LEARNING-based Focused WEB Crawler

References

• H. Bullot, S. K. Gupta, and M. K. Mohania, “A data-mining approach for optimizing performance of an incremental crawler,” in Proceedings IEEE/WIC International Conference on Web Intelligence, Halifax, NS, Canada, 2003, pp. 610–615.
   Google Scholar
• M. Kc, M. Hagenbuchner, and A. C. Tsoi, “A Scalable Lightweight distributed crawler for crawling with limited resources,” in 2008 IEEE/WIC/ACM International Conference on Web Intelligence and intelligent Agent Technology, Sydney, NSW, 2008, pp. 663–666.
   Google Scholar
• D. Mukhopadhyay, A. Biswas, and S. Sinha, “A new approach to design domain specific ontology based Web crawler,” in 10th International Conference on information Technology (ICIT), Orissa, 2007, pp. 289–291.
   Google Scholar
• M. Wu, and J. Lai, “The research and implementation of parallel Web crawler in Cluster,” in 2010 International Conference on Computational and information Sciences, Chengdu, 2010, pp. 704–708.
   Google Scholar
• S. Anbukodi, and K. M. Manickam, “Reducing web crawler overhead using mobile crawler,” in 2011 International Conference on Emerging Trends in Electrical and Computer Technology, Nagercoil, 2011, pp. 926–932.
   Google Scholar
• A. Gupta, and P. Anand, “Focused web crawlers and its approaches,” in International Conference on Futuristic Trends on Computational Analysis and Knowledge Management (ABLAZE), Noida, 2015, pp. 619–622.
   Google Scholar
• G. H. Agre, and N. V. Mahajan, “Keyword focused web crawler,” in 2nd International Conference on Electronics and Communication Systems, Coimbatore, 2015, pp. 1089–1092.
   Google Scholar
• T. Suebchua, A. Rungsawang, and H. Yamana, “Adaptive focused website Segment crawler,” in 19th International Conference on network-based information Systems (NBi-S), Ostrava, 2016, pp. 181–187.
   Google Scholar
• R. Navinkumar, and S. Sureshkumar, “Two-stage Smart crawler for efficiently Harvesting deep-Web Interfaces,” International Research Journal of Engineering and Technology (IRJET), Vol. 3, pp. 111–114, 2016.
   Google Scholar
• Y. Patil, and S. Patil, “Implementation of enhanced web crawler for deep-web Interfaces,” International Research Journal of Engineering and Technology (IRJET), Vol. 3, pp. 2088–2092, 2016.
   Google Scholar
• G. V. Jaybhaye, and A. V. Deorankar, “Machine learning approach for self-adaptive semantic focused crawler based data mining Services,” International Journal of Innovative Research in Computer and Communication Engineering, Vol. 4, pp. 2507–2512, 2016.
   Google Scholar
• P. S. Sekhon, and S. Aggarwal, “Focused web crawling using neural network, decision tree induction and naıve bayes classifier,” IJCST, Vol. 5, pp. 155–159, 2014.
   Google Scholar
• S. Gurav, J. Gilani, V. Gore, and S. Jadhao, “Web content extraction using machine learning,” International Research Journal of Engineering and Technology (IRJET), Vol. 5, pp. 4517–4518, 2018.
   Google Scholar
• D. Taylan, M. Poyraz, S. Akyokus, and M. C. Ganiz, “Intelligent focused crawler: learning which links to crawl,” in International Symposium on Innovations in intelligent Systems and Applications (INISTA), Istanbul, 2011, pp. 504–5081.
   Google Scholar
• N. Mtetwa, M. Yousefi, and V. Reddy, “Feature Selection for an SVM based webpage classifier,” in International Conference on Soft Computing & machine Intelligence (ISCMI), Port Louis, 2017, pp. 85–88.
   Google Scholar
• A. Darshakar, “Crawler intelligence with machine learning and data mining integration,” in International Conference on Pervasive Computing (ICPC), Pune, 2015, pp. 1–6.
   Google Scholar
• L. Jiang, Z. Wu, Q. Zheng, and J. Liu, “Learning deep Web crawling with Diverse features,” in IEEE/WIC/AC-M International Joint Conference on Web Intelligence and intelligent Agent Technology, Milan, Italy, 2009, pp. 572–575.
   Google Scholar
• M. Diligenti, F. M. Coetzee, S. Lawrence, C. L. Giles, and M. Gori, “Focused crawling using context Graphs,” in VLDB ‘00 Proceedings of the 26th Intern-ational Conference on very large data Bases, Cairo, Egypt, 2000, pp. 527–534.
   Google Scholar
• M. Chau, and H. Chen, “A machine learning approach to web page filtering using content and structure analysis,” Decis. Support. Syst., Vol. 44, pp. 482–494, 2008.
   Web of Science ®Google Scholar
• H. T. Y. Achsana, and W. C. Wibowob, “A Fast distributed focused-Web crawling,” in DAAAM International Symposium on intelligent Manufacturing and automation, Zadar, Croatia, 2013, pp. 492–499.
   Google Scholar
• M. Kumar, A. Bindal, R. Gautam, and R. Bhatia, “Keyword query based focused web crawler,” in International Conference on Smart Computing and Communications, ICSCC, Kurukshetra, India, 2018, pp. 584–590.
   Google Scholar
• M. Kumar, and R. Vig, “Learnable focused Meta crawling Through Web,” in International Conference on Communication, Computing & security, Odisha, India, 2012, pp. 606–611.
   Google Scholar
• S. R. Mani Sekhar, G. M. Siddesh, S. S. Manvi, and K. G. Srinivasa, “Optimized focused Web crawler with Natural Language processing based relevance Measure in Bioinformatics Web Sources,” Cybern. Inf. Technol., Vol. 19, pp. 146–158, 2019.
   Web of Science ®Google Scholar
• S. Han, M. Bendersky, P. Gajda, S. Novikov, M. Najork, B. Brodowsky, and A. Popescul, “Adversarial bandits policy for crawling Commercial Web content,” in International World Wide Web Conference Committee (IW3C2), ACM, Taipei, Taiwan, 2020, pp. 407–417.
   Google Scholar
• Y. Azar, E. Horvitz, E. Lubetzky, Y. Peres, and D. Shahaf, “Tractable near-optimal policies for crawling,” Proc. Natl. Acad. Sci. U. S. A., Vol. 115, pp. 8099–8103, 2018.
   PubMed Web of Science ®Google Scholar
• K. Avrachenkov, K. Patil, and G. Thoppe, “Change rate estimation and optimal freshness in Web page crawling,” in 13th EAI International Conference on performance Evaluation Methodologies and Tools, VALUETOOLS'20, ACM, New York, USA, 2020, pp. 3–10.
   Google Scholar
• R. Todesschini, “k-nearest neighbor method: The influence of data transformations and metrics,” Chemom. Intell. Lab. Syst., Vol. 6, pp. 213–220, 1989.
   Web of Science ®Google Scholar
• J. Di, and X. Gou, “Bisecting K-means algorithm based on K-valued Self-determining and Clustering Center Optimization,” School of Control and Comp-Uter Engineering, Vol. 13, pp. 588–595, 2018.
   Google Scholar