Abstract
On the internet, a large number of information is available, which consolidates data and hyperlinks. With the large heterogeneous information resource, it is very difficult to locate the coveted data that matched with client needs and intrigue. To recover the relevant report from the user’s query, we use different types of algorithms. Page Ranking is additionally one of the groundbreaking algorithms to recover the best significant records that likewise lessen the client’s searching time. Web mining instruments are utilized by page ranking algorithm. Web mining device is utilized to arrange, group, and rank the report so the client can without much of a stretch finish the guide the query item and search the required data content. Mining can be done using two types, namely “Web Structure Mining” and “Web Content Mining”. In Web Structure Mining, rank the pages on the preface of their hyperlinks and in Web Content Mining, rank the pages on the premise of content of the pages. This paper portrays the examination and consolidates investigation of Web Structure Mining and Web Content Mining to enhance the positioning of pages.
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
References
Zhang, M., Ma S.P., Song, R.H.: On the use of primary feature model for web information retrieval. J. Softw., 1012–1020 (2005)
Arasu, A., Cho, J., Garcia-Molina, H., Paepcke, A., Raghavan, S.: Searching the web. ACM Trans. Internet Technol., 97–101 (2001)
Edwards, J., McCurley, K.S., Tomlin, J.: An adaptive model for optimizing performance of an cremental web crawler. In: Proceedings the 10th Conference on World Wide Web , pp. 106–113. Elsevier Science, Hong Kong (2001)
Page, L., Brin, S., Motwani, R., Winograd, T.: The page rank citration ranking: bringing order to the web. Stanford Digital Libraries SIDL-WP, pp. 1990–2000 (1999)
Ridings, C., Shishigin, M.: Page rank uncovered. Technical Report (2002)
Cooley, R., Mobasher, B., Srivastava, J.: Web mining: information and pattern discovery on the world wide web. In: 9th IEEE International Conference on Tools with Artificial Intelligence (ICTAI 97) (1997)
Dunham, M.H.: Data Mining Introductory and Advanced Topics. Prentice Hall, New Jersey (2002)
Jicheng, W., Yuan, H., Gangshan, W., Fuyan, Z.: Web mining: knowledge discovery on the web. Systems, man, and cybernetics. In: IEEE SMC’99 Conference Proceedings, vol. 2, pp. 137–141, 15 Oct 1999
Han, J., Kamber, M., Pei J.: Data Mining: Concepts and Techniques. Morgan Kaufmann Publishers, Burlington (2000)
Kosala, R., Blockeel, Hendrik.: Web mining research: a survey (2000)
Sanjay, Kumar, D.: A review on page ranking algorithm. Int. J. Adv. Res. Comput. Eng. Technol. 4 (2015)
Getoor, L.: Link mining: a new data mining challenge. In: SIGKDD Explorations, vol. 4 (2003)
Xing, W., Ghorbani A.: Weighted pagerank algorithm. In: Proceedings of the 2nd Annual Conference on Communication Networks and Services Research (CNSR’04). IEEE (2004)
Cheng, A., Friedman, E.: Manipulability of page rank under sybil strategies. 6 Nov 2006
Xing, L.Z.: Research and improvement of page rank sort algorithm based on retrieval result. IEEE, 8 Jan 2015
Kumar, A., Singh, R.K.: A study on web structure mining. Int. Res. J. Eng. Technol. (IRJET) 04(1) (2017)
Sote, A.M., Pande, S.R.: Application of page ranking algorithm in web mining. IOSR J. Comput. Sci., 47–51 (2014)
Dave, D.: Review of various web page ranking algorithms in web structure mining. In: National Conference on Recent Research in Engineering and Technology; Int. J. Adv. Eng. Res. Dev. (2015). ISSN:2348-6406
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Pradhan, N., Dhaka, V.S. (2020). Comparison-Based Study of PageRank Algorithm Using Web Structure Mining and Web Content Mining. In: Somani, A.K., Shekhawat, R.S., Mundra, A., Srivastava, S., Verma, V.K. (eds) Smart Systems and IoT: Innovations in Computing. Smart Innovation, Systems and Technologies, vol 141. Springer, Singapore. https://doi.org/10.1007/978-981-13-8406-6_68
Download citation
DOI: https://doi.org/10.1007/978-981-13-8406-6_68
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-13-8405-9
Online ISBN: 978-981-13-8406-6
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)