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Analyzing Quantum Probability Ranking Principle with the concept of Hyperspace Analogue to Language (HAL)

机译:用超空间模拟语言(HAL)概念分析量子概率排名原理

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In the light of Quantum Physics, probabilistic technique is said to support a backbone in the domain of Quantum Information Retrieval (QIR). This well known domain is based on the Quantum Probability Theory, which is used to examine the probability of relevance of a document given a user's query. The Quantum Probability Ranking Principle (QPRP), captures dependencies between documents in absolute way via “quantum interference” by considering a single vector i.e., one-dimension subspace. The HAL semantic space can be used to capture meaning of the document of information needs by representing the document into a high dimensional semantic space. This paper presents an investigation of the Quantum Probability Ranking Principle with the concept of HAL semantic space such that which can act as a bridge the gap between Quantum Probability Theory and HAL semantic space, that can results to agreeable performance in an ad-hoc retrieval task of document ranking.
机译:根据量子物理学,据说概率技术支持量子信息检索(QIR)域中的主干。这个众所周知的领域是基于量子概率论的,该理论用于检查给定用户查询时文档相关性的概率。量子概率排名原则(QPRP)通过考虑单个矢量(即一维子空间),通过“量子干扰”以绝对方式捕获文档之间的依赖关系。通过将文档表示为高维语义空间,可以使用HAL语义空间来捕获信息需求文档的含义。本文对具有HAL语义空间概念的量子概率排名原理进行了研究,以期在量子概率理论与HAL语义空间之间架起一座桥梁,从而在临时检索任务中取得令人满意的性能文档排名。

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