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Traceable and trusted smart harvesting algorithm from unstructured and structured web (smese-ttsha)

Author: 
Ronald Brisebois, Apollinaire Nadembega and Toufic Hajj
Subject Area: 
Physical Sciences and Engineering
Abstract: 

Entity Resolution and unstructured Web has recently attracted significant attentions and usage of Block Chain is increasing to try to solve different problems as traceability. Entity Resolution can be defined as the process of identifying, matching, verifying accuracy and try to get to the same metadata definition of the Entity from several sources including the unstructured web and structured databases. A new issue have been identified for Entity Resolution: What is information today could be wrong in an instant later, so we talk now of the value of the Entity Resolution in function of the time. In this paper, we address the issue of data and metadata timely integration from unstructured, structured and multi-sources. We propose a new semantic approach of data integration and Entity Resolution that aims to build a unified and trusted traceable repository (UTTR), called SMESE Traceable Trusted Smart Harvesting Algorithm from Unstructured and Structured Web (SMESE-TTSHA). SMESE-TTSHA is based on Traceable Smart Harvesting Strategies (TSHS) addresses the problem of performing Traceable Entity Resolution (MLM-TTSHA) using trusted, ranked sources and taking care of the value of the information at an instant t. We experimentally evaluate our SMESE-TTSHA approach on large real datasets and compare the performance results with those of existing approaches. Our experimental results show our proposed models perform well on the Traceable Entity Resolution compared to the existing approaches, while also satisfying constraint of the algorithm.

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