摘要
由一名新闻记者-机器人与机器学习的工作人员新闻编辑每日新闻-机器学习的最新数据-英特尔智能系统在一份新的报告中呈现。根据NewsRx编辑对湖北的新闻报道，本文提出了一种改进信息内容的混合模型，即IC+SP，该模型用于提高信息内容的(IC)个词间语义相似性的相关推理，命名为IC+SP，基于IC和最短路径是两个相对独立的语义变量,对语义相似度的影响大致相等的基本假设,IC+SP的范式是将IC相关度量与最短路径线性组合。本研究的资助单位包括国家自然科学基金(NSFC)、国家自然科学基金(NSFC)、湖北省自然科学基金、国家自然资源部数字制图与土地信息应用重点实验室开放研究基金。
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Fresh data on Machine Learning - Intel ligent Systems are presented in a new report. According to news reporting out of Hubei, People’s Republic of China, by NewsRx editors, the research stated, “Thi s paper proposes a hybrid model to improve Information Content (IC) related metr ics of semantic similarity between words, named IC+SP, based on the essential hy pothesis that IC and the shortest path are two relatively independent semantic e vidences and have approximately equal influences to the semantic similarity metr ic. The paradigm of IC+SP is to linearly combine the IC-related metric and the s hortest path.” Funders for this research include National Natural Science Foundation of China ( NSFC), National Natural Science Foundation of China (NSFC), Hubei Provincial Nat ural Science Foundation, China, Open Research Fund of Key Laboratory of Digital Cartography and Land Information Application, Ministry of Natural Resources, Chi na.
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