Tuesday, January 1, 2013

UGC NET COMPUTER SCIENCE AND APPLICATIONS PAPER-II KEY HELD AT DECEMBER 30 2012

SOME SAMPLE COMPUTE SCIENCE  AND APPLICATIONS QUESTIONS WITH KEY OF UGC NET EXAM HELD AT DECEMBER 30 2012

                         PAPER-II

(UGCNET EXAM PAPER KEY,UGCNET DECEMBER 30 KEY,UGCNET COMPUTER SCIENCE KEY 2012,UGC NET COMPUTER SCIENCE AND APPLICATION KEY,UGCNET PAPER-2 KEY,UGCNET DEC 30 KEY, UGCNET PAPER -II KEY,UGC NET KEY RELEASED,UGCNET DECEMBER 30,2012 KEY,FIRST KEY RELEASE OF UGCNET DECEMBER 30 2012,UGCENT KEY RELEASED,UGC NET PAPER1,PAPER 2,PAPER-3,UGCNET COMPUTERS PAPER -3 KEY)



7)THE C LANGUAGE IS -------       ANSWER: CONTEXT SENSITIVE GRAMMAR(B)

8)THE MOBILE APPLICATION PROTOCOL(MAP) TYPICALLY RUNS ON TOP OF WHICH PROTOCOL-------------------------------ANSWER: SS7(SIGNALLING SYSTEM 7)  (C)

11)IN COMPILER DESIGN "REDUCING THE STRENGTH" REFERS TO ------ANSWER:CODE OPTIMIZATION USING CHEAPER MACHINE INSTRUCTIONS(B)

13)WHICH OF THE FOLLOWING IS TRUE?---ANSWER:A RELATION IS  BCNF IS ALWAYS IN 3NF(A)

16)IN WHICH TREE FOR EVERY NODE THE HEIGHT OF ITS LEFT AND RIGHT SUBTREE DIFFER ALMOST BY 1--------------ANSWER: AVL TREE(B)

17)THE DESIGN ISSUE OF DATALINK LAYER IN OSI REFERENCE MODEL IS -----ANSWER: FRAMING(A)

20)THE PROBLEM OF INDEFINITE BLOCKAGE OF LOW-PRIORITY JOBS IN GENERAL PRIORITY SCHEDULING ALGORITHM CAN BE SOLVED USING ----- ANSWER AGING(B)

21)WHICH API IS USED TO DRAW A CIRCLE    ----- ANSWER: CIRCLE(A)(NOT SURE)

26)A HASH FUNCTION F DEFINED AS F(KEY)=KEY MOD 13,WITH LINEAR PROBING IS USED TO INSERT KEYS 55,55,68,91,27,145. WHAT WILL BE THE LOCATION OF 79?....................ANSWER 4(D)

30)WHICH OF THE FOLLOWING MEMORY ALLOCATION SUFFERS FROM EXTERNAL FRAGMENTATION?........................... ANSWER:  SEGMENTATION(A)


35)WHICH OF THE FOLLOWING IS THE MOST POWERFUL PARSING METHOD?
ANSWER: CANONICAL LR(B)

36)IN UNIX WHICH OF THE FOLLOWING IS COMMAND IS USED TO SET THE TASK PRIORITY?...................ANSWER NICE(B)

39)MATCH THE FOLLOWING WITH RESPECT TO C++ DATATYPES:

A.USER DEFINED TYPE     1  QUALIFIER
B BUILT IN TYPE                2 UNION
C DERIVED TYPE               3  VOID
D LONG DOUBLE               4 POINTER
......................................
ANSWER:     A-2,B-3,C-4,D-1    (1)

40)GIVEN AN EMPTY STACK,AFTER PERFORMING PUSH(1),PUSH(2),POP,PUSH(3),POP,POP,PUSH(5),POP, WHAT IS THE VALUE OF THE TOP OF STACK...................ANSWER: 1(D)

