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Building a scalable and accurate copy detection mechanism
Open accessAbstract
Often, publishers are reluctant to offer valuable digital documents on the Internet for fear that they will be re-transmitted or copied widely. A Copy Detection Mechanism can help identify such copying. For example, publishers may register their documents with a copy detection server, and the server can then automatically check public sources such as UseNet articles and Web sites for potential illegal copies. The server can search for exact copies, and also for cases where significant portions of documents have been copied. In this paper we study, for the first time, the performance of various copy detection mechanisms, including the disk storage requirements, main memory requirements, response times for registration, and response time for querying. We also contrast performance to the accuracy of the mechanisms (how well they detect partial copies). The results are obtained using SCAM, an experimental server we have implemented, and a collection of 50,000 netnews articles.
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Citations
Cited by
Identifying and Filtering Near-Duplicate Documents
Broder, A. Z. (2000) · Lecture Notes in Computer Science · doi:10.1007/3-540-45123-4_1 · Cited by 395
LSH forest: self-tuning indexes for similarity search
Bawa, M., Condie, T., & Ganesan, P. (2005) · Proceedings of the 14th international conference on World Wide Web - WWW '05 · doi:10.1145/1060745.1060840 · Cited by 353
State-of-the-art in detecting academic plagiarism
Meuschke, N., & Gipp, B. (2013) · International Journal for Educational Integrity · doi:10.21913/ijei.v9i1.847 · Cited by 112
Multilayer SOM With Tree-Structured Data for Efficient Document Retrieval and Plagiarism Detection
Chow, T. W. S., & Rahman, M. K. M. (2009) · IEEE Transactions on Neural Networks · doi:10.1109/tnn.2009.2023394 · Cited by 67
Near Similarity Search and Plagiarism Analysis
Stein, B., & zu Eissen, S. M. (2006) · Studies in Classification, Data Analysis, and Knowledge Organization · doi:10.1007/3-540-31314-1_52 · Cited by 62
Metadata
- Authors
- Shivakumar, N., & Garcia-Molina, H.
- Venue
- Proceedings of the first ACM international conference on Digital libraries - DL '96
- Publisher
- ACM Press
- Published
- 1996
- Pages
- 160-168
- