Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  focus on the problem of selecting reviers (or raters) that are considered by a recommender system (or a user) under the aspect of security. Malicious reviers can exert unreasonable influence, and can bias online consumers unfairly against an attacked item or competitor.  proposes an approach where a meta-recommender maximizes the aggregated diversity of reviers when deciding which reviews should be considered by a recommender system or an online consumer. This problem can be of interest in many domains where producers or service providers may seek advantages by compromising competitors with fake reviews or ratings such as tourism and hospitality industries or even free open-source software. A solution is proposed for users linked in social networks, such as unstructured P2P societies. In order to evaluate the proposed solution,  describe a mechanism of selecting reviers of software updates such that not all end-users of a software are impacted by a potentially malicious strict subset of all available reviers, and  experimentally assess resistance to attacks.
['Khalid Alhamed', 'Markus Zanker', 'Shakre Elmane', 'Marius C. Silaghi']
I am writing a research paper on a idea P2P Meta-Recommenders: Aggregated Diversity Maximization as a Bulwark against Attacks on Reviewers
[{"from": "human", "value": "I am writing a research paper on a idea P2P Meta-Recommenders: Aggregated Diversity Maximization as a Bulwark against Attacks on Reviewers"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  focus on the problem of selecting reviers (or raters) that are considered by a recommender system (or a user) under the aspect of security. Malicious reviers can exert unreasonable influence, and can bias online consumers unfairly against an attacked item or competitor.  proposes an approach where a meta-recommender maximizes the aggregated diversity of reviers when deciding which reviews should be considered by a recommender system or an online consumer. This problem can be of interest in many domains where producers or service providers may seek advantages by compromising competitors with fake reviews or ratings such as tourism and hospitality industries or even free open-source software. A solution is proposed for users linked in social networks, such as unstructured P2P societies. In order to evaluate the proposed solution,  describe a mechanism of selecting reviers of software updates such that not all end-users of a software are impacted by a potentially malicious strict subset of all available reviers, and  experimentally assess resistance to attacks."}]