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Information Structuring and Product Classification

机译:信息结构与产品分类

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摘要

Today's e-commerce often suffers from problems of differing terminologies used by vendors and buyers. Using standardized product classification schemes, such as UNSPSC or eCl@ss often requires time-consuming and costly manual "translation" of internal product catalogues into the standardized terminologies. This paper explores the use of text mining and machine learning approaches to the task of automatic product classification. The results obtained on a real-life product catalogue indicate that high accuracy can be reached, but that some instances cannot be classified automatically, thus suggesting semi-automatic and interactive procedures.
机译:当今的电子商务经常遭受供需双方使用的术语不同的问题。使用诸如UNSPSC或eCl @ ss之类的标准化产品分类方案通常需要耗时且昂贵的手动将内部产品目录“翻译”为标准化术语。本文探讨了文本挖掘和机器学习方法在自动产品分类任务中的使用。在现实生活中的产品目录中获得的结果表明可以达到很高的精度,但是某些实例无法自动分类,因此建议使用半自动和交互过程。

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