International Journal of Engineering Trends and Technology (IJETT) – Volume17 Number5–Nov2014
An Empirical Architecture for Efficient Search Results in Mobile
1
S.Peddiraju, 2Dr.M.NagabhushanaRao
1
Final Mtech student, 2Professor
Dept of Cse, Swarnandhra College of Engineering& Technology, Narsapuram, A.P
Abstract: Retrievalof user interesting results over Mobile
Search engine is always an interesting and important
research issue in now days of information retrieval, due to
there is a rapid growth of mobile usage of user. Even
though various traditional approaches available,
performance and time complexity issues are the primary
factors while implementation of the search engines, we are
proposing an efficient personalized mobile search engine
with efficient features of Mining, ranking and cache
implementation over the service web services.
I. INTRODUCTION
The responsibilities of the client is to receive the
user’s request and also submitting the requests to the
PMSE server and get the result and collects clickthrough in
order to derive personal preferences and also user profile
stores in PMSE client to provide privacy preserving of the
data of the user. Similarly the responsibilities of the server
are to send request to a commercial search engine and also
training, reranking of search results earlier they returned to
client.
Users have different queries for identification of
the content or location has importance based upon the
query, now to normalize the characterized diversity of the
concepts with the associated query and the user’s necessity
for the relevance’s we propose the location and content
entropies for the query to find the quantity of the data
stored by the client-server network. Similarly we measure
the interest of finding the location of the user to the their
results of their necessity fulfillment and also click content
and location entropies
Depending upon these we find the effectiveness of
identifying a query for the personalization of the required
user information of finding the location based on content
and location entropies and then reranking them to
preferences prior to the returned data to the client
The World-Wide Web [3, 4] has reached a size
where it is becoming increasingly challenging to satisfy
certain information needs. While search engines are still
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able to index a reasonable subset of the (surface) web, the
pages a user is really looking for are often buried under
hundreds of thousands of less interesting results. Thus,
search engine users are in danger of drowning in
information. Adding additional terms to standard keyword
searches often fails to narrow down results in the desired
direction. A natural approach is to add advanced features
that allow users to express other constraints or preferences
in an intuitive manner, resulting in the desired documents
to be returned among the first results. In fact, search
engines have added a variety of such features, often under a
special advanced search interface, but mostly limited to
fairly simple conditions on domain, link structure, or
modification date.
Third, geographic search supports locally targeted
web advertising, thus attracting advertisement budgets of
small businesses with a local focus. Other opportunities
arise from mining geographic properties of the web, e.g.,
for market research and competitive intelligence.
II. RELATED WORK
Various Search engines developed from the so many Year
of research from the various researchers, But they still have
the vulnerabilities in optimization, Specifically in
personalized mobile search engines, Only the mining of
results may not give the optimal results to the user search
query, Time complexity and space complexity are also the
factors while implementing the personalized mobile search
engines [7, 8].
 Round trip should be performed for each search
 Lack of cross language communication
 Increases the duplication of business logic and
risk factor chances
 Less performance
We propose a personalized mobile search engine
(PMSE) technique that catches the users’
necessity of mining the data by click through as it
is very important aspect to get the information of
location over search in mobile through the concept
of mining the data. PSME classifies into two
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International Journal of Engineering Trends and Technology (IJETT) – Volume17 Number5–Nov2014

concepts which are content concepts and location
concepts, location concepts also support users’
location which is supported by GPS System. The
preferences of the users are organized based on
ontology, multifaceted profile these are used to get
the order of the preferences and also observe the
search results for future, basing on personalized
ranking function to get the rank of the preferences.
Four Entropies are proposed to stabilize the
weights between the content and facets location to
get the characterized diversity of the concepts
with the associated query and find the relevance
necessity of the user. PMSE over network using
client-server we propose complete architecture
and implementation design. In the client-server
design the client perform the tasks like collects the
data ,stores the data within it locally, protect
privacy for the click through data and so on
coming for the server the tasks such as training
,concept extraction, reranking such heavy works
are performed by the server at PMSE.in addition it
also provide the privacy by restricting the
information of the user profile between two
privacy parameters exposed to PMSE We propose
PMSE prototype on the Google Android platform.
Experimental
results
show
that
PMSE
significantly provides accuracy comparing to the
baseline.
