A Markovian random field approach to information retrieval

D. Bouchaffra, J. Meunier
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引用次数: 5

Abstract

A Markovian random field approach is proposed for automatic information retrieval in full text documents. We draw up an analogy between a flow of queries/document images connections and statistical mechanics systems. The Markovian flow process machine (MFP) models the interaction between queries and document images as a dynamical system. The MFP machine searches to fit the user's queries by changing the set of descriptors contained in the document images. There is hence a constant transformation of the informational states of the fund. For each state, a certain degradation of the system is considered. We use simulated annealing algorithm to isolate low energy states: this corresponds to the best "matching" in some sense between queries and images.
一种信息检索的马尔可夫随机场方法
提出了一种用于全文文档信息自动检索的马尔可夫随机场方法。我们将查询流/文档图像连接与统计力学系统进行类比。马尔可夫流处理机(MFP)将查询和文档图像之间的交互建模为一个动态系统。MFP机器通过更改文档图像中包含的描述符集来搜索以适应用户的查询。因此,国际货币基金组织的信息状态不断发生变化。对于每个状态,都考虑了系统的一定退化。我们使用模拟退火算法来隔离低能态:这在某种意义上对应于查询和图像之间的最佳“匹配”。
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