42)WHICH OF THE FOLLOWING MODE DECLARATION IS USED IN C++ TO OPEN FILE FOR INPUT?....................ANSWER:  IOS::IN(D)

43)DATA ENCRYPTION TECHNIQUES ARE PARTICULARLY ARE USED FOR ............ANSWER: PROTECTING DATA IN DATA COMMUNICATION SYSTEM(A)

49)IDENTIFY THE OPERATION WHICH IS COMMUTATIVE BUT NOT ASSOCIATIVE?...
ANSWER: NAND (D)




Monday, August 6, 2012

EPASS RENEWAL APPLICATION 2012-13




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Print the below income declaration on the
Non-Judicial Stamp Paper (Rs. 10/-)













INCOME DECLARATION FORM
Name of the Student
1.
(i) Name of the Father


4.
Business mention the trade/name of business


(ii) Whether Employed



Income derived from the venture


(iii) if employed, Designation


5.
(i) No. of Vehicles owned by the Family


(iv) Salary per month



(ii) Whether used for personal/private use only


2.
(i) Name of the Mother



(iii) Mention type of vehicles (two wheeler/ three wheeler/four wheeler)

Regd. No.
(ii) Whether Employed



(iv) Vehicle registered on whose name


(iii) if employed, Designation


6.
(i) Type of House: Mention whether RCC, thatched/Tiled roofed



(iv) Salary per month



(ii) Mention whether Indiramma House


3.
Agricultural holding of the parents mention extent



(iii) Cost of Construction of House


(i) In the name of the Father



(iv) Whether Constructed with loan, if so amount and Bank Branch


(ii) In the name of the Mother



(v)  Any other type of house


(a)
Crops Grown in land


7.
(i) Whether living in own house or rented house


(b)
Whether Dry or Wet land



(ii) if rented, mention rent amount


(c)
Annual Income from Agricultural Land


8
Telephone / Mobile Number






9.
Total Family income from all sources.


I hereby declare that the above information given is true & correct.  I will be held liable for any wrong information given which shall include cancellation of scholarship, recovery of amounts paid already if any besides criminal action.

Name & Signature of the Student                                                                            Name & Signature of the Parent
ePASS Application ID (2011-12):____________                                                  Address: H.No.:____________
Course: ­­­________    Course Year:_                                                                        Village & Mandal:___________            
College: ____________________________________          ___________          City & District: _____________
College District:______________                                                                          Mobile No:_________
Mobile No:__________ 

                     For more details visit official website at "http://epass.cgg.gov.in/"                                                                                                        

Sunday, July 1, 2012

EAMCET MOCK COUNSELLING 2012


eamcet 2012,meidical counselling,engieering mock counselling 2012,medical mock counselling 2012
eamet counselling 2012,which seat i cant get in eamcet counselling 2012,eacmet dates


http://www.schools9.com/e12mock.htm

Friday, June 29, 2012

APTET RESULTS 2012



AP TET RESULTS 2012,APTET RANK CARD,Andhra Pradesh Teacher Eligibility Test Results 2012,APTET 2012,APTET TOP RANKERS,APTET SCORES,APTET MARKS,Andhra Pradesh Teacher Eligibility Test RANK CARD,APTET QULALIFIED STUDENTS,




http://www.results.manabadi.co.in/APTET-Results-2012.htm

http://results.bharatstudent.com/aptet-results-2012-ap-teachers-eligibility-test-results-2012.php

http://aptet.cgg.gov.in/aptetResultsjan2012.aptet


eamcet key 2012,eamcet 2012 result,eamcet rank card,
eamcet results 2012,eamcet first rank,eamcet marks,eamcet rank,eamcet official website,,
eamcet 2012 results,eamcet top ten rankers,eamcet question paper and key,eamcet counselling 

