SEO is the process of optimizing webpages to increase their ranking in search engine results. The Google Hummingbird algorithm aims to better understand user search queries by taking into account contextual elements like location and the intent behind questions. It uses Google's knowledge graph to provide more relevant responses to complex queries. PageRank is Google's method to determine a page's importance - important pages receive a higher PageRank and rank higher in search results. Factors like backlinks, relevant content, and keywords impact a page's PageRank. The document provides examples of how PageRank is calculated using a mathematical formula and transition matrix.

1. Search engine
optimization [ SEO ]
A GAME OF PAGE RANKING
MD AFZAL RAIS
UNDER THE GUIDANCE OF
MS. CIJI K R
ASSISTANT PROFESSOR , DEPT. OF CSE
PESIT-BSC

2. 1. What is SEO ?
 SEO stands for search engine optimization.
 Process of maximizing page ranking in search engine result.
 A page ranking is measured by the position of web pages
displayed in the search engine results.
SEO

3. 2. How seo works ?
myWebsite
content
Search Algorithm
Title
keywords
Links
Search engine
SEO
meta tag

4. 3. Why seo is important ?

5. 3. cont….

6. 4. Google Hummingbird algorithm.
 Google hummingbird algorithm was announced in september,2013.
 Hummingbird’s strength is the ability to quickly understand the long and more
complex query and provide the best result to the user.
 Better than the previous version panda and penguin .
 Hummingbird algorithm is ‘question based’ , ‘conversational’ and semantic search (
takes into account why , when , who )
 Google Hummingbird aims to better understand the intent of the query instead of just
looking at the keywords used in the query.
 It uses the user information if you have shared with Google like geographic location.
 It starts with answering qusetion this is called conversational search.
SEO

7. 4. cont…
 It takes into account question based queries like ‘why’ , ‘when’ , ‘who’ ,
‘what’ etc .
 Pays more attention to each word in the query , ensuring that the whole
query – the whole sentence, is taken into account , rather than particular
word.
 It uses the Google’s ‘knowledge graph’ to improve the searching.
SEO

8. 5. Features of Hummingbird
 Hummingbird uses the ‘knowledge graph’ so that Google answer more
complex search queries and also improves the follow-up search process.
 For example: if you search ‘TAJ MAHAL’ and then do a second search for
‘ where it is ‘ , Google will understand the context of second query.
Where it is

9. 6. working model of Google
hummingbird algorithm.
User Complicated
query
Google search
engine
Pages sorted
according to
page rank
Sort into pages
according to the
query –taking into
account
“why”,”what” …
inputs
Most appropriate html
pages
Page
request
response
SEO

10. 7. Page rank
 Google Page Rank (Google PR) is one of the methods Google uses to determine a
page's relevance or importance. Important pages receive a higher Page Rank and are
more likely to appear at the top of the search results. Google Page Rank (PR) is a
measure from 0 - 10. Google Page Rank is based on back links.
 formulae used for calculating the ranking of a page.
 Page Rank(A) = ( 1-d ) + d + ……………..+
 PR(A) is the Page Rank of page A,
 C (T n) = is number of out links from Page T n .
 d = Dampling coefficient values between 0 and 1
 N=number of pages on internet.
Page Rank(T1)
C( T1 )
Page Rank(T n)
C(T n)N
SEO

11. 7. cont…
 Example
 The number of web pages N= 3
 The dampling parameter d= 0.7
A
B
C
SEO

12. 7 cont…

 PR(A) = (1 – d) × ( 1 / N) + d× ( PR(B) / 2 )
 PR(B) = (1 – d) × ( 1 / N) + d× ( PR(A) / 1 + PR(C)/1 )
 PR(C) = (1 – d) × ( 1 / N) + d× ( PR(B) / 2 )
 By solving the above system of linear equations, we get
 PR(A) = 0.2647 , PR(B) = 0.4706 , PR(C) = 0.2647
 The result shows that page B has the highest value amongst them because it
is linked to large number of pages and page B and the page C has the same
Ranking.
SEO

13. 7. cont…
Example 2
if a node has k outgoing
edges, it will pass on 1/k of
its importance to each of
the nodes that it links to.
SEO
A ij =
1/L j if there is link
from i to j ,
0 otherwise

14. 7 cont…
the transition matrix of the graph, A =
Suppose that initially the importance is uniformly distributed among the 4 nodes, each getting
1/4. Denote by v the initial rank vector, having all entries equal to 1/4. Each incoming link increases
the importance of a web page, so at step 1, we update the rank of each page by adding to the
current value the importance of the incoming links. This is the same as multiplying the matrix A
with v . At step 1, the new importance vector is v1 = Av. We can iterate the process, thus at step
2, the updated importance vector is v2 = A(Av) = A2v.
SEO

15. 7 cont…
After the 8th iteration
the matrix tend to
the equilibrium value. so
page1 has Ranking- 0.38
Page2 has 0.12
Page3 has 0.29
Page4 has 0.19
Page Ranking of page1 is
Highest because it is
Linked to large no of
Pages.
Page2 has least Ranking
SEO

16. 8 Conclusion
 For getting high google PageRank the website should have
 1. good backlinks from related sites. Related backlinks improves
the page ranking.
 2. content of the website should be related to the website.
 website which only focuses on keyword will be effected negatively.

17. 9 Bibliography
 https://www.slideshare.net/PriyodarshiniDhar/google-hummingbird-
algorithm-ppt/10
 http://www.math.cornell.edu/~mec/Winter2009/RalucaRemus/Lecture3/lect
ure3.html

18. THANK YOU