crowdsourcing systems on world wide web

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CROWDSOURCING SYSTEMS ON WORLD-WIDE WEB By:- SACHIDANAND KUMAR, SEM-7, ROLL NO-12090067, COMPUTER SCIENCE & ENGINEERING, SOE, CUSAT

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Presented by Sachin sharma.Crowdsourcing systems enlist a multitude of humans to help solve a wide variety of problems. Over the past decade, numerous such systems have appeared on the World-Wide Web. Prime examples include Wikipedia, Linux, Yahoo! Answers, Mechanical Turk-based systems, and much effort is being directed toward developing many more.

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Page 1: Crowdsourcing Systems on world wide web

CROWDSOURCING SYSTEMS ON WORLD-WIDE WEB

By:- SACHIDANAND KUMAR,

SEM-7, ROLL NO-12090067,

COMPUTER SCIENCE & ENGINEERING,

SOE, CUSAT

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INDEX:

1. Introduction

2. Definition

3. Classifying Crowdsourcing Systems

4. Standalone Vs Piggyback

5. Sample Crowdsourcing Systems on web

6. Challenges and Solutions

7. Conclusion

8. References

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1. 1. INTRODUCTION:-

Crowdsourcing systems enlist a multiple of humans to solve a wide verity of problems. Over the past decade, numerous such systems have appeared on the World-Wide Web. Prime examples include Wikipedia, Linux, Yahoo!

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2.Definition:-

Crowdsourcing is an online, distributed problem solving and production model.

It has been defined as “the online distribution of certain tasks to crowds of experts and enthusiasts.”

Crowdsourcing, a hybrid of “crowd” and “outsourcing.”

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Crowdsourcing= Crowd+ Outsourcing

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Definition…Contd..

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3. Classifying Crowdsourcing systems:-

CS systems can be classified along nine most important dimensions. The two that immediately come to mind are the 

(1) nature of collaboration and 

(2) type of target problem.

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Classification contd..

The next four dimensions refer how a CS system solves fundamental challenges: 

(3) how to recruit and retain users;

(4) what can users do;

(5) how to combine their inputs; and

(6) how to evaluate them. 

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Classification Contd..

The remaining three dimensions:

-> degree of manual effort,

-> role of human users, and

-> standalone versus piggyback architectures.

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3.1 Degree of manual effort:

 When building a CS system, we must decide how much manual effort is required to solve each of the CS challenges.

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3.2 Role of human users:

 We consider four basic roles of humans in a CS system:-

-> Slaves: humans help solve the problem in a divide-and-conquer fashion, to minimize the resources of the owners. 

-> Perspective providers: humans contribute different perspectives, which when combined often produce a better solution.

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Role of human users….contd..

-> Content providers: humans contribute self-generated content (for example, videos on YouTube, images on Flickr).

-> Component providers: humans function as components in the target artifact, such as a social network, or just a community of users.

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Examples for content providers:-

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4. Standalone versus piggyback:Piggyback is decided on a well-established system, by exploiting traces that users leave in that system to solve our target problem.

For example, Google's "Did you mean" and Yahoo's Search Assist utilize the search log and user clicks of a search engine to correct spelling mistakes.

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Standalone versus piggyback:…Contd.

Unlike standalone systems, such piggyback systems do not have to solve the challenges of recruiting users and deciding what they can do.

But they still have to decide how to evaluate users and their inputs, and to combine such inputs to solve the target problem.

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5. Sample Crowdsourcing Systems on the Web:

Building on this discussion of CS dimensions, first of all to be described a set of basic system types, and then showing how deployed CS systems often combine multiple such types.

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Sample CS Systems on the Web: contd..Explicit Systems:  Let users

collaborate explicitly. In particular, users can evaluate, share, network, build artifacts, and execute tasks.

Evaluating: Let users evaluate "items" using textual comments, numeric scores, or tags.

Set, starting with explicit systems:-

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Sample CS Systems on the Web: contd..