http://results.bharatstudent.com/eamcet-results-2012.php

http://www.results.manabadi.co.in/EAMCETResults2012.htm

http://www.schools9.com/eamcet-12-results.htm



Wednesday, November 30, 2011

LIST OF IEEE DATAMINING PROJECTS(ABSTRACTS) IMPLEMENTED IN DOTNET

Web Technology and Architecture for Personal Health Records
Abstract:
Contemporary Web-based architectures can help us address the technological and architectural challenges inherent to modern personal health record (PHR) systems. Current research in the area of healthcare informatics has focused on incorporating Web-based technology for PHR systems’ primary functions. This special issue presents work in this area of research. First, however, let’s look at how PHR systems are defined, examine some of their benefits, and examine possible barriers to their widespread adoption.

Existing System:

ü The use of technology to let individuals share healthcare information makes PHRs an important aspect in how patients and providers manage care in the future.
ü Whereas only healthcare providers can keep and maintain electronic health records (EHRs), PHR record systems are controlled by the patient.
ü PHR platforms could radically move the locus of control over health information to the patient (consumer).
ü PHR systems are in contrast to the traditional clinician’s record of patient encounter-related information managed within a healthcare institution.

Proposed System:

ü Current research in the area of healthcare informatics has focused on incorporating Web-based technology for PHR systems’ primary functions.
ü An electronic application through which individuals can access, manage, and share their health information, and that of others for whom they are authorized, in a private, secure, and confidential environment.
ü PHRs let individuals monitor and share their healthcare information with healthcare providers as well as third-party health and wellness providers
ü PHR systems help develop closer interactions with patients to improve patient satisfaction
ü Two areas in which PHR systems have the greatest recognized potential are for patients with long-term conditions and for leveraging the mobile and remote submission of patient data to facilitate patient monitoring and decision support and efficiency in the provision of care.

KEYWORDS:
Generic Technology Keywords: Database, User Interface, Programming
Specific Technology Keywords: C#.Net, ASP.Net, MS SqlServer-08
Project Keywords: Presentation, Business Object, Data Access Layer
SDLC Keywords: Analysis, Design, Code, Testing, Implementation, Maintenance

SYSTEM CONFIGURATION
HARDWARE CONFIGURATION
S.NO
HARDWARE
CONFIGURATIONS
1
Operating System
Windows 2000 & XP
2
RAM
1GB
3
Processor (with Speed)
Intel  Pentium IV (3.0 GHz) and Upwards
4
Hard Disk Size
40 GB and above
5
Monitor
15’ CRT

SOFTWARE CONFIGURATION
S.NO
SOFTWARE
CONFIGURATIONS
1
Platform
Microsoft Visual Studio
2
Framework
.Net Framework 4.0
3
Language
C#.Net
4
Front End
Asp.Net
5
Back End
SQL Server 2008



Relevance-Based Retrieval on Hidden-Web
Text Databases without Ranking Support
Abstract:
Many online or local data sources provide powerful querying mechanisms but limited ranking capabilities. For instance, PubMed allows users to submit highly expressive Boolean keyword queries, but ranks the query results by date only. However, a user would typically prefer a ranking by relevance, measured by an information retrieval (IR) ranking function. A naive approach would be to submit a disjunctive query with all query keywords, retrieve all the returned matching documents, and then rerank them. Unfortunately, such an operation would be very expensive due to the large number of results returned by disjunctive queries. In this paper, we present algorithms that return the top results for a query, ranked according to an IR-style ranking function, while operating on top of a source with a Boolean query interface with no ranking capabilities (or a ranking capability of no interest to the end user). The algorithms generate a series of conjunctive queries that return only documents that are candidates for being highly ranked according to relevance metric. Our approach can also be applied to other settings where the ranking is monotonic on a set of factors (query keywords in IR) and the source query interface is a Boolean expression of these factors. Our comprehensive experimental evaluation on the Pub Med database and a TREC data set show that we achieve order of magnitude improvement compared to the current baseline approaches.

