Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: A Natural Language Generation (NLG) system is able to generate text from nonlinguistic data, ideally personalising the content to a user’s specific needs. In some cases, hover, there are multiple stakeholders with their own individual goals, needs and preferences. ,  explore the feasibility of combining the preferences of two different user groups, lecturers and students, when generating summaries in the context of student feedback generation. The preferences of each user group are modelled as a multivariate optimisation function, therefore the task of generation is seen as a multi-objective (MO) optimisation task, where the two functions are combined into one. This initial study shows that treating the preferences of each user group equally smooths the ights of the MO function, in a way that preferred content of the user groups is not presented in the generated summary.
['Dimitra Gkatzia', 'Helen F. Hastie', 'Oliver Lemon']
I am writing a research paper on a idea Finding middle ground? Multi-objective Natural Language Generation from time-series data
[{"from": "human", "value": "I am writing a research paper on a idea Finding middle ground? Multi-objective Natural Language Generation from time-series data"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: A Natural Language Generation (NLG) system is able to generate text from nonlinguistic data, ideally personalising the content to a user\u2019s specific needs. In some cases, hover, there are multiple stakeholders with their own individual goals, needs and preferences. ,  explore the feasibility of combining the preferences of two different user groups, lecturers and students, when generating summaries in the context of student feedback generation. The preferences of each user group are modelled as a multivariate optimisation function, therefore the task of generation is seen as a multi-objective (MO) optimisation task, where the two functions are combined into one. This initial study shows that treating the preferences of each user group equally smooths the ights of the MO function, in a way that preferred content of the user groups is not presented in the generated summary."}]