Web Content Extraction

Author:

Weninger Tim1,Palacios Rodrigo2,Crescenzi Valter3,Gottron Thomas4,Merialdo Paolo3

Affiliation:

1. University of Notre Dame, Notre Dame, Indiana

2. California State University, Fresno, California

3. Università Roma Tre Dipartimento di Ingegneria, Rome, Italy

4. University of KoblenzLandau, Germany

Abstract

In this paper, we present a meta-analysis of several Web content extraction algorithms, and make recommendations for the future of content extraction on the Web. First, we find that nearly all Web content extractors do not consider a very large, and growing, portion of modernWeb pages. Second, it is well understood that wrapper induction extractors tend to break as theWeb changes; ; heuristic/ feature engineering extractors were thought to be immune to a Web site's evolution, but we find that this is not the case: heuristic content extractor performance also tends to degrade over time due to the evolution of Web site forms and practices. We conclude with recommendations for future work that address these and other findings.

Publisher

Association for Computing Machinery (ACM)

Cited by 10 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Lecture Information Service Based on Multiple Features Fusion;International Journal of Software Engineering and Knowledge Engineering;2021-04

2. Improving User Experience of Eye Tracking-Based Interaction;ACM Transactions on Computer-Human Interaction;2019-12-05

3. Automatic news-roundup generation using clustering, extraction, and presentation;Multimedia Systems;2019-11-09

4. Robust Web Data Extraction Based on Unsupervised Visual Validation;Intelligent Information and Database Systems;2019

5. Main Content Detection in HTML Journal Articles;Proceedings of the ACM Symposium on Document Engineering 2018;2018-08-28

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