INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & MANAGEMENT INFORMATION SYSTEM (IJITMIS) International Journal of Information Technology & Management Information System (IJITMIS), ISSN 976 645(Print) ISSN 976 6413(Online) Volume 5, Issue 1, January - April (214), pp. 53-59 IAEME: http://www.iaeme.com/ijitmis.asp Journal Impact Factor (214): 6.2217 (Calculated by GISI) www.jifactor.com IJITMIS I A E M E IMPROVEMENT IN THE EFFICIENCY OF WEB BASED SEARCH ENGINES BY INCREASING PAGE RANK BASED ON REFERRING FACTORS Dr. Suryakant B Patil 1, Ms. Ashlesha Sawant 2, Dr. Preeti Patil 3 1 Professor, JSPM s Imperial College of Engineering & Research, Wagholi, Pune 2 Research Scholar, JSPM s ICOER, Wagholi, Pune 3 Dean (SA), HOD & Professor, KIT s COE, Kolhapur ABSTRACT There are millions of pages are there on web. Therefore need to find the popular pages.page rank is a logarithmic calculation to determine page popularity; page rank is one of the factors. Page rank the number counting and links quality to a page to determine a rough estimate of finding important of the website is. The no. of backlink it gives the popularity or importance of website or page. In this paper we have analysed several educational institutions and university to study the page rank and other important interfaces like external back links, referring domains, referring IPs, referring subnet. The proposed web based experimentation to identify these details and further classification and analysis of the web traffic. These external links and interfaces play the major role in the Page rank of any domain. From new organization to the old organization and from group of institutions like JSPM to university like Pune, various web traffics observed through these interfaces which are major contributors in the increasing the page rank. Categories and Subject Descriptors C.2.1[Network Architecture and Design]: Computer Communication Network. GENERAL TERMS: Algorithm, Experimentation, Performance. Keywords: Page Rank, External Back Link, Search Engine, Searching, Referring, s, Subnet. 53
I. INTRODUCTION Page Rank is used for counting the number and quality of links to a page to determine importance of page. The underlying assumption is that more important websites are receiving more links from other websites. Page Rank is a logarithmic calculation of various factors which point toward your site, showing that how much the page is reliable and related to that content. It is a probability distribution which is used to represent that how much time person click on link on any particular page.it is link analysis algorithm which link hyperlink set of document with relative importance within set. The algorithm may be applied to any collection of entities with reciprocal quotations and references. Backlink is also known as inbound link, in link, and inward links.backlink is nothing but link which received by a web node which relate to web page,web site or top level domain from another web node.subnet is dividing network into two or more networks.the computer which belongs to subnet is addressed with common, identical,most significant bit-group in their IP address.as there is specific IP address is assign to each device which participating in a computer network. Address indicates where it is. name is used for searching. Different extension will give different domain.page rank relate to Referring domain, Referring IP S And Referring subnet. II. LITERATURE SURVEY There are most search engine are ranking there search result with respect to user queries to make search easier[5].there are different search engines which provide relevant information to the user there are different algorithm used for that like Page rank, Weighted Page Rank, Hyperlink-induced Topic Search[1]. Web search engine is now becoming dominant approach for information retrieval. A new page rank algorithm is based on SimRank to score web pages [6].User needs specialized accurate result. Search engine depend on degree of importance of document, page rank and factor of relevance of document[2]the semantic web is idea therefore of connecting, integrating and analysing data from various data sources, web databases connected to each other and one machine connected to other machine. A semantic searching of keyword which is the semantic retrieval of information [3]. For overcoming the problem of pitfalls of existing approach an algorithm is proposed for computing the rank of document [4].Page rank method is also considered similarity and divergence