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News Agency System...

The MagentA News Agency System is intended for the sector of the knowledge management market concerned with the personalisation and distribution of information (news). In e-commerce applications it is used for the delivery of news items to website visitors, eg, buyers of products, customers of new services, investors or business partners. Within the MagentA i-Enterprise System, the system is also used for the co-ordination of teamwork.

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The system supporting the delivery of news to website visitors works as follows. An agent is assigned to every item of news (or every element of information). Agents compete with each other for the attention of the visitor's agent and the winner is selected through a negotiation guided by the visitor preferences.

Visitors to a website, typically, limit the amount of news items that they want to see on their screens. There is, consequently, a competition among news items for display space. To win, agents of those news items, known to be preferred by the current visitor, will have to offer to other news items a compensation for permission to reach the screen.

Winning news items are displayed and rated by the user and its (and its author's) fee depends on this rating. News-item agents that loose in this competition will have to decide whether they want to have another attempt with the same visitor or try to reach others. Agents may employ different strategies, eg, they can try to reach all potential users or choose the most promising one.

As a result of making wrong decisions, news-item agents will loose money through the payment of compensations to other news-item agents - and consequently will weaken their chances of reaching users and earning more money. This will lead to their gradual 'death' in the system. The more successful competitors, on the contrary, will gain more returns on their 'investments' and this will allow them greater scope in competing for the attention of future website visitors.

News negotiations News description
News negotiations News description

News review and user preferences

News review and user preferences

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