ArticlePDF Available

Web Search Engine

Authors:
  • Lendi Institute of Engineering and Technology (A)

Abstract and Figures

The World Wide Web (WWW) allows people to share information or data from the large database repositories globally. We need to search the information with specialized tools known generically as search engines. There are many search engines available today, where retrieving meaningful information is difficult. However to overcome this problem of retrieving meaningful information intelligently in common search engines, semantic web technologies are playing a major role. In this paper we present a different implementation of semantic search engine and the role of semantic relatedness to provide relevant results. The concept of Semantic Relatedness is connected with Wordnet which is a lexical database of words. We also made use of TF-IDF algorithm to calculate word frequency in each and every webpage and Keyword Extraction in order to extract only useful keywords from a huge set of words. These algorithms are used to retrieve much optimized and useful results to the user.
Content may be subject to copyright.
Page 774
Web Search Engine
Bosubabu Sambana, MCA, M.Tech
Assistant Professor,
Dept of Computer Science & Engineering,
Simhadhri Engineering College, Visakhapatnam, AP-531001, India.
Abstract:
The World Wide Web (WWW) allows people to share
information or data from the large database
repositories globally. We need to search the
information with specialized tools known generically
as search engines. There are many search engines
available today, where retrieving meaningful
information is difficult. However to overcome this
problem of retrieving meaningful information
intelligently in common search engines, semantic
web technologies are playing a major role. In this
paper we present a different implementation of
semantic search engine and the role of semantic
relatedness to provide relevant results. The concept
of Semantic Relatedness is connected with Wordnet
which is a lexical database of words. We also
made use of TF-IDF algorithm to calculate word
frequency in each and every webpage and
Keyword Extraction in order to extract only useful
keywords from a huge set of words. These
algorithms are used to retrieve much optimized and
useful results to the user.
Keywords:
TF-IDF, Semantic Relatedness, Keyword Extraction,
Word net.
1. INTRODUCTION:
The grandfather of all search engines was Archie,
created in 1990 by Alan Emtage, a student at McGill
University in Montreal. World Wide Web provides us
with huge amount of necessary data digitally available
as hypertext Data may be WebPages, images,
information and other type.
This hypertext pool is dynamically changing due to
this reason it is more difficult to find useful
information.In 1995, when the number of “usefully
searchable” Web pages was a few tens of millions, it
was widely believed that “indexing the whole of the
Web” was already impractical or would soon become
so due to its exponential growth. A little more than a
decade later, the GYM search enginesGoogle,
Yahoo!, and Microsoftare indexing almost a
thousand times as much data and between them
providing reliable sub second responses to around a
billion queries a day in a plethora of languages. If this
were not enough, the major engines now provide much
higher quality answers.
For most searchers, these engines do a better job of
ranking and presenting results, respond more quickly
to changes in interesting content, and more effectively
eliminate dead links, duplicate pages, and off-topic
spam .In this two-part series, we go behind the scenes
and explain how this data processing “miracle” is
possible.
We focus on whole-of-Web search but note that
enterprise search tools and portal search interfaces use
many of the same data structures and algorithms.
Search engines cannot and should not index every
page on the Web. After all, thanks to dynamic Web
page generators such as automatic calendars, the
number of pages is infinite. To provide a useful and
cost-effective service, search engines must reject as
much low-value automated content as possible. In
addition, they can ignore huge volumes of Web-
accessible data, such as ocean temperatures and
astrophysical observations, without harm to search
effectiveness.
Page 775
The History of Search Engines:
Modern search engines are pretty incredible complex
algorithms enable search engines to take your search
query and return results that are usually quite accurate,
presenting you with valuable information nuggets
amidst a vast information data mine [1].
Search engines have come a long way since their early
prototypes, as our Internet Search Engines History info
graphic illustrates. From improvements in web
crawlers and categorizing and indexing the web, to
introducing new protocols such as robots.txt so that
webmasters have control what web pages get crawled,
the development of search engines has been the
culmination of multiple search technologies that
developed from different search engines. Alta Vista
was the first search engine to process natural language
queries; Lycos started strong with a system
categorizing relevance signals, matching keywords
with prefixes and word proximity; and Ask Jeeves
introduced the use of human editors to match actual
user search queries,
Most of the traditional search engines search
for keywords to answer queries from users. The main
focus of these search engines is solving queries with
close to precise results in small period of time
using much advanced algorithms. However, it
shows that such search engines are incompetent in
answering queries intelligently using traditional
approach. The Semantic Web will support more
efficient discovery, automation, integration and reuse
of data and provide support for interoperability
problem which cannot be resolved with current web
technologies. In short it will intelligently understand
the user query and search for those results that match
not only the keyword but also the meaning of that
query.
