Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Social media advertising is a multi-billion dollar market and has become the major revenue source for Facebook and Twitter. To deliver ads to potentially interested users, these social network platforms learn a prediction model for each user based on their personal interests. Hover, as user interests often evolve slowly, the user may end up receiving repetitive ads. ,  propose a context-aware advertising framework that takes into account the relatively static personal interests as ll as the dynamic news feed from friends to drive growth in the ad click-through rate. To meet the real-time requirement,  first propose an online retrieval strategy that finds k most relevant ads matching the dynamic context when a read operation is triggered. To avoid frequent retrieval when the context varies little,  propose a safe region method to quickly determine whether the top-k ads of a user are changed. Finally,  propose a hybrid model to combine the merits of both methods by analyzing the dynamism of news feed to determine an appropriate retrieval strategy. Extensive experiments conducted on multiple real social networks and ad datasets verified the efficiency and robustness of our hybrid model.
['Yuchen Li', 'Dongxiang Zhang', 'Ziquan Lan', 'Kian-Lee Tan']
I am writing a research paper on a idea Context-aware advertisement recommendation for high-speed social news feeding
[{"from": "human", "value": "I am writing a research paper on a idea Context-aware advertisement recommendation for high-speed social news feeding"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Social media advertising is a multi-billion dollar market and has become the major revenue source for Facebook and Twitter. To deliver ads to potentially interested users, these social network platforms learn a prediction model for each user based on their personal interests. Hover, as user interests often evolve slowly, the user may end up receiving repetitive ads. ,  propose a context-aware advertising framework that takes into account the relatively static personal interests as ll as the dynamic news feed from friends to drive growth in the ad click-through rate. To meet the real-time requirement,  first propose an online retrieval strategy that finds k most relevant ads matching the dynamic context when a read operation is triggered. To avoid frequent retrieval when the context varies little,  propose a safe region method to quickly determine whether the top-k ads of a user are changed. Finally,  propose a hybrid model to combine the merits of both methods by analyzing the dynamism of news feed to determine an appropriate retrieval strategy. Extensive experiments conducted on multiple real social networks and ad datasets verified the efficiency and robustness of our hybrid model."}]