the results for digitizing written text. 34 Finally, it can be argued that the target problem of many systems (that provide user services) is simply to grow a large community of users, for various reasons (such as personal satisfaction, charging subscription fees, selling ads, selling the systems to other companies). Buy/ sell/auction websites (such as eBay) and massive multiplayer games (such as World of Warcraft) for instance fit this description. Here, by simply joining the system, users can be viewed as implicitly collaborating to solve the target problem (of growing user communities).

The second kind of implicit system we consider is 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. For example, over time many piggyback CS systems have been built on top of major search engines, such as Google, Yahoo!, and Microsoft. These systems exploit the traces of search engine users (such as search logs, user clicks) for a wide range of tasks (such as spelling correction, finding synonyms, flu epidemic prediction, and keyword generation for ads6). Other examples include exploiting user purchases to recommend products, 26 and exploiting click logs to improve the presentation of a Web site. 19

 

Cs systems on the Web We now build on basic system types to discuss deployed CS systems on the Web. Founded on static HTML pages, the Web soon offered many interactive services. Some services serve machines (such as DNS servers, Google Map API server), but most serve humans. Many such services do not need to recruit users (in the sense that the more the better). Examples include pay-parking-ticket services (for city residents) and room-reservation services. (As noted, we call these crowd management systems). Many services, however, face CS challenges, including the need to grow large user bases. For example, online stores such as Amazon want a growing user base for their services, to maximize profits, and startups such as epinions.com grow their user bases for advertising. They started out as primitive CS systems, but quickly improved over time with additional CS features (such as reviewing, rating,

the user interface
should make it
easy for users to
contribute. this is
highly non-trivial.

networking). Then around 2003, aided by the proliferation of social software (for example, discussion groups, wiki, blog), many full-fledged CS systems (such as Wikipedia, Flickr, YouTube, Facebook, MySpace) appeared, marking the arrival of Web 2.0. This Web is growing rapidly, with many new CS systems being developed and non-CS systems adding CS features.

These CS systems often combine multiple basic CS features. For example, Wikipedia primarily builds a textual KB. But it also builds a structured KB (via infoboxes) and hosts many knowledge sharing forums (for example, discussion groups). YouTube lets users both share and evaluate videos. Community portals often combine all CS features discussed so far. Finally, we note that the Semantic Web, an ambitious attempt to add structure to the Web, can be viewed as a CS attempt to share structured data, and to integrate such data to build a Web-scale structured KB. The World-Wide Web itself is perhaps the largest CS system of all, encompassing everything we have discussed.

 

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. First, we can require users to make contributions if we have the authority to do so (for example, a manager may require 100 employees to help build a company-wide system). Second, we can pay users. Mechanical Turk for example provides a way to pay users on the Web to help with a task. Third, we can ask for volunteers. This solution is free and easy to execute, and hence is most popular. Most current CS systems on the Web (such as Wikipedia, You Tube) use this solution. The downside of volunteering is that it is hard to predict how many users we can recruit for a particular application.

The fourth solution is 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. Consider for example a blog website (that is, system A), where a user U can leave a comment only after solving a puzzle (called a captcha) to prove that U is a human. As a part of the puzzle, we