Existing System:
v Online or local data sources provide powerful querying mechanisms but limited ranking capabilities.
v For instance, PubMed allows users to submit highly expressive Boolean keyword queries, but ranks the query results by date only.
v a user would typically prefer a ranking by relevance, measured by an information retrieval (IR) ranking function.
v A naive approach would be to submit a disjunctive query with all query keywords, retrieve all the returned matching documents, and then rerank them.
v Unfortunately, such an operation would be very expensive due to the large number of results returned by disjunctive queries.


Proposed System:
v we present algorithms that return the top results for a query, ranked according to an IR-style ranking function, while operating on top of a source with a Boolean query interface with no ranking capabilities (or a ranking capability of no interest to the end user).
v We presented a framework and efficient algorithms to build a ranking wrapper on top of a documents data source that only serves Boolean keyword queries.
v Our algorithm submits a minimal sequence of conjunctive queries instead of a very expensive disjunctive one.
v Our comprehensive experimental evaluation on the PubMed database shows that we achieve order of magnitude improvement compared to the baseline approach.
v The algorithms generate a series of conjunctive queries that return only documents that are candidates for being highly ranked according to relevance metric.

KEYWORDS:
Generic Technology Keywords: Database, User Interface, Programming
Specific Technology Keywords: C#.Net, ASP.Net, MS SqlServer-08
Project Keywords: Presentation, Business Object, Data Access Layer, Database
SDLC Keywords: Analysis, Design, Code, Testing, Implementation, Maintenance

SYSTEM CONFIGURATION
HARDWARE CONFIGURATION
S.NO
HARDWARE
CONFIGURATIONS
1
Operating System
Windows 2000 & XP
2
RAM
1GB
3
Processor (with Speed)
Intel  Pentium IV (3.0 GHz) and Upwards
4
Hard Disk Size
40 GB and above
5
Monitor
15’ CRT
SOFTWARE CONFIGURATION
S.NO
SOFTWARE
CONFIGURATIONS
1
Platform
Microsoft Visual Studio
2
Framework
.Net Framework 4.0
3
Language
C#.Net
4
Front End
Asp.net, html
5
Back End
SQL Server 2008



Ranking Spatial Data by Quality Preferences

Abstract:
A spatial preference query ranks objects based on the qualities of features in their spatial neighborhood. For example, using a real estate agency database of flats for lease, a customer may want to rank the flats with respect to the appropriateness of their location, defined after aggregating the qualities of other features (e.g., restaurants, cafes, hospital, market, etc.) within their spatial neighborhood. Such a neighborhood concept can be specified by the user via different functions. It can be an explicit circular region within a given distance from the flat. Another intuitive definition is to assign higher weights to the features based on their proximity to the flat. In this paper, we formally define spatial preference queries and propose appropriate indexing techniques and search algorithms for them. Extensive evaluation of our methods on both real and synthetic data reveals that an optimized branch-and-bound solution is efficient and robust with respect to different parameters.

Existing System:

v In the existing system there is no solution for processing the top-k spatial preference query.
v In the existing system there are no alternative techniques for minimizing the I/O accesses to the object and feature data sets.
v In the existing system there are two basic ways for ranking objects,
v 1) Spatial ranking, which orders the objects according to their distance from a reference point.
v 2) Non spatial ranking, which orders the objects by an aggregate function on their non spatial values.


Proposed System:

v In this paper, we studied top-k spatial preference queries, which provide a novel type of ranking for spatial objects based on qualities of features in their neighborhood.
v The neighborhood of an object p is captured by the scoring function.
v 1) The range score restricts the neighborhood to a crisp region centered at p, whereas 2) the influence score relaxes the neighborhood to the whole space and assigns higher weights to locations closer to p.
v We presented five algorithms for processing top-k spatial preference queries.
v The baseline algorithm SP computes the scores of every object by querying on feature data sets. The algorithm GP is a variant of SP that reduces I/O cost by computing scores of objects in the same leaf node concurrently.
v The algorithm BB derives upper bound scores for non leaf entries in the object tree, and prunes those that cannot lead to better results.
v The algorithm BB* is a variant of BB that utilizes an optimized method for computing the scores of objects (and upper bound scores of non leaf entries).
v The algorithm FJ performs a multi way join on feature trees to obtain qualified combinations of feature points and then search for their relevant objects in the object tree.
v The challenge is to develop alternative methods for computing the upper bound scores for a group of points on a road network.


