Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Cold-start link prediction is a term for information starved link prediction where little or no topological information is present to guide the determination of whether links to a node will form. Due to the lack of topological information, traditional topology-based link prediction methods cannot be applied to solve the cold-start link prediction problem. Therefore, an effective approach is presented through establishing connections beten non-topological and topological information. In the approach, topological information is first extracted by a latent-feature representation model, then a logistic model is proposed to establish the connections beten topological and non-topological information, and finally the linking possibility beten cold-start users and existing users is calculated. Experiments with three types of real-world social networks ibo, Facebook, and Twitter show that the proposed approach is more effective in solving the cold-start link prediction problem and establishing connections beten topological and non-topological information.
['Zhiqiang Wang', 'Jiye Liang', 'Ru Li', 'Yuhua Qian']
I am writing a research paper on a idea An Approach to Cold-Start Link Prediction: Establishing Connections between Non-Topological and Topological Information
[{"from": "human", "value": "I am writing a research paper on a idea An Approach to Cold-Start Link Prediction: Establishing Connections between Non-Topological and Topological Information"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Cold-start link prediction is a term for information starved link prediction where little or no topological information is present to guide the determination of whether links to a node will form. Due to the lack of topological information, traditional topology-based link prediction methods cannot be applied to solve the cold-start link prediction problem. Therefore, an effective approach is presented through establishing connections beten non-topological and topological information. In the approach, topological information is first extracted by a latent-feature representation model, then a logistic model is proposed to establish the connections beten topological and non-topological information, and finally the linking possibility beten cold-start users and existing users is calculated. Experiments with three types of real-world social networks ibo, Facebook, and Twitter show that the proposed approach is more effective in solving the cold-start link prediction problem and establishing connections beten topological and non-topological information."}]