基于上下文需求和特征样本大小的信息检索过程原型研究

K. Sridevi, S. Prakasha
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引用次数: 0

摘要

信息检索可以为组织提供即时的价值,信息检索已经成为当前信息管理系统的核心,这对于我们如何在海量的数据中收集有效的信息有着深远的意义。信息检索在许多领域都是一个备受争议的问题。今天,从数字图书馆到媒体搜索,信息检索已经在行业中占据了一席之地。有效的仿真是有效信息检索的基础。这些框架根据其统计估计方法分为两组:检查术语依赖性的模型,以及考虑术语加权特征的模型。大多数模型找到了一个可以理解的术语“自由”,而其他模型则考虑了这种关系。另一方面,术语加权是一种有效索引文本的技术。本文的目的是比较和对比使用术语依赖/独立和术语加权的各种信息检索结构。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Study of Prototyping in Information Retrieval Process Utilizing Context Requirements and Feature Sample Sizes
Information retrieval can provide organizations with immediate value, Information retrieval has become a core of the current information managing systems, this has given profound importance on how we gather effective information in a huge pile of data. Information retrieval is a highly debated issue in a variety of fields. Today right from digital library to media searching information retrieval has taken up the place in the industry. Effective simulation is the foundation of effective information retrieval. These frameworks were divided into two groups based on their statistical estimation methods: models where the terminology dependency is being checked and also the models where the weighting features of the terms are being taken into consideration. Most models found an understanding term freedom, whereas others take this relationship into account. Term weighting, but in the other end, is a technique for effectively indexing a text. The intention of this research article is to compare and contrast various information retrieval structures that use term dependence/independence and term weighting.
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