Analyzing Characteristics and Implementing Machine Learning Algorithms for Internet Search
DOI:
https://doi.org/10.63876/jdsi.v1i1.2Keywords:
search engines, Information retrieval, User intention, Web MiningAbstract
With the rapid growth of online information, socializing on websites has become increasingly popular. However, finding relevant information within a limited time frame can be a daunting task, often resulting in irrelevant or incompatible search results. To address this challenge, researchers have explored different features used in information retrieval and their effectiveness in delivering relevant web pages to users. This paper provides an overview of various features utilized in information retrieval, including their classification and evaluation. The study also examines the relevance of web pages with users and compares different techniques, highlighting their pros and cons. Ultimately, this research aims to improve web search capabilities and enhance user satisfaction in finding relevant information.
Downloads
References
O. Etzioni,†The world wide web: Quagmire or gold mineâ€, Communications of the ACM, 39(11):65-68,1996.
https://en.wikipedia.org/wiki/Machine_learning
Michael Chau, Hsinchun Chen,â€A machine learning approach to web page filtering using content and structure analysisâ€,Decision Support Systems 44(2008) 482-494,2007
Tarannum Bibi, Pratiksha Dixit, Rutuja Ghule, Rohini Jadhav, “Web search personalization using machine learning techniquesâ€, IEEE, 2014
M.Indra Devi, Dr.R.Rajaram and K.Selvakuberan,"Machine learning techniques for automated web page classification using URL features",International conference on computational intelligence and multimedia applications 2007,IEEE.
Kinam Park, Taemin Lee; Soonyoung Jung; Sangyep Nam; Heuiseok Lim, “Extracting Search Intentions from Web Search Logsâ€, Information Technology Convergence and Services (ITCS),Pages: 1 – 6,IEEE,2010.
Varun Gupta, Neeraj Garg and Tarun Gupta, â€Search Bot: Search Intention Based Filtering Using Decision Tree Based Techniquesâ€, Third International Conference on Intelligent Systems Modeling and Simulation, IEEE, 2012.
Xiaoguang Qi and Brian D. Davison,â€Web page classification:features and algorithmsâ€, ACM computing surveys, vol.41,No. 2,Article 12(February 2009). [9] J. Kleinberg, "Authoritative sources in a hyperlinked environment", Proceedings of the ACM-SIAM Symposium on Discrete Algorithms, 1998. [10] S.Brin, L.Page, “The anatomy of a large-scale hypertextual web search engineâ€, Proceedings of the 7th International World Wide Web Conference, Brisbane, Australia, Apr 1998. [11] M.Chau, H .Chen, “Comparison of three vertical search spidersâ€, IEEE Computer 36(5) (2003a) 56-62.
CJ van Rijsbergen, "Information Retrieval", Second edition, Butterworths, London, 1979.
K. Tolle, H. Chen, "Comparing noun phrasing techniques for use with medical digital library tools", Journal of the American Society for Information Science 51(4) (2000) 352-370.
MF Porter, “An algorithm for suffix strippingâ€, Program 14 (3) (1980) 130-137.
JR Quinlan,â€Induction of Decision Treeâ€,Machine Learning,Vol. 1,pp 81-106,1986.
