本文探讨了Web信息抽取系统的最新进展，强调了从不同来源提取有用数据的重要性，并概述了当前主要的数据抽取方法。文中详细对比了这些方法的任务领域、自动化程度和技术手段，为评估各种抽取方法提供了有价值的依据。
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http://www.csie.ncu.edu.tw/~chia/
Chang, C.; Kayed, M.; Girgis, R. & Shaalan, K. A Survey of Web Information Extraction Systems Knowledge and Data Engineering, IEEE Transactions on, 2006, 18, 1411-1428.
Abstract—The Internet presents a huge amount of useful information which is usually formatted for its users, which makes it difficult to extract relevant data from various sources. Therefore, the availability of robust, flexible Information Extraction (IE) systems that transform the Web pages into program-friendly structures such as a relational database will become a great necessity. Although many
approaches for data extraction from Web pages have been developed, there has been limited effort to compare such tools. Unfortunately, in only a few cases can the results generated by distinct tools be directly compared since the addressed extraction tasks are different. This paper surveys the major Web data extraction approaches and compares them in three dimensions: the task domain, the automation degree, and the techniques used. The criteria of the first dimension explain why an IE system fails to handle some Web sites of particular structures. The criteria of the second dimension classify IE systems based on the techniques used. The criteria of the third dimension measure the degree of automation for IE systems. We believe these criteria provide qualitatively measures to evaluate various IE approaches.
Chang, C.; Kayed, M.; Girgis, R. & Shaalan, K. A Survey of Web Information Extraction Systems Knowledge and Data Engineering, IEEE Transactions on, 2006, 18, 1411-1428.
Abstract—The Internet presents a huge amount of useful information which is usually formatted for its users, which makes it difficult to extract relevant data from various sources. Therefore, the availability of robust, flexible Information Extraction (IE) systems that transform the Web pages into program-friendly structures such as a relational database will become a great necessity. Although many
approaches for data extraction from Web pages have been developed, there has been limited effort to compare such tools. Unfortunately, in only a few cases can the results generated by distinct tools be directly compared since the addressed extraction tasks are different. This paper surveys the major Web data extraction approaches and compares them in three dimensions: the task domain, the automation degree, and the techniques used. The criteria of the first dimension explain why an IE system fails to handle some Web sites of particular structures. The criteria of the second dimension classify IE systems based on the techniques used. The criteria of the third dimension measure the degree of automation for IE systems. We believe these criteria provide qualitatively measures to evaluate various IE approaches.
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