In this paper, we will make modification over the
existing search engine by adding an additional
concept of keyword extraction and semantic
relatedness calculation. Semantic relatedness here
is a metric which calculates the relation between
words. This metric is computed with the help
of Wordnet. Another metric used in the current
approach is TF-IDF (Term Frequency-Inverse
Document Frequency).
It is used to calculate the relevancy of each word and
relevance of each document. Finally, Web search
engines have no access to restricted content, such as
pages on corporate intranets. What follows is not an
inside view of any particular commercial engine
whose precise details are jealously guarded secrets
but a characterization of the problems that whole - of -
Web search services face and an explanation of the
techniques available to solve these problems.
2. BACKGROUND:
2.1 Search Engine:
Search Engine provides the gateway for most of the
users trying to explore the huge information base of
web pages. Search engines are a program that search
documents for specified keywords on search for
information on the World WideWeb and returns a list
of the documents where the keywords were found. A
Search Engine is really a class of programs. However,
the term is often used to specifically describe systems
like Google, Bing and Yahoo! Search that enable users
to search for documents on the World Wide Web [2].
FIGURE 1: EXAMPLE OF SEARCH ENGINE
2.2 Cloud computing:
Cloud computing is continuously developing as a
standard for sharing the data over the remote storage in
an online cloud server. Cloud services offers great
amenities for the users to enjoy the on-demand cloud
applications without any obligations related to data.
During the data retrieving, different users may be in a
cooperative relationship, and hence data distribution
becomes important.
Page 776
2.3. Autantication :
A legal user can access its own data fields, only the
authorized partial or entire data fields can be identified
by the legal user, and any forged or tampered data
fields cannot deceive the legal user.
2.4. Cloud Characteristics:
One of the oft-cited advantages of cloud computing is
its elasticity in the face of changing conditions. For
example, during seasonal or unexpected spikes in
demand for a product retailed by an e-commerce
company, or during an exponential growth phase for a
social networking Website, additional computational
resources can be allocated on the fly to handle the
increased demand in mere minutes (instead of the
many days it can take to procure the space and capital
equipment needed to expand the computational
resources in-house).Similarly, in this environment, one
only pays for what one needs, so increased resources
can be obtained to handle spikes in load and then
released once the spike has subsided. Having DBMS in
the cloud will give advantage in fast and elastic
computing.
2.5 Cloud Storage:
Cloud storage means the storage of data online in
the cloud, wherein a company's data is stored in and
accessible from multiple distributed and connected
resources that comprise a cloud.
2.6 Data anonymicy:
Any irrelevant entity cannot recognize the exchanged
data and communication state even it intercepts the
exchanged messages via an open channel.
2.7. User privacy :
Any irrelevant entity cannot know or guess a user’s
access desire, which represents a user’s interest in
another user’s authorized data fields. If and only if the
both users have mutual interests in each other’s
authorized data fields, the cloud server will inform the
two users to realize the access permission sharing.
Figure.2: DBMS in the Cloud Architecture
3. RELATED WORK:
Literature Survey:
Search Engine:
Search Engine provides the gateway for most of the
users trying to explore the huge information base of
web pages. Search engines are a program that search
documents for specified keywords on search for
information on the World Wide Web and returns a list
of the documents where the keywords were found. A
Search Engine is really a class of programs; however,
the term is often used to specifically describe systems
like Google, Bing and Yahoo! Search that enable users
to search for documents on the World Wide Web.
Figure.3: Search Engines in Web
Page 777
Goals of Search Engine:
Quality - Means effectiveness can be defined as
to retrieve the most relevant set of document for
a query. Process text and store text statistics to
improve relevance be used.
Speed - Means efficiency may be defined as a
process queries from users as fast as possible
For it specialized data structure should be used.
How web Based Search Engine Works?
Web based search engine works by saving the
information of many web pages, which they retrieve
itself. These pages are retrieved by a web crawler
which is also called spider which follows every link on
the site. Search engine is a term used for information
retrieval. Search engine match queries against an index
that they create. This index contains the word in each
document, pointers to their location within the
document. This is called inverted file [4]
Figure.4: How do Search Engine Work
Web search engines get their information by web
crawling from site to site. The "spider" checks for the
standard filename robots.txt, addressed to it, before
sending certain information back to
be indexed depending on many factors, such as the
titles, page content, JavaScript, Cascading Style
Sheets (CSS), headings, as evidenced by the standard
HTML markup of the informational content, or its
metadata in HTML meta tags. Indexing means
associating words and other definable tokens found on
web pages to their domain names and HTML-based
fields. The associations are made in a public database,
made available for web search queries.