KEYWORDS:
Generic Technology Keywords: Database, User Interface, Programming
Specific Technology Keywords: C#.Net, ASP.Net, MS SqlServer-08
Project Keywords: Presentation, Business Object, Data Access Layer, Database
SDLC Keywords: Analysis, Design, Code, Testing, Implementation, Maintenance







SYSTEM CONFIGURATION
HARDWARE CONFIGURATION
S.NO
HARDWARE
CONFIGURATIONS
1
Operating System
Windows 2000 & XP
2
RAM
1GB
3
Processor (with Speed)
Intel  Pentium IV (3.0 GHz) and Upwards
4
Hard Disk Size
40 GB and above
5
Monitor
15’ CRT
SOFTWARE CONFIGURATION
S.NO
SOFTWARE
CONFIGURATIONS
1
Platform
Microsoft Visual Studio
2
Framework
.Net Framework 4.0
3
Language
C#.Net
4
Front End
Asp.Net
5
Back End
SQL Server 2008


On Computing Farthest Dominated Locations

Abstract:

In reality, spatial objects (e.g., hotels) not only have spatial locations but also have quality attributes (e.g., price, star). An object p is said to dominate another one p0, if p is no worse than p0 with respect to every quality attribute and p is better on at least one quality attribute. Traditional spatial queries (e.g., nearest neighbor, closest pair) ignore quality attributes, whereas conventional dominance-based queries (e.g., skyline) neglect spatial locations. Motivated by these observations, we propose a novel query by combining spatial and quality attributes together meaningfully. Given a set of (competitors’) spatial objects P, a set of (candidate) locations L, and a quality vector _ as design competence (for L), the farthest dominated location (FDL) query retrieves the location
s 2 L such that the distance to its nearest dominating object in P is maximized. FDL queries are suitable for various spatial decision support applications such as business planning, wild animal protection, and digital battle field systems. As FDL queries cannot be readily solved by existing techniques, we develop several efficient R-tree-based algorithms for processing FDL queries, which offer users a range of selections in terms of different indexes available on the data. We also generalize our methods to support the generic distance metric and other interesting query types. The experimental results on both real and synthetic data sets disclose the performance of those algorithms, and reveal the most efficient and scalable one among them.

Existing System:
o   In the existing system different constraints have been combined with conventional spatial queries to select semantically optimal locations or objects.
o   In the existing system we are not combining the both spatial locations and quality attributes to define a novel query.
o   In existing system they are not using the any algorithms to processing the FDL query.
o   In the existing system they are not design specific and efficient methods for FDL query.
o   In the existing system FDL queries are suitable for various spatial decision making applications, they cannot be readily solved by any of the existing techniques.

Proposed System:

o   In this paper, we propose a novel complex type of query: farthest dominated location query. Given a set of (competitors) spatial objects P with both spatial locations and non spatial attributes.
o   FDL queries are suitable for various spatial decision making applications.
o   We develop several efficient R-tree-based algorithms for processing FDL queries, which offer users a range of selections in terms of different indexes available on the data.
o   We also generalize our proposals to support the generic distance metric and other interesting query types.
o   We conduct an extensive experimental study with various settings on both real and synthetic data sets.
o   The results disclose the performance of our proposals, and reveal our spatial joint-based algorithm as the most efficient and scalable query processing algorithm.



