Home| Join Now | Sign In | Trainers Login              
SPIRO, Spiro, project for student, student projects

A UNIT OF SPIRO GROUP OF COMPANIES

A RESEARCH & DEVELOPMENT ORGANIZATION

For Project Enquiry +91 9791 044 044

To Search
Last Live Projects with video description
VLSI Projects, Student Projects, Best Projects, College Projects Matlab Projects, vlsi projects Final Year Projects in Chennai , Final Year Training Projects in Chennai
Slideshow Image 1
CONTEXTUAL ONLINE LEARNING FOR MULTIMEDIA
Post Your concept Get Project
Guidance
It is purposely dedicated for innovative students. Here we encourage students who have new concepts and projects in various domains.

For Project Title


Project Zone > Software > Multimedia

Social share: Facebook SPIRO Google Plus

CONTEXTUAL ONLINE LEARNING FOR MULTIMEDIA

Category : Multimedia


Sub Category : DOTNET


Project Code : ITDMM03


Project Abstract

CONTEXTUAL ONLINE LEARNING FOR MULTIMEDIA

CONTENT AGGREGATION

ABSTRACT

            In this paper we study about last decade has witnessed a tremendous growth in the volume as well as the diversity of multimedia content generated by a multitude of sources. Faced with a variety of content choices, consumers are Exhibiting diverse preferences for content; their preferences often depend on the context in which they consume content as well as various exogenous events. To satisfy the consumer demand for such diverse content, multimedia content aggregators (CAs) have emerged which gather content from numerous multimedia sources. A key challenge for such systems is to accurately predict what type of content each of its consumers prefers in a certain context, and adapt these predictions to the evolving consumer preferences, contexts, and content characteristics. We propose a novel, distributed, online multimedia content aggregation framework, which gathers content generated by multiple heterogeneous producers to fulfill its consumer demand for content. Since both the multimedia content characteristics and the consumer preferences and contexts are unknown, the optimal content aggregation strategy is unknown a priori. Our proposed content aggregation algorithm is able to learn online what content to gather and how to match content and users by exploiting similarities between consumer types. We prove bounds for our proposed learning algorithms that guarantee both the accuracy of the predictions as well as the learning speed. Importantly, our algorithms operate efficiently even when feedback from consumers is missing or content and preferences evolve over time.



EXISTING SYSTEM

PROPOSED SYSTEM

EXISTING CONCEPT:-

In the existing system the server cluster handles only a specific type of multimedia task, and each client requests a different type of multimedia service at a different time. Such a scenario can be modeled as an integer linear programming problem.

 

PROPOSED CONCEPT:-

In the proposed system a cloud computing based Framework for big data information management in smart grids, which provides not only flexibility and scalability but also security features.

 

EXISTING ALGORITHM:-

centralized algorithm

PROPOSED ALGORITHM:-

Aggregation algorithm and Learning algorithms

ALGORITHM DEFNITION:-

Centralized algorithms in the distributed implementation of these centralized algorithms, we assume that each CA runs an independent instance of these algorithms. For instance, when implementing a centralized algorithm on the distributed system of CAs.

 

ALGORITHM DEFNITION:-

Aggregation algorithm is able to learn online what content to gather and how to match content and users by exploiting similarities between consumer types. We prove bounds for our proposed learning algorithms that guarantee both the accuracy of the predictions as well as the learning speed.

 

DRAWBACKS:-

Centralized method is suitable for only small collection of system.

Server cluster can handle only one type request at a time so that problem occurs.

ADVANTAGES:-

The Aggregation is scalable framework is suitable for larger collection of systems.

Client’s requests assigned to each server.

Cluster so that the load of each server cluster is distributed as balanced.

 
 
MILE STONES
GUARANTEES
CONTACT US
 
Training and Developemet, Engg Projects
So far we have provided R&D training for more than 1,00,000 engineering Students.
Latest Projects 2012, Latest Technologiy Project
Had conducted seminars in the recent trends of technology at various colleges.
Our research projects had been presented in various National & International Conferences.
Most of our projects were identified by the industries as suitable for their needs.
Our n-number of students got research scholarship to extend our assisted projects for further development.
   
   
Training and Developemt, Project Development in Chennai
SPIRO guarantees small class sizes.
Final Year Projects
SPIRO guarantees quality instructors.
Student Projects, Stupros
SPIRO guarantees competence.
Projects, student projects
SPIRO guarantees that training from SPIRO will be more cost-effective than training from any other source.
Final Year Projects, Projects, student projects
SPIRO guarantees that students in open-enrollment classes are protected against cancellations and will be able to receive desired training at the cost they expect and in the time frame they have planned.
Projects for student
SPIRO guarantees overall quality with a 100% money-back guarantee. If you're not totally satisfied for any reason, simply withdraw before the second day of any class. Notify the instructor and return all course materials and you will receive a 100% refund.
SPIRO SOLUTIONS PRIVATE LIMITED
For ECE,EEE,E&I, E&C & Mechanical,Civil, Bio-Medical
#1, C.V.R Complex, Singaravelu St, T.Nagar, Chennai - 17,
(Behind BIG BAZAAR)Tamilnadu,India
Mobile : +91-9962 067 067, +91-9176 499 499
Landline : 044-4264 1213
Email: info@spiroprojects.com

For IT, CSE, MSC, MCA, BSC(CS)B.COM(cs)
#78, 3rd Floor, Usman Road, T.Nagar, Chennai-17.
(Upstair Hotel Saravana Bhavan) Tamilnadu,India
Mobile: +91-9791 044 044, +91-9176 644 044
E-Mail: info1@spiroprojects.com
About Us | Project Training | Privacy policy | Disclaimer | Contact Us

Copyright © 2015-2016 Stupros All rights reserved.