You are welcome to my blog today. This is the third and final part of the post: A Review Of Journal Article On Search Engine Operations as you can read the previous part here, Enjoy reading and have a wonderful day.. Kumari, Gupta & Dixit (2014) in their
research paper discussed the page rank algorithm.The paper highlights the
strengths, weaknesses. They explained that the Page Rank algorithm uses
link structure to determine the importance of web page. This algorithm
is based on random surfer model. According to them, the random surfer
model assumes that a user randomly keeps on clicking the links on a page
and if she/he get bored of a page then switches to another page
randomly. Thus, a user under this model shows no bias towards any page
or link. Page Rank (PR) is the probability of a page being visited by
such user under this model. Page Rank algorithm assumes that if a page
has a link to another page then it votes for that page. Therefore, each
in-link to a page raises its importance. Page Rank is a recursive
algorithm in which the Page Rank of a page depends upon the Page Rank of
the pages linking to it. Thus, not only the number of in-links of a page
influences its ranking but also the page ranks of the pages linking to
it. A page confers importance to the pages it references to by evenly
distributing its Page Rank value among all its out-links. Kumari, Gupta
& Dixit (2014) gave the working formula that the Page Rank algorithm
uses to rank a page. The formula is stated as follows.
PR(P) = 1 – d + d
· Where N0...Nn are the pages that point to page P.
· O(Ni) is defined as the number of links going out of page P.
· The parameter d is a Damping factor which can be set between 0 and 1.
They
further explained that damping factor, d is the probability of user’s
following the direct links and 1- d denotes the rank distribution from
non– directly linked web pages. It is usually set to 0.85.
Kumari,
Gupta & Dixit (2014) further outlined the strengths and weaknesses
of the Page Rank algorithm. The strengths included:
· Less
Time consuming:- As Page Rank is a query independent algorithm i.e. it
computes the rank score ahead, so it takes very less time .
· Feasibility:-This algorithm is more feasible as it computes rank score at indexing time not at query time.
· Importance: - It returns important pages as Rank is calculated on the basis of the popularity of a page.
·
Less susceptibility to localized links: - For calculating rank value of
a page, it consider the entire web graph, rather than a small subset,
it is less susceptible to localized link spam.
The weaknesses as highlighted by them include:
·
The main disadvantage is that it favors older pages, because a new
page, even a very good one, will not have many links unless it is part
of an existing web site.
· Relevancy of the resultant pages to the user query is very less as it does not consider the content of web page.
·
Dangling link: This occurs when a page contains a link such that the
hypertext points to a page with no outgoing links. Such a link is known
as Dangling Link.
· Rank Sinks: The Rank sinks problem occurs when in a network pages get in infinite link cycles.
· Dead Ends: Dead Ends are simply pages with no outgoing links.
·
Spider Traps: Another problem in Page Rank is Spider Traps. A group of
pages is a spider trap if there are no links from within the group to
outside the group.
· Circular References: If you have circle references in your website, then it will reduce your front page’s Page Rank.
Wenpu
Xing and Ali Ghorbani projected a Weighted Page Rank (WPR) algorithm
which is a modification to the Page Rank algorithm. This algorithm
assigns a larger rank values to the more important pages rather than
dividing the rank value of a page evenly among its outgoing linked
pages. Each outgoing link gets a value proportional to its importance.
The importance is assigned in terms of weight values to the incoming and
outgoing links. The strengths of the weighted page rank include:
· Quality: Quality of the pages returned by this algorithm is high as compared to Page Rank algorithm.
·
Efficiency: It is more efficient than Page Rank because rank value of a
page is divided among its out-link pages according to importance of that
page.One noticeable weakness about this algorithm is that as this
algorithm considers only link structure not the content of the page, it
returns less relevant results to the user query. I have these posts series have given you a better understanding of search engine operations. Have a nice time and Thank you for reading.
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A Review Of Journal Article On Search Engine Operations (Part 3)
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