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中文总结 AI 辅助
研究CD指数操纵问题的复杂性，该问题模拟学者通过合并、添加或删除论文提高论文CD指数的场景，证明这些问题计算困难，还探讨不同参数对其参数化复杂性的影响。
中文摘要 AI 辅助
合并-破坏指数（CD指数）是一种定性衡量专利或研究论文贡献的指标。自其诞生以来，已经进行了大量实验研究来探索该指数。我们着手研究CD指数操纵问题的复杂性，该问题模拟了学者旨在通过合并、添加或删除论文来提高其论文CD指数的场景。我们表明，这些问题在计算上是困难的，即使限制在非常现实的特殊情况下。此外，我们还探讨了不同参数如何影响这些问题的参数化复杂性。
英文摘要
Consolidation-disruption index (CD index) is a metric for qualitatively measuring the contribution of a patent or a research paper. Since its inception, a plethora of experimental studies have been undertaken to explore this index. We embark on the study of the complexity of CD index manipulation problems, which model scenarios where a scholar aims to enhance the CD indices of their papers through merging, adding, or removing papers. We show that these problems are computationally hard, even when restricted to very realistic special cases. Additionally, we explore how different parameters influence the parameterized complexity of these problems.
