Originality criteria are frequently used to assess the validity of intellectual property (IP) rights, such as copyright and design rights. In this work, the originality of an asset is formulated as a function of the distances between this asset and its comparands, using concepts of maximum entropy and surprisal analysis. Namely, this function is defined as the reciprocal of the surprisal associated with a given asset. Creative assets can justifiably be compared to particles that repel each other. This allows a very simple formula to be obtained, in which the originality of a given asset writes as the ratio of a reference energy to an interaction energy imparted to that asset. In particular, using an electrostatic-like pair potential makes it possible to rewrite the originality function as the ratio of two average distances, i.e., as the harmonic mean of the distances from the given asset to its comparands divided by the harmonic mean of the distances between the sole comparands. Thus, the originality of objects such as IP assets can be simply estimated based on distances computed according to vectors extracted thanks to unsupervised machine learning techniques or other algorithms. Application is made to various types of IP assets, including emojis, typeface designs, paintings, and novel titles.
翻译:通常使用原始标准来评估知识产权(IP)权利的有效性,例如版权和设计权。在这项工作中,资产的原始性是作为该资产与其比较器之间的距离函数而形成的,使用最大正辛基和超正基分析的概念。也就是说,这一功能被定义为与特定资产相关联的超离差的对等值。创造性资产可以合理地与相互反射的粒子进行比较。这样可以取得一种非常简单的公式,在这种公式中,特定资产的原始性作为参考能量与该资产所传导的交互能量之比来写。特别是,使用类似电静配方的潜力使得有可能将原始性功能改写为两个平均距离之比,也就是说,从特定资产到该资产之间相联的距离的对等值的对等值的对等值。因此,可以简单地根据通过不超强的图像提取的载量量量量量计算到该资产所传输的能量的原始性比值来估算某项资产的原始性。 应用的是各种机器类型,包括新式的机器设计或新式结构。