A query from a user can be a single word. The index
helps find information relating to the query as quickly
as possible. Some of the techniques for indexing,
and caching are trade secrets, whereas web crawling is
a straightforward process of visiting all sites on a
systematic basis. Between visits by the spider, the
cached version of page (some or all the content needed
to render it) stored in the search engine working
memory is quickly sent to an inquirer. If a visit is
overdue, the search engine can just act as a web
proxy instead. In this case the page may differ from the
search terms indexed. The cached page holds the
appearance of the version whose words were indexed,
so a cached version of a page can be useful to the web
site when the actual page has been lost, but this
problem is also considered a mild form of linkrot.
Figure.5: High-level architecture of a standard
Web crawler
Typically when a user enters a query into a search
engine it is a few keywords. The index already has the
names of, the sites containing the keywords, and these
are instantly obtained from the index. The real
processing load is in generating the web pages that are
the search results list: Every page in the entire list must
be weighted according to information in the
indexes. Then the top search result item requires the
lookup, reconstruction, and markup of
the snippets showing the context of the keywords
matched. These are only part of the processing each
search results web page requires, and further pages
(next to the top) require more of this post processing.
Beyond simple keyword lookups, search engines offer
their own GUI- or command-driven operators and
search parameters to refine the search results.
Page 778
These provide the necessary controls for the user
engaged in the feedback loop users create
by filtering and weighting. While refining the search
results, given the initial pages of the first search
results. For example, from 2007 the Google.com
search engine has allowed one to filter by date by
clicking "Show search tools" in the leftmost column of
the initial search results page, and then selecting the
desired date range.[16] It's also possible to weight by
date because each page has a modification time. Most
search engines support the use of the Boolean AND,
OR and NOT to help end users refine the search query.
Boolean operators are for literal searches that allow the
user to refine and extend the terms of the search. The
engine looks for the words or phrases exactly as
entered. Some search engines provide an advanced
feature called proximity search, which allows users to
define the distance between keywords. There is
also concept-based searching where the research
involves using statistical analysis on pages containing
the words or phrases you search for. As well, natural
language queries allow the user to type a question in
the same form one would ask it to a human. A site like
this would be ask.com.
The usefulness of a search engine depends on
the relevance of the result set it gives back. While
there may be millions of web pages that include a
particular word or phrase, some pages may be more
relevant, popular, or authoritative than others. Most
search engines employ methods to rank the results to
provide the "best" results first. How a search engine
decides which pages are the best matches, and what
order the results should be shown in, varies widely
from one engine to another.[14] The methods also
change over time as Internet usage changes and new
techniques evolve. There are two main types of search
engine that have evolved: one is a system of
predefined and hierarchically ordered keywords that
humans have programmed extensively. The other is a
system that generates an "inverted index" by analyzing
texts it locates. This first form relies much more
heavily on the computer itself to do the bulk of the
work.
Most Web search engines are commercial ventures
supported by advertising revenue and thus some of
them allow advertisers to have their listings ranked
higher in search results for a fee. Search engines that
do not accept money for their search results make
money by running search related ads alongside the
regular search engine results. The search engines make
money every time someone clicks on one of these ads.
Features of Web based Search Engine:
Following are the basic features for evaluating web
based search engine [5].
Web Indexes-When a web search request is
generated. It is the web index generated by web
robots or spiders. The combination of web
indexes affects the performance of a web search
engine. Three main key points to design of web
index are coverage, update frequency and the part
of indexed web page.
Search Capability- Search Engine must provide
Phrase searching, truncation Search capacity finds
its Performance efficiency, throughput.
Retrieval Issue -This issue proceed on three Key
points- Precision, Recall and response time.
Write Option-Write option or output option
provides the deal with actual content of output.
User effort -User effort means the documentation
and interface. Good prepared documentation and
good interface play a different role in users’
selection of web search engine. User will only
user the search engine when the interface is user
friendly only.
Quality of Good Search Engine:
Ability to produce the most relevant result to
any given search.
A true search engine is an automated software
program that moves around the web collecting
WebPages to include in its catalog or database.
It searches when user requests information from
a search engine has its own catalog or database
of collected WebPages, so you will get different
results. Hits by using different search engines.