KEYWORDS:
Generic Technology Keywords: Database, User Interface, Programming
Specific Technology Keywords: C#.Net, ASP.Net, MS SqlServer-08
Project Keywords: Presentation, Business Object, Data Access Layer
SDLC Keywords: Analysis, Design, Code, Testing, Implementation, Maintenance






SYSTEM CONFIGURATION
HARDWARE CONFIGURATION
S.NO
HARDWARE
CONFIGURATIONS
1
Operating System
Windows 2000 & XP
2
RAM
1GB
3
Processor (with Speed)
Intel  Pentium IV (3.0 GHz) and Upwards
4
Hard Disk Size
40 GB and above
5
Monitor
15’ CRT
SOFTWARE CONFIGURATION
S.NO
SOFTWARE
CONFIGURATIONS
1
Platform
Microsoft Visual Studio
2
Framework
.Net Framework 4.0
3
Language
C#.Net
4
Front End
Asp.Net
5
Back End
SQL Server 2008


 
MYOLAP: An Approach to Express and Evaluate
OLAP Preferences
Abstract:
Multidimensional databases are the core of business intelligence systems. Their users express complex OLAP queries, often returning large volumes of facts, sometimes providing little or no information. Thus, expressing preferences could be highly valuable in this domain. The OLAP domain is representative of an unexplored class of preference queries, characterized by three peculiarities: preferences can be expressed on both numerical and categorical domains; they can also be expressed on the aggregation level of facts; the space on which preferences are expressed includes both elemental and aggregated facts. In this paper we present MYOLAP, an approach for expressing and evaluating OLAP preferences, devised by taking into account the three peculiarities above. We first propose preference algebra where users are enabled to express their preferences, besides on attributes and measures, also on the aggregation level of facts, for Instance by stating that monthly data are preferred to yearly and daily data. Then, with respect to preference evaluation, we propose an algorithm called WEST that relies on a novel graph representation where two types of domination between sets of facts may be expressed, which considerably improves efficiency. The approach is extensively tested for efficiency and effectiveness on real data, and compared against two other approaches in the literature.

Existing System:

Ø In the existing system the problem of developing a theory of preferences for multidimensional databases has been mostly neglected.
Ø Preferences can be expressed not only on attributes, that have categorical domains, but also on measures, that have numerical domains.
Ø  This makes the existing approaches that are oriented to handling either categorical or numerical preferences, ineffective.
Ø  Preferences can also be formulated on the aggregation level of data, which comes down to expressing preferences on schema rather than on instances.
Ø  The space on which preferences are declared is dramatically larger than that of typical transactional databases due to the presence, besides elemental facts, also of aggregated facts.
Ø In real cases, materializing all aggregated facts is impossible for space reasons, which makes all sort-based approaches unfeasible.

Proposed System:
Ø In this paper we have argued that the OLAP domain introduces a new class of preference queries that cannot be satisfactorily managed by recurring to the existing approaches.
Ø We propose the WEST algorithm, a partitioning approach for evaluating MYOLAP preference queries based on the wBTG.
Ø We will work towards establishing a tighter integration between MYOLAP and the DBMS optimizer, which allows algebraic and semantic optimization techniques to be applied.
Ø We have defined an algebra that allows preferences to be formulated, besides attributes and measures, also on hierarchies, i.e., on the aggregation level of facts.
Ø We have proposed a partitioning approach for evaluating preference queries, based on a graph capable of expressing weak and strict domination relationships between sets of facts.
Ø Finally, we have shown that in presence of preferences on both categorical and numerical domains, where the existing techniques fall short, our approach is still capable of effectively processing the data cube by significantly pruning the search space.
Ø We will examine the possibility of dynamically determining the best way of collapsing S-classes into nodes of  the  wBTG according to the actual distribution of data

