The main, if not the only, income for social networks is from advertising. Social media platforms like Twitter have become a main stream communication medium to disseminate information and capture the interest of potential customers. So, it is crucial that the policy implemented to decide which ads to show in proximity of which user's posts, is the most profitable one: the ads shown should be as much as possible targeted to the user's interests. In this paper, we propose a context-aware advertising recommendation system that, analyzing the users' tweets during the timeline, interpretes the personal interests of users through orthopairs (they are equivalent to rough sets) to meet ads and users' interests at the right time.

Context-aware advertisment recommendation on twitter through rough sets

Gerla, Brunella;
2018

Abstract

The main, if not the only, income for social networks is from advertising. Social media platforms like Twitter have become a main stream communication medium to disseminate information and capture the interest of potential customers. So, it is crucial that the policy implemented to decide which ads to show in proximity of which user's posts, is the most profitable one: the ads shown should be as much as possible targeted to the user's interests. In this paper, we propose a context-aware advertising recommendation system that, analyzing the users' tweets during the timeline, interpretes the personal interests of users through orthopairs (they are equivalent to rough sets) to meet ads and users' interests at the right time.
IEEE International Conference on Fuzzy Systems
2018 IEEE International Conference on Fuzzy Systems, FUZZ 2018
Rio de Janeiro, Brazil
8 July 2018 through 13 July 2018
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11383/2077744
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