Page 779
Figure.6: Index and working Process
Compression:
Indexers can reduce demands on disk space and
memory by using compression algorithms for key data
structures. Compressed data structures mean fewer
disk accesses and can lead to faster indexing and faster
query processing, despite the CPU cost of compression
and decompression.
Early termination:
The query processor can save a great deal of
computation if the indexer creates indexes in which it
sorts postings lists in order of decreasing value. It can
usually stop processing after scanning only a small
fraction of the lists because later results are less likely
to be valuable than those already seen. At first glance,
early termination seems to be inconsistent with
skipping and compression techniques, which require
postings to be in document number order.
Figure.7: Information Retrieval Process in web
search
Timeline (full list) [3]
Year
Engine
Current status
1993
W3Catalog
Inactive
Aliweb
Inactive
JumpStation
Inactive
WWW Worm
Inactive
1994
WebCrawler
Active, Aggregator
Go.com
Inactive, redirects to
Disney
Lycos
Active
Infoseek
Inactive
1995
AltaVista
Inactive, redirected to
Yahoo!
Daum
Active
Magellan
Inactive
Excite
Active
SAPO
Active
Yahoo!
Active, Launched as a
directory
1996
Dogpile
Active, Aggregator
Inktomi
Inactive, acquired by
Yahoo!
HotBot
Active (lycos.com)
Ask Jeeves
Active (rebranded
ask.com)
1997
Northern Light
Inactive
Yandex
Active
1998
Google
Active
Ixquick
Active also as Startpage
MSN Search
Active as Bing
empas
Inactive (merged with
NATE)
1999
AlltheWeb
Inactive (URL redirected
to Yahoo!)
GenieKnows
Active, rebranded
Page 780
Yellowee.com
Naver
Active
Teoma
Inactive, redirects to
Ask.com
Vivisimo
Inactive
2000
Baidu
Active
Exalead
Active
Gigablast
Active
2003
Info.com
Active
Scroogle
Inactive
2004
Yahoo! Search
Active, Launched own web
search
(see Yahoo! Directory,
1995)
A9.com
Inactive
Sogou
Active
2005
AOL Search
Active
GoodSearch
Active
SearchMe
Inactive
2006
Soso (search
engine)
Active
Quaero
Inactive
Ask.com
Active
Live Search
Active as Bing, Launched
as
rebranded MSN Search
ChaCha
Active
Guruji.com
Inactive
2007
wikiseek
Inactive
Sproose
Inactive
Wikia Search
Inactive
Blackle.com
Active, Google Search
2008
Powerset
Inactive (redirects to Bing)
Picollator
Inactive
Viewzi
Inactive
Boogami
Inactive
LeapFish
Inactive
Forestle
Inactive (redirects to
Ecosia)
DuckDuckGo
Active
2009
Bing
Active, Launched as
rebranded Live Search
Yebol
Inactive
Mugurdy
Inactive due to a lack of
funding
Scout (Goby)
Active
NATE
Active
2010
Blekko
Inactive, sold to IBM
Cuil
Inactive
Yandex
Active, Launched global
(English) search
2011
YaCy
Active, P2P web search
engine
2012
Volunia
Inactive
2013
Halalgoogling
Active, Islamic / Halal
filter Search
2013
Egerin
Active, Kurdish / Sorani
Search engine
Search engine
Google
69.24%
Bing
12.26%
Yahoo!
9.19%
Baidu
6.48%
Page 781
Search engine
Market share in September
2015-16
AOL
1.11%
Ask
0.24%
Lycos
0.00%
4. REASEARCH WORK:
Existing System:
Problems Facing by Current Search Engines:
Crawlers are not able to analyze the content of
keyword in web page before they download it.
User submits his request for retrieval of
information without mentioning the content in
which he otherwise desire.
Crawler treats user search request in isolation.
There is a requirement to prepare separate files
for each web document.
Augmentation is required in HTML document.
Types of Search Engine:
According to functioning three types of search engine
1. Crawler Based Search Engine:
They create their listings automatically. Spider
builds them. Computer algorithm ranks all
pages. These types of search engines are heavy
and often retrieve a lot of information. For
complex search it allows to search within the
results of previous search and enable you to
refine search results.
2. Human Power Directories:
These are designed by human selection means
they depend on professional to create listings.
These never contain full text or webpage they
link to.
3. Hybrid Search Engine:
These are different from traditional text oriented
search engine such as Google or directly based
searched engine such as Yahoo in which each
program operates by comparing a sets of
metadata.