Documents score can compute based on
occurrences of a keyword in individual and multiple
documents and inverse document frequency parameters. In
this technique, it concentrates on frequency of input query
or keyword but not with time relevance of the document
or file, so there is no order of priority for recently updated
documents even though user interesting or relevant result.
Time relevance based technique works with recent
time stamp of the uploaded document or file along with
weight. Clustering based mechanisms gives good results by
combing the similar type of objects based the time
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relevance and file relevance scores between the documents
[8].
The relationships retrieve the priorities of the
users.
Traditional
search
engines,such
as
Google,Bing,Yahoo currently cannot get the
relationships. Using Search engines, for example,
when a user clicks on a URL or link on user search
results, the browser directly goes to extract theWeb
pages based on the given URL or website. The search
engine doesnot know what link has been clicked. To
allow the searchengine to know what link clicked, each
click needs to be passed through the search engine.
The search keywords and the destination URL is
embedded on each link provided on the search results.
When a user clicks a link, the browser passes these
data to the search engine. The search engine records
the data and then redirects the browser to go to retrieve
the destination Web page.
III. PROPOSED WORK
We are proposing a novel model of mobile search engine
with efficient features to full fill theend user requirements
by the approaches of mining the previous search results
based on the location of the search result for the user
relevant query, ranking the user search query results and
Cache implementation for the Frequently accessed
previous search results to improve the performance from
the both ends. Proposed system provides language
interoperability through service oriented application.
Reduces the chances of redundancy and risk factors and
improves the mobile performance by implementing the
simple cache and rank oriented results can be retrieved.
Web services is the technology to create
service oriented applications, it reduces the duplication of
code by maintain the business logic at single location. The
main objective of the web services is language
interoperability (i.e. any standard language can
communicate with other language) and reduces the chances
of malfunctions from the user end
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International Journal of Engineering Trends and Technology (IJETT) – Volume17 Number5–Nov2014
Database
Business
Logic
Wsdl with Soap protocol
UI (VB.Net)
UI ( Java)
UI (Android)
Fig.1 Web Service Architecture
Cache is the mechanism which stores the
previously accessed information i.e. round trips over the
request and responses during the user query. If a user
makes the same query which is searched previously, no
need to process a round trip again, because once results
retrieved from the server it can be stored in the cache,
second time onwards query results retrieved from cache.
Initially it computes the file relevance score in terms of
term frequency and inverse document frequency, Term
frequency (Tf) gives the number of occurrences of the
keyword in a document and Inverse document frequency
gives the number of occurrences of the keyword in all the
documents then file relevance score can be calculated as
follows
3
.
Web service
Data base
4
.
2. Forward Request
Mobile User
5. Results
1. New Account
7. Search Results
Cache
8. Send Request
6. Store in cache
9. Result
Fig.2 Proposed Architecture
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International Journal of Engineering Trends and Technology (IJETT) – Volume17 Number5–Nov2014
Sequential Steps for Rank oriented results from Web service as follows
Step1: Initially user makes a request with input keyword
from Mobile
Step2: it reaches to cache and checks whether it is retrieved
previously, if available in cache then returns from cache
else forwards the request to service
Step3: service retrieves rank oriented results based on term
frequency from the data base.
F_ Score=TF*IDF
FScore=file relevance score
TF=term frequency
IDF=Inverse document frequency
Step4: retrieved results stored in Cache for future purpose
Step5: Finally rank oriented results can be forwarded to
mobile User
For experimental analysis we implemented service
oriented application
in Dot Net and Android. Business
logic can be maintained in Dot net web service, client end
or user interface can be android emulator. Input query
canbe passed through Android Mobile and logical
computation can be done at service oriented application.
IV. CONCLUSION
We are concluding our research work with efficient
Ranking oriented results approach through service oriented
application in mobile applications. Cache Implementation
increases the performance by reducing the response time or
execution time if a query is processed previously, our
experimental results shows efficient results than the
traditional approaches.
REFERENCES
[1] E. Agichtein, E. Brill, and S. Dumais, “Improving Web
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Proc. Int’l ACMSIGIR Conf. Research and Development
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BIOGRAPHIES
S.Peddiraju , final m.tech student,
Department of Cse, Swarnandhra College
of
Engineering & Technology,
Narsapuram, A.P. His interested areas are
data mining, network security.
Dr.M.NagabhushanaRao,
Professor,
Department of Cse, Swarnandhra College of
Engineering& Technology, Narsapuram,
A.P.His interested areas are data mining,
network security.
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