)
Baeza-Yates, R., Ribeiro-Neto, B.: Modern information retrieval. Addison-Wesley, Essex (1999)
Bruce, K., Chad, B.: The Infofinder Agent: Learning User Interests through Heuristic Phrase Extraction. IEEE Expert 12(5), 22–27 (1997)
Salton, G., Buckley, C.: Improving retrieval performance by relevance feedback. Journal of the American Society for Information Science 41(4), 288–297 (1990)
Horng, J.T., Yeh, C.C.: Applying genetic algorithms to query optimization in document retrieval. Information Processing and Management 36, 737–759 (2000)
Eiben, A.E., Smith, J.E.: Introduction to Evolutionary Computing. Springer, Berlin (2003)
Liang, T.P., Lai, H.J.: Discovering User Interests from Web Browsing Behavior: An Application to Internet News Services. In: Proceeding of the 35th Annual Hawaii International Conference on System Sciences (HICSS-35 2002). IEEE, Los Alamitos (2002)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
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
Download citation
DOI: https://doi.org/10.1007/11539902_7
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28320-1
Online ISBN: 978-3-540-31863-7
eBook Packages: Computer ScienceComputer Science (R0)