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Text similarity computing method

A text similarity and calculation method technology, applied in the field of personalized product recommendation, can solve problems such as not applicable to ordinary e-commerce models

Inactive Publication Date: 2014-06-04
DALIAN LINGDONG TECH DEV
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Problems solved by technology

There are many shortcomings in these methods: although the recommendation technology based on user statistical information is very useful in some websites with membership as the main sales model, it is not suitable for ordinary e-commerce models; Content-based recommendation has a common characteristic that it needs to describe the characteristics of the item, that is, the recommended product, before it can be recommended.

Method used

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Embodiment Construction

[0029] Such as figure 1 Calculation of the similarity of the text shown: After the feature vector is determined, all texts must be standardized using the final feature set after word segmentation, and all texts can be described by a vector. The traditional text similarity calculation method is to use the vector space model, according to the word frequency TF and the inverse text frequency IDF, to give the weight of each component of the vector, which corresponds to the vector in the Euclidean space one by one, and borrow the cosine of the vector angle in the Euclidean space The method to obtain a quantitative representation of the similarity between text q and d is shown in the following three formulas:

[0030] q={w q1 ,w q2 ,...,w qn}

[0031] d={w d1 ,w d2 ,...,w dn}

[0032] sim ( q , d ) = cos ( q , d ...

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Abstract

The invention discloses a text similarity computing method. The method comprises the following steps of text representation and text similarity computing. The aim of text representation is that a text document of product description is converted into a vector for description. In the text similarity computing method, natural language processing technologies such as Chinese words segmentation, stop word removing, word frequency statistics and the like are used for converting all the description texts of products into vectors; the text similarity is computed by a method based on a Hamming distance, and the other advantage of the Hamming distance is that the computing speed is very high. Due to the fact that the method of statistical machine learning is used, so that the text similarity computing method is more stable and effective compared with a method based on rules.

Description

technical field [0001] The invention relates to a personalized product recommendation technology, in particular to a text similarity calculation method. Background technique [0002] With the rapid development of e-commerce websites, people rely more and more on e-commerce websites to purchase goods. However, the number and types of commodities on e-commerce websites are increasing exponentially, and it is very difficult to accurately and quickly find and obtain the commodities you need from this ocean. Users tend to lose their purpose when making queries. Therefore, when browsing the site, many users often spend a lot of time and energy browsing pages that have nothing to do with the goods they want to buy, which makes many users lose confidence in purchasing goods on this website, thus causing this website to lose many users. In order to increase sales, increase user satisfaction, increase competitiveness and theoretical research, e-commerce commodity recommendation syst...

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Application Information

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IPC IPC(8): G06F17/30
CPCG06F40/216G06F40/30G06Q30/0271
Inventor 汲业徐青
Owner DALIAN LINGDONG TECH DEV
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