for finding match degree between web page and user query[7]. III. EXPERIMENTATION AND RESULTS With the development of web there are different pages on web for different domain to know the popular pages; page ranking is method which gives the improved efficiency without reducing the speed. In this paper we have analysed several educational institutions and university to study the page rank and other important interfaces like external back links, referring domains, referring IPs, referring subnet. The proposed web based experimentation to identify these details and further classification and analysis of the web traffic. These external links and interfaces play the major role in the Page rank of any domain. 54
Page Rank External Back Link Referring domain Referring IP's Referring Subnet dpespune.com 1 373 75 73 73 jspmnarhe.in 2 48 18 12 9 ghrcem.raisoni.net 3 248 21 21 21 mitpune.com 4 2422 394 352 323 jspm.edu.in 5 677 18 15 97 unipune.ac.in 7 156291 1524 117 1 Table 1: Cumulative Analysis of the Interfaces to increase page rank Basically, the Referring domain is the domain that people "came from" when visiting your site. Your "Top Referrers" are the web sites that have brought visitors to your site. For example, if I'm on www.xyz.com domain and I follow a link on that site to get to your site, that is one referral for www.xyz.com. You will probably also notice statistics from something like "no referral." This means that the visitor reached your site by either a bookmark saved on their browser or typing in your site's url into their browser. For example, if you look in google for your name or some unique part of your website and Google returns your page in the results, when you click on it it takes you to your website. Google.com is thus the referring domain! If you link to your site from your signature in forums, and people click on it, then the forum becomes the referring site or domain. Page Rank 8 7 6 5 4 3 2 1 Analysis of Page Rank Fig. 1: Analysis of Page Rank Fig1 shows the Page rank of different domain like unipune.ac.in, jspm.edu.in, mitpune.com, ghrcem.raisoni.net, jspmnarhe.in, dpespune.com. Out of selected domain www.unipune.ac.in is having high rank than the other domain where www.dpespune.com is having less page rank than other domain. 55
Referring IP'S 4 35 3 25 2 15 1 5 Analysis of referring Fig. 2: Analysis of Referring Fig. 2 reflects the domain specific analysis based on the referring domains to it, where most of the web links referred by the respective domain based on the user interests which plays major role in the increasing page rank. External Backlink 3 25 2 15 1 5 Analysis Of External Backlink Fig. 3: Analysis of External Backlink According to Majestic SEO's glossary, a "Referring domain, also known as "ref domain", is a domain from which a backlink is pointing to a page or link."acklinks are often described as either "internal backlinks" or "external backlinks". The difference between the two is that an internal backlink is a link from one part of a specific domain (website) to another part of that same site. For example, on HubPages authors often use internal backlinks to connect one hub to another. An external backlink is a link that comes from a separate website. If you linked to your Facebook page in a hub about Facebook, for instance, this would be an external 56
backlink, because hubpages.com and facebook.com are two different domains. Generally when people are talking about how to get backlinks, they are speaking about external backlinks. Referring IP'S 4 35 3 25 2 15 1 5 Analysis of referring IP's Fig.4: Analysis of Referring IP s Many domains (websites) can be hosted on one IP address. A Referring IP refers to an IP which may host one or more websites, that may contain one or more links to a given target URL or. Referring Subnet 35 3 25 2 15 1 5 Analysis of referring subnet Fig.5: Analysis of Referring Subnet Multiple counts are calculate for links, de-duplicating links across pages ( which we refer to as backlink count ), across domains ( the domain count ), and across c-subnets. The c- subnet count is useful, as it is possible for the same class c subnet to be used by one, or 57
