Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: With a growing number of b documents, many approaches have been proposed for knowledge discovery on b documents. The documents do not always provide keywords or categories, so unsupervised approaches are desirable, and topic modeling is such an approach for knowledge discovery without using labels. Further, b documents usually have time information such as publish years, so knowledge patterns over time can be captured by incorporating the time information. ,  propose a new topic model called the Author Topic-Flow (ATF) model whose objective is to capture temporal patterns of research interests of authors over time, where each topic is associated with a research domain. The design of the ATF model is based on the hypothesis that direct topic flows are better than indirect topic flows in the state-of-the-art Temporal Author Topic (TAT) model, which is the most similar approach to ours.  prove the hypothesis by showing the effectiveness of the ATF model compared to the TAT model.
['Young-Seob Jeong', 'Sang-Hun Lee', 'Gahgene Gweon']
I am writing a research paper on a idea Discovery of research interests of authors over time using a topic model
[{"from": "human", "value": "I am writing a research paper on a idea Discovery of research interests of authors over time using a topic model"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: With a growing number of b documents, many approaches have been proposed for knowledge discovery on b documents. The documents do not always provide keywords or categories, so unsupervised approaches are desirable, and topic modeling is such an approach for knowledge discovery without using labels. Further, b documents usually have time information such as publish years, so knowledge patterns over time can be captured by incorporating the time information. ,  propose a new topic model called the Author Topic-Flow (ATF) model whose objective is to capture temporal patterns of research interests of authors over time, where each topic is associated with a research domain. The design of the ATF model is based on the hypothesis that direct topic flows are better than indirect topic flows in the state-of-the-art Temporal Author Topic (TAT) model, which is the most similar approach to ours.  prove the hypothesis by showing the effectiveness of the ATF model compared to the TAT model."}]