Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Skyline queries are a ll-studied problem for multidimensional data, wherein points are returned to the user i↵ no other point is preferable across all attributes. This leaves only the points most likely to appeal to an arbitrary user. Hover, some dominated points may still be interesting, and the skyline o↵ers little support for helping the user understand why some interesting points are omitted from the results. ,  introduce the Sky-not query .G iven a query point p, a dataset S, and constraints with bounding corners qL and qU, the Sky-not query returns the alternative constraints q 0 closest to qL for which p is in the skyline. This equips the user with an understanding of not just that a point was dominated, but also how severely. He can then assess himself whether the point is competitive.  first propose theoretical results that show how to drastically reduce the input processed by a Sky-not query, independent of any algorithm.  then o↵er a skyline-like and an ecient recursive algorithm for solving Sky-not queries, which  evaluate in an extensive experimental evaluation.
['Sean Chester', 'Ira Assent']
I am writing a research paper on a idea Explanations for Skyline Query Results
[{"from": "human", "value": "I am writing a research paper on a idea Explanations for Skyline Query Results"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Skyline queries are a ll-studied problem for multidimensional data, wherein points are returned to the user i\u21b5 no other point is preferable across all attributes. This leaves only the points most likely to appeal to an arbitrary user. Hover, some dominated points may still be interesting, and the skyline o\u21b5ers little support for helping the user understand why some interesting points are omitted from the results. ,  introduce the Sky-not query .G iven a query point p, a dataset S, and constraints with bounding corners qL and qU, the Sky-not query returns the alternative constraints q 0 closest to qL for which p is in the skyline. This equips the user with an understanding of not just that a point was dominated, but also how severely. He can then assess himself whether the point is competitive.  first propose theoretical results that show how to drastically reduce the input processed by a Sky-not query, independent of any algorithm.  then o\u21b5er a skyline-like and an ecient recursive algorithm for solving Sky-not queries, which  evaluate in an extensive experimental evaluation."}]