associated organisations. For larger sites, counting the unique linking relationships across C- Subnets can be useful IV. CONCLUSION As web traffic increased with the number of users and domains the searching becomes crucial. In this paper we have experimented for the same with the help of educational organizations domains and web traffic. We found that the page rank directly proportionate to the popularity of the s and obviously the user traffic on it. Further we have experimented all kind interfaces like interfaces like external back links, referring domains, referring IPs, referring subnet. As Page rank is a logarithmic calculation to determine page popularity; the number of interfaces with external world matters to attract the users followed by the traffic. We have proved the same with the traffic classifications based on these interfaces which plays major role in increasing the page rank. REFERENCES [1] Jain, A. ; Sharma, R. ; Dixit, G. ; Tomar, V.Page Ranking Algorithms in Web Mining, Limitations of Existing Methods and a New Method for Indexing Web Pages. Communication Systems and Network Technologies (CSNT), International Conference pages 64-645, 213. [2] Harb, H.M. ; Syst. &Comput. Dept., Al Azhar Univ., Cairo, Egypt ; Khalifa, A.R. ; Ishkewy, H.M.Personal search engine based on user interests and modified page rank.computer Engineering & Systems, ICCES, pages 411-417, 29. [3] Preethi, N.; Devi, T. New Integrated Case and Relation Based (CARE) Page Rank Algorithm Computer Communication and Informatics (ICCCI), pages 1-8, 213. [4] Sharma, Robin ; Kandpal, Ankita ; Bhakuni, Priyanka ; Chauhan, Rashmi ; Goudar, R.H. ; Tyagi,Web page indexing through page ranking for effective semantic search.asit Intelligent Systems and Control (ISCO), pages 389-392, 213. [5] Duhan, N. ; Sharma, A.K. ; Bhatia, K.K.Page ranking algorithm: A Survey, Advance Computing Conference, IEEE International pages 153-1535, IACC, pages153-1535,29 [6] ShaojieQiao ; Sch. of Inf. Sci. & Technol., Southwest Jiaotong Univ., Chengdu, China ; Tianrui Li ; Hong Li ; Yan Zhu.SimRank: A Page Rank approach based on similarity measure,intelligent Systems and Knowledge Engineering (ISKE), International Conference pages39-395, 21. [7] Yong Zhang ; Long-bin Xiao ;The Research about Web Page Ranking Based on the A-PageRank and the Extended VSM,; Bin Fan Fuzzy Systems and Knowledge Discovery.pages 223-227, 28S. [8] S B Patil, SachinChavan, PreetiPatil; High Quality Design and Methodology Aspects To Enhance Large Scale Web Services, International Journal of Advances in Engineering & Technology (IJAET-212), ISSN: 2231-1963, March 212, Volume3, Issue1, Pages175-185. (Journal Impact Factor: 1.96). [9] Srikantha Rao, PreetiPatil, S B Patil; Enhanced Software Development Strategy implying High Quality Design for Large Scale Database Projects, International Conference and Workshop on Emerging Trends in Technology ICWET 212, ISBN: 978--615-58717-2, TCET Mumbai, February 22 25, 212, Pages: 58-513. 58
[1] Srikantha Rao, PreetiPatil, S B Patil; Object-Oriented Software Engineering Paradigm: A Seamless Interface in Software Development Life Cycle, ACM_Asia_Pacific International Conference on Advances in Computing (ICAC- 28), Anuradha Engineering College, Chikhali, Feb 28. [11] Prof. S B Patil, Sachin Chavan, Dr. Preeti Patil and Prof. Sunita R Patil, High Quality Design to Enhance and Improve Performance of Large Scale Web Applications, International Journal of Computer Engineering & Technology (IJCET), Volume 3, Issue 1, 212, pp. 198-25, ISSN Print: 976 6367, ISSN Online: 976 6375. (Journal Impact Factor: 1.425) [12] S B Patil, D. B. Kulkarni; Improving web performance through Hierarchical caching & content aliasing, The 7th International Conference on Information Integration and Web-based Applications & Services, 19-21 September 25, Kuala Lumpur, Malaysia. [13] Srikantha Rao, PreetiPatil, S B Patil, SunitaPatil, Customized Approach for Efficient Data Storing and Retrieving from University Database Using Repetitive Frequency Indexing, IEEE INTERNATIONAL CONFERENCE PUBLICATIONS, RAIT 212, ISM Dhanbad, Jahrkhand, March 15 17, 212 (Aavailable on IEEE Xplore) Print ISBN: 978-1-4577-694-3, Digital Object Identifier: 1.119/RAIT.212.6194612 Page(s): 511 514. [14] Tanmaya Kumar Das, Dillip Kumar Mahapatra and Gopakrishna Pradhan, An Integrated Framework for Interoperable and Service Oriented Management of Large Scale Software, International Journal of Computer Engineering & Technology (IJCET), Volume 3, Issue 3, 212, pp. 459-483, ISSN Print: 976 6367, ISSN Online: 976 6375. [15] Alamelu Mangai J, Santhosh Kumar V and Sugumaran V,, Recent Research in Web Page Classification A Review, International Journal of Computer Engineering & Technology (IJCET), Volume 1, Issue 1, 21, pp. 112-122, ISSN Print: 976 6367, ISSN Online: 976 6375. 59