Automatic Extraction of Product Information from Multiple e-Commerce Web Sites

被引：0

作者：

Nasti, Samiah Jan ^{[1
]}

Asger, M. ^{[2
]}

Butt, Muheet Ahmad ^{[3
]}

机构：

[1] BGSB Univ, Dept Comp Sci, Rajouri, Jammu & Kasmir, India

[2] BGSB Univ, Sch Math Sci & Engn, Rajouri, Jammu & Kasmir, India

[3] Univ Kashmir Hazratbal Srinagar, Dept Comp Sci, Srinagar, Jammu & Kasmir, India

来源：

PROCEEDINGS OF RECENT INNOVATIONS IN COMPUTING, ICRIC 2019 | 2020年 / 597卷

关键词：

Document Object Model (DOM) tree; Crawling; Clustering; Wrapper generation;

D O I：

10.1007/978-3-030-29407-6_53

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

With the growth of e-commerce, shopping online has now become a part and parcel of every one's life. The advantage of e-commerce Web sites is that they can reach to a very large number of customers despite of distance and time limitations. The main aim of this paper is to extract the product information from various e-commerce sites. Extraction of such information can help the business organizations to fetch and attract the large number of customers to their Web site and increase profit. So, in this paper, we propose a fully automatic method which will extract and integrate information from multiple e-commerce Web sites in order to improve business decision making. The proposed method is also comparatively better at precision and recall than other methods.

引用

页码：739 / 747

页数：9

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