4. Content/topic
5. Web search engines
6. Selection-based search engines
7. Meta search engines
8. Semantic search engine
9. Desktop search tools
10. Web portals and vertical market websites that
have a search facility for online databases
11. Deep Web Search Engines
Search Engine Optimization (SEO):
Search Engine Optimization is the procedure of
improving the visibility of a website or webpage in
search engine via the natural or unpaid searched
results. Optimization may target different types of
search like image search, local search, video search,
academic search, new search, industry specific vertical
search .It can also be define as the process of affecting
the visibility of a website or webpage in search engine.
In search engine optimization updating or modification
of all variables to get a better location in the search
engine takes place. We start with Search Engine
Optimization and how it can be used to formulate
internet marketing. Strategy as well as Technical
aspects of SEO.
A) Using SEO as a marketing strategy it can be
described as a method of getting our website to
rank higher in search engine as Google; Yahoo,
Means that if user likes to search for a list of
optimized keywords the chances are that the
visitors see your site on first few places may be
good.
B) Parameters for evaluating SEO of websites- Page
Rank- Page rank of each page depends on the
page rank of pages pointing to it.
C) To enhance our site page rank few key ideas are
inbound links, outbound links, Dangling links,
domain and File names and broken links.
Search Engine Optimization Technique:
Basically three techniques for search engine
optimization are there
Page 782
Directory Submission: It is the important
technique in Search Engine Optimization to
create in coming links to a website through
indexed page and category. Different directory
provides free service to website. Directory
submission request information regarding
URL, title, keywords.
Keyword Generation: All search engine
optimization need some words to elaborate
information based on these words. Keywords
should be of your organization on subject.
This process can be proceeding by different
online tools like word tracker, yahoo keyword
selector tool, Google Ad words.
Link Exchange: To start up any website for
any business we need reciprocal link exchange
with other websites. It is the procedure to take
place link on other website and other website
place links on our site.
Tools of Search Engines Optimization:
SEO tools are the operators that optimize the search
engine functionality Basics tools are-
Keyword Tool- Include keyword research tools,
keyword density analysis tool, and competitor
analysis tool. It can used for website classification
and regulate keywords deployment columns.
Example Keyword selector tool, external tool
Link Tool- These tools include link popularity
spider simulator, by which ranking of website can
be increased.
Usability Tool- This tool test pages display
effects in different resolution, different operating
system, and different browser. These include
HTML and CSS validation, Firefox extension,
and Page speed test.
Keywords Strategy- When choosing keywords,
it must be related with products, area, service.
High duality incoming Link- Submit the website
to search engine directories, find websites to
exchange links. In it import link, outbound links,
internal link are used.
Figure.8: Overview of SEO
Disadvantage:
Present System does not have the option of
granting/revoking data access in Proper manner for
user/clients needs.
Proposed System:
In this paper, we are proposed in new method in this
web Search Process
Proposed Architecture:
This architecture should be capability of systems
working in a Distributed manner. In it all processing
should be processed on idle computer. The distributed
architecture should not increase Network traffic. All
the systems connected in a Network should be
operated using some firewalls. The module should be
as much as easy to plug and play.
Crawler Unit: - It will crawl a website. It will
need to use secondary memory to store the web
pages downloaded before analysis. The web pages
should be saved on each host system, rather than
transferred to the control unit to minimize the
network traffic. In crawler unit the technique of
Data mining that is cluster may be applied by
which similar data elements, similar URL’s may
be kept as a cluster. Cluster helps us to crawl the
different pages. Different types of clustering
algorithm may be used to crawl the useful URL’s.
Control Unit: - When a crawler requests a job or
sends some data elements the control unit will
live on a web server and will be used by it.
Page 783
It will need to save the commands that the user like to
be process. This can also be understudied by this
example as doc file is saved on server.
Messaging System: - To satisfy the necessity of
crawler and control unit the crawler must be able
to download and process websites with less
transmission with control unit-The crawler unit
starting a crawl, sending a message to control unit
shows that it is ready to execute a new request.
The control unit sending an instruction to the
crawler showing a site to crawl and type of
processing to be performed on downloaded
website.
Figure A
The problem is that control unit outside the network
can not initiate communication with component inside
but only can send information in response to a request
for it as per Figure-A. This architecture can be
successful for any component. Where the control unit
is on a public access web server. The architecture
described here is employed to design a system for the
job of analyzing the link structure of web sites. This
program had not run quickly enough to consider
necessary number of websites and so it has been
individually setup and run on a number of computers
parallel. One more feature that was built into the
crawler was a option of types of checking for duplicate
pages to be used in a website crawl.