Sharing: Let users share "items" such as products, services, textual knowledge and structured knowledge. Ex:-Napster, YouTube, CPAN etc.

Networking: Let users collaboratively construct a large social network graph, by adding nodes and edges over time (such as homepages, friendships).

They exploit the graph to provide services.

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Sample CS Systems on the Web: contd..

Building Artifacts: Let users build artifacts such as Wikipedia often merge user inputs tightly, and require users to edit and merge one another's inputs.

Executing Tasks:  The last type is the kind that executes tasks. Examples : finding extraterrestrials, searching for missing people and cooperative debugging.

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Blogger as an crowdsourcing system in www

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Design parts of the blog where users can modify it a/c to their needs

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To check the status of visitors for that particular site:-

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Sample CS Systems on the Web: contd..

Implicit Systems:  

Let users collaborate implicitly to solve a problem of the system owners. They fall into two groups: ‘standalone’ and ‘piggyback’.

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Implicit Systems: Contd..

-> A standalone system provides a service such that when using it users implicitly collaborate to solve a problem.

-> A piggyback system that exploits the user traces of yet another system (thus, making the users of this latter system implicitly collaborate) to solve a problem.

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6. Challenges and Solutions:-

Here, we discuss the key challenges of CS systems:

How to recruit and retain users? Recruiting users is one of the most important CS challenges, for which five major solutions exist.

1.To ‘require users’ to make contributions if we have the authority to do so.

2. To ‘pay users’. Mechanical Turk for example provides a way to pay users on the Web to help with a task.

3. To ask for volunteers. This solution is free and easy to execute, so its most popular.

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How to recruit and retain users?.... Contd..

4. To ‘make users pay for service’. The basic idea is to require the users of a system A to "pay" for using A, by contributing to a CS system B.

5. To ‘piggyback on the user traces’ of a well-established system. This gives us a steady stream of users.

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How to recruit and retain users?.... Contd..

After selection of a recruitment strategy, many ‘encouragement and retention (E&R) schemes’ exist. The most popular ones:

1. To provide ‘instant gratification’, by immediately showing a users how their contribution makes a difference.

2. To provide an ‘enjoyable experience or a necessary service’, such as game playing.

3. To provide ways to establish, measure, and show ‘fame/trust/reputation’.

4. To set up competitions, such as showing top rated users.

5. To provide ‘ownership situations,’ where a user may feel he or she "owns" a part of the system.

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 Challenges and Solutions.. Contd..What contributions can users make?

In many CS systems the kinds of contributions users can make are somewhat limited. For example, to evaluate, users review, rate etc.

The four important factors:-

1. how ‘cognitively demanding’ are the contributions? To take care to design cognitively appropriate contribution types for different user groups.

2. what should be the impact of a contribution? To measure the potential impact by considering how the contribution potentially affects the CS system.

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What contributions can users make? ..Contd..

3. what about ‘machine contributions’? If a CS system employs an algorithm for a task, then users should make contributions that are easy for humans, but ‘difficult for machines’.

4. User interface should make it easy for users to contribute. This is highly non-trivial. A natural language format is easy for users, but difficult for machines to understand and use.

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7. Conclusion:-

We have discussed CS systems on the World-Wide Web. Our discussion shows that crowdsourcing can be applied to a wide variety of problems, and that it raises numerous interesting technical and social challenges.

Given the success of current CS systems, we expect that this emerging field will grow rapidly. In the near future, we foresee three major directions: more generic platforms, more applications and structure, and more users and complex contributions.

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8.References:-

1. Adamic, L.A., Zhang, J., Bakshy, E. and Ackerman, M.S. Knowledge sharing and Yahoo answers: Everyone knows something. In Proceedings of WWW, 2008.

2. The Cimple/DBLife project; http://pages.cs.wisc.edu/~anhai/projects/cimple 

3. Time. Special Issue Person of the year: You, 2006; http://www.time.com/time/magazine/article/0,9171,1569514,00.html 

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Thank you

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Queries???Queries???