Collective intelligence

internet-based encyclopedia has disrupted the reference world and demonstrated the power of large-scale, highly diverse collaboration within a new organizational model. This model is strictly related to concept of collective intelligence, the shared intelligence that emerges from the collaboration, collective efforts, and competition of many individuals and appears in consensus decision-making. Threadless is a crowd-company that built its entire business model as a mix of contests and collaborative communities:

benefit through an analysis of Soylent, one of the latest innovations in crowd sourcing using John Rawls’ Theory of Justice, the Veil of Ignorance, I aim to demonstrate how can we all benefit from crowdsourcing and harness the true power of collective intelligence and mass collaboration just by maintaining a fine

Several ways have been proposed for combining basic recommender system techniques to create a new hybrid system. The earlier survey of hybrids approaches [40] identified seven different types such as weighted, switching, mixed, feature combination, feature augmentation, cascade and meta-level [114]. A weighted hybrid recommender is one in which the score of a recommended item is computed from the results of all of the available recommendation techniques present in the system [40]. The score of different

Amongst the common workplace theories, the theories of motivation and autonomy speak the most relevant to me in my experiences in the workplace concerning group behavior. By being able to maintain a consistent feeling of autonomy in my workplace duties, I have been able to feel empowered and grow to accomplish my responsibilities and learn to incorporate new innovations. Motivation is undeniably linked to the autonomy and group behavior. As I further analyze how these concepts are related, I will

1.7 CONCLUSION Most recommender systems work on single domains, i.e., they recommend items related to the same domain where users have expressed ratings. However, the integration of different domains into one recommender system could allow users to span over different types of items. For instance, in our research users that have watched movies could like to be recommended with on-demand movies and related books. This report focuses on cross-domain collaborative recommender systems, whose aim is

made. Basically there are six different types of recommendation techniques: [3] Content-based: In this method, the system learns to recommend items that are similar to the ones that the user liked in the past. The similarity of items is calculated based on the features associated with the compared items. For example, if a user has highly rated a movie that belongs to the comedy genre, then the system can learn to recommend other movies from this genre. Some of the advantages of content-based systems

The most important desire while experiencing a health problem is finding a hospital or a doctor who would most appropriate for providing a solution to our health condition. Choosing a doctor is a typical problem related to information asymmetry as the information available is inefficient to take a proper decision. E-health is changing the scenario of clinical practice and medical care. Sharing knowledge and information can encourage individuals and makes the care/patient team relation with a patient

There is another class that is a combination of two or all of approaches, called hybrid approach. This kind of recommender systems arises with the aim of solving drawbacks that the other systems present in some situations [120] and to improve performance lead to advanced recommender systems [14]. In order to do that, these systems combine different techniques of the previous recommender systems [120] to achieve some synergy between them [121]. For example, a collaborative system and a knowledge-based

Crowd sourcing is being used in a wide variety of ways on the Internet, and it continues to evolve. Companies use crowd sourcing to develop new ideas and designs. Police have been known to use crowd sourcing to solve crimes, such as after the Boston Marathon bombing. Even governments have enlisted crowd sourcing to come up with ideas and to help determine what should be cut in their budgets. Now that governments have the Internet to reach the public and gather ideas from them can it be done properly

is Modcloth."- We are put in the designer/ buyers shoes, almost literally. "Pick It" or "Skip It", as they say. It helps the consumer to be able to engage in their own creativity. What about the opinion of an expert though being overlooked by a collective group? This clever plan has spread like wildfire, but can we trust the wisdom of crowds? I plan to show the pro's and con's of crowdsourcing. The risk for small businesses, the pitfalls and uprising's of this online phenomenon. Keywords: Crowdsourcing