This document discusses a proposed system for improving the process of clustering and displaying search results from literature on cloud computing. The existing system has problems with only displaying results from registered candidates, poor data display, and lack of security. The proposed system aims to display the highest ranking search keywords based on user and publisher rankings to make the process more secure. It uses clustering to automatically organize documents by topic to improve information retrieval. The system would have administrative, publisher, search, and user modules and use ASP.Net and SQL Server software.
IEEE 2014 DOTNET CLOUD COMPUTING PROJECTS A scientometric analysis of cloud computing literature
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A Scientometric Analysis of cloud computing
literature
Abstract
The popularity and rapid development of cloud computing in recent
years has led to a huge amount of publications containing the achieved
knowledge of this area of research. Due to the interdisciplinary nature and
high relevance of cloud computing research, it becomes increasingly
difficult or even impossible to understand the overall structure and
development of this field without analytical approaches. While evaluating
science has a long tradition in many fields, we identify a lack of a
comprehensive scientometric study in the area of cloud computing. Based on
a large bibliographic data base, this study applies scientometric means to
empirically study the evolution and state of cloud computing research with a
view from above the clouds. By this, we provide extensive insights into
2. publication patterns, research impact and research productivity.
Furthermore, we explore the interplay of related subtopics by analyzing
keyword clusters. The results of this study provide a better understanding of
patterns, trends and other important factors as a basis for directing research
activities, sharing knowledge and collaborating in the area of cloud
computing research.
SYSTEM ANALYSIS
EXISTING SYSTEM:
Clustering is widely employed for automatically structuring large
document collections and enabling cluster-based information browsing,
which alleviates the problem of information overflow. In previous work
process search words are does not clearly displayed. And all related
information to view user searching process.
Problems on existing system
1. Any process operates only resisted candidates.
2. Not be excellent data display.
3. No secure process.
Proposed System
3. It enables a peer to compare each of its documents only with very few
selected clusters, without significant loss of clustering quality. The
algorithm offers probabilistic guarantees for the correctness of each
document assignment to a cluster. In this process search keywords to display
highest ranking based in registered user. To get output in user and publisher
ranking basic to be secure and view your search data also rank with us. Both
cluster indexing and document assignments are repeated periodically to
compensate churn, and to maintain an up-to-date clustering solution.
Examples of document clustering include web document clustering for
search users. Websites where the main purpose is to vote content and images
are called rating sites. Ratings are implemented in separate users and
publishers.
Main Modules:
Admin module
Publisher module
clustering
Search module
User module
1. Admin Module:
4. In this module, Admin should login with his specified AdminName
and with his specified password. And accept the publisher uploads data.
Admin can check the publisher’s and user’s browsing history. And admin
give access to register user and publisher.
2. Publisher Module :
In this module, is used to enter the publisher in our own registered
website and also edit our password details. The module publisher is used to
upload any famous details and images and view admin can check and verify
all details and images to accept our uploaded files. It is allowed to accept
and then view in all users and publishers. Because secure process in
searching.
3. Clustering :
Clustering is automatic document organization, topic extraction
and fast information retrieval or filtering. It is closely related to data
clustering. Document clustering is generally considered to be a centralized
process. Examples of document clustering include web document clustering
for search users. Websites where the main purpose is to vote content and
images are called rating sites.
4. Search Module :
To create and upload the famous information details in any
interest publisher process. And the updating detail to view any publisher and
user enter into Search key and all very highest voting data initially displayed
5. in links.And click any order of the links connect to view uploaded datas and
accepted images. Our required data and images are download in any
registered users and publishers. Mainly may like this contents and images
also voting our search view sites.
5. User Module
User can get the relavent literature survey data and user can give the
ratings for that user can download the literatures data and images.
System Specification
Hardware Requirements
• System : Pentium IV 2.4 GHz.
• Hard Disk : 40 GB.
• Floppy Drive : 1.44 Mb.
• Monitor : 14’ Colour Monitor.
• Mouse : Optical Mouse.
• Ram : 512 Mb.
• Keyboard : 101 Keyboard.
Software Requirements
• Operating system : Windows 7 32 bit ultimate
6. • Coding Language : ASP.Net with C,VS2010
• Data Base : SQL Server 2008.
Conclusion
Cloud computing attracts a lot of interdisciplinary attention and is a
rapidly developing field of research In this paper, we conduct a
scientometric analysis to comprehensively investigate the development and
current state of cloud computing related publications based on a large
bibliographic data basis provided by Scopus. The results of this study reveal
that past and current research is dominated by computer science research
conveyed especially through conference proceedings. The focus of research
activities is predominantly influenced by fundamental and highly recognized
scientists and publications. In this regard, we demonstrate the Matthew
effect in the area of cloud computing. Given the results of the keyword
analysis it is obvious that the past and current focus of cloud computing
research lies mainly on the technology itself rather than on socioeconomic
issues. Current trends, such as depicted by keywords related to data analysis
and Big Data, demonstrate the increasing importance of shifting the focus of
research to socioeconomic issues to solve understudied problems and better
utilize the potentials of cloud computing. This may help to increase the
overall value of cloud computing and may facilitate further adoption in both
an academic and practical context. Thus, the results of the scientometric
analysis may help the relatively new field of cloud computing to (re-) define
itself in order to provide a clear direction and objectives for research.