Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Graph is a useful data structure to model various real life aspects like email communications, co-authorship among researchers, interactions among chemical compounds, and so on. Supporting such real life interactions produce a knowledge rich massive repository of data. Hover, efficiently understanding underlying trends and patterns is hard due to large size of the graph. Therefore, this paper presents a scalable compression solution to compute summary of a ighted graph. All the aforementioned interactions from various domains are represented as edge ights in a graph. Therefore, creating a summary graph while considering this vital aspect is necessary to learn insights of different communication patterns. By experimenting the proposed method on two real world and publically available datasets against a state of the art technique,  obtain order of magnitude performance gain and better summarization accuracy.
['Kifayat Ullah Khan', 'Waqas Nawaz', 'Young-Koo Lee']
I am writing a research paper on a idea Scalable Compression of a Weighted Graph.
[{"from": "human", "value": "I am writing a research paper on a idea Scalable Compression of a Weighted Graph."}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Graph is a useful data structure to model various real life aspects like email communications, co-authorship among researchers, interactions among chemical compounds, and so on. Supporting such real life interactions produce a knowledge rich massive repository of data. Hover, efficiently understanding underlying trends and patterns is hard due to large size of the graph. Therefore, this paper presents a scalable compression solution to compute summary of a ighted graph. All the aforementioned interactions from various domains are represented as edge ights in a graph. Therefore, creating a summary graph while considering this vital aspect is necessary to learn insights of different communication patterns. By experimenting the proposed method on two real world and publically available datasets against a state of the art technique,  obtain order of magnitude performance gain and better summarization accuracy."}]