KEYWORDS:
Generic Technology Keywords: Database, User Interface, Programming
Specific Technology Keywords: C#.Net, Windows Forms, MS SqlServer-08
Project Keywords: Presentation, Business Object, Data Access Layer, Database
SDLC Keywords: Analysis, Design, Code, Testing, Implementation, Maintenance
SYSTEM CONFIGURATION
HARDWARE CONFIGURATION
S.NO
HARDWARE
CONFIGURATIONS
1
Operating System
Windows 2000 & XP
2
RAM
1GB
3
Processor (with Speed)
Intel  Pentium IV (3.0 GHz) and Upwards
4
Hard Disk Size
40 GB and above
5
Monitor
15’ CRT
SOFTWARE CONFIGURATION
S.NO
SOFTWARE
CONFIGURATIONS
1
Platform
Microsoft Visual Studio
2
Framework
.Net Framework 4.0
3
Language
C#.Net
4
Front End
Windows Forms
5
Back End
SQL Server 2008




Location-Related Privacy in Geo-Social Networks

Abstract:
Geo-social networks (GeoSNs) provide context-aware services that help Associate location with users and content. The proliferation of GeoSNs Indicates that they’re rapidly attracting users.GeoSNs currently offer different types of services, including photo sharing, friend tracking, and “check-ins.” However, this ability to reveal users’ locations causes new privacy threats, which in turn call for new privacy-protection methods. The authors study four privacy aspects central to these social networks — location, absence, co-location, and identity privacy — and describe possible means of protecting privacy in these circumstances.


Existing System:

Ø In the existing system online social networks increasingly enable users to publish geo-located content in real time.
Ø In the existing system geo-social networks (GeoSNs) are used combine the
Real time location reporting capabilities with traditional social network functionality.
Ø Location-aware capability in social networks enables new possibilities, such as “check-ins,” where users register their arrival at a location online.
Ø Existing techniques for traditional LBSs need to be reengineered to enable privacy in GeoSNs.

Proposed System:

Ø In the proposed system Geo-social networks (GeoSNs) provide context-aware services that help associate location with users and content.
Ø In proposed system GeoSNs currently offer different types of services, including photo sharing, friend tracking, and “check-ins”.
Ø In this system we discuss aspects of user privacy that are potentially at risk and examine possible solutions.



Ø A GeoSN locates a user via a location update, which takes two forms: With some services, users can update their locations only at certain, predefined places (check-ins). Other services can continuously or periodically rack users, typically via GPS or a service that exploits the communication infrastructure for positioning.

Ø GeoSNs can associate both content and users with locations and vice versa. Most GeoSNs are location-centric in the sense that they enable convenient content retrieval according to location.



KEYWORDS:
Generic Technology Keywords: Database, User Interface, Programming
Specific Technology Keywords: C#.Net, ASP.Net, MS SqlServer-08
Project Keywords: Presentation, Business Object, Data Access Layer, Database
SDLC Keywords: Analysis, Design, Code, Testing, Implementation, Maintenance








SYSTEM CONFIGURATION
HARDWARE CONFIGURATION
S.NO
HARDWARE
CONFIGURATIONS
1
Operating System
Windows 2000 & XP
2
RAM
1GB
3
Processor (with Speed)
Intel  Pentium IV (3.0 GHz) and Upwards
4
Hard Disk Size
40 GB and above
5
Monitor
15’ CRT
SOFTWARE CONFIGURATION
S.NO
SOFTWARE
CONFIGURATIONS
1
Platform
Microsoft Visual Studio
2
Framework
.Net Framework 4.0
3
Language
C#.Net
4
Front End
Asp.net, html
5
Back End
SQL Server 2008


 LIST OF IEEE PROJECTS!IEEE PROJECTS 2011,DATAMINING PROJECTS 2011,IEEE PROJECTS 2011,IEEE JOURNALS,DATAMINING PROJECTS IMPLEMENTED IN DATAMINING,IEEE 2011 DOTNET PROJECTS,IEEE 2011 DATAMINING PROJECTS IMPLEMENTED IN DOTNET,DATAMINING  JOURNALS,RANKING PROJECTS,OLAP PROJECTS,ASSOCIATION RULES PROJECTS,