There are three (3) options-
1. Uses no page checking thinks that two page
with different pages are different pages.
2. Use HTML page checking oppose new page
which is identical HTML to later retrieved
page.
3. Use weak HTML Page Checking.
Clustering is a method in which like records are
grouped together. This technique is done to give the
end user a high level view of what is going on in the
data set.Sometimes clustering is performed not so
much to keep records together as to make it easier to
see when one record sticks out from the rest.
Figure B
Clusters may be created either statistically or by using
artificial intelligence methods. Clusters can be
analyzed automatically by a program or by using
visualization techniques as described in fig- B.
Criteria for site optimization:
For a new website to be optimized for the given
keywords need to have some technical issues checked
[5].
Meta descriptions or Metadata Keywords
Keyword analysis
Title Tags
Page content
Headlines Tag
URL structure and domain
Images Tag
Page Load time
XML site Map
Meta data using schema
Site map
Robot.txt
404 error
Duplicate contents
Crawling Techniques:
Focused Crawling:- Focused crawler is designed
only to retrieve documents on a specific topic,
thus reducing the amount of network traffic and
downloads. The goal is to selectively seek out
pages that are relevant to a pre defined set of
topics. This leads to savings in Hardware and
Network resources and helps keep the crawl more
up to date.
Page 784
Distributed Crawling:- A single crawling
process is non-useful for large scale engine that
needs to fetch large amount of data rapidly.
Distributing the crawling activity via multiple
processes can help build a scalable, system which
is fault tolerant system. Distributing the load
decreases hardware requirements and at the same
time increases the overall download speed and
reliability.
Advantage:
Here we proposed the methods using Web Search in an
efficient manner without any restrictions.
CONCLUSION:
In this work, we have identified a challenges during
the architecture defined here is capable of crawling a
large number of websites. It cannot process 100%
automatic for jobs that involve crawling entire
websites without heuristic for finding or searching
duplicate pages. This design approach is suitable for
the situations where a job can be divided into a
disconnected crawling based job by which execution
on different systems should not produce a problem.
It may be non-useful if the crawls have to cross
transmission each other in any case, for example to
check a page from one crawl had already been found
in another. Second case may be if the data mining has
to be perform upon the whole data set is an integrated
way.
FUTURE WORK:
In this work, though we have identified and studied
and research a Search engine is a complex system on
which further enhancements should be made. Some of
the key ideas are like using query caching, disk
allocation, sub indices, RAID techniques. More
advanced algorithms are also required to decide which
old pages should be re crawled and which should be
new one crawl. Normal features by commercial Search
engine like Boolean operators, negations, steaming use
of AI should be added.
Acknowledgment:
This thesis paper is Heartily Dedicated to my parents
Sri.S.Dandasi & Smt.Janaki, Mrs.Suneetha and My life
Inspirer Eminent Scientist Sri.Dr.A.P.J.Adbulkalam.
Authors’ Profiles:
Bosubabu Sambana working
with as an Assistant Professor
in Simhadhri Engineering
College, Visakhapatnam. He is
completed Master of Computer
Applications and Master
Degree in Computer Science & Engineering from
Jawaharlal Nehru Technological University
Kakinada, Pursing Master of Science in Mathematics,
Andhra University, and Andhra Pradesh, India. He has
4 years good teaching experience and having a good
Knowledge on Space Research, Future Internet
Architecture, Cloud Computing, Internet of
Things/Services/Data, Computer Network and
Hacking along with Computer Science Subjects. He is
Published 4 Research Papers in various reputed
International Journals and Magazines. He is the
member of NASA, INTERNET SCOCIETY, W3C,
MECS-PRESS, IAENG, IAAE and IJECSE.
REFERENCES
[1] http://www.en.wikipedia.org/worldwideweb
history.
[2] web search engine in Google Search .
[3] Search engine Time in Available:
http://www.en.wikipedia.org/
[4] Web search part:1,2 David Hawking,CSIRO
ICT Centre.
[5] Rajesh Singh, S.K. Gupta, IJAIEM- ISSN 2319
4847, Volume 2, Issue 9, September 2013
[6] Images and Information
http://www.google.co.in/
[7] All content are Available :
http://www.wikipedia.org/
ResearchGate has not been able to resolve any citations for this publication.
ResearchGate has not been able to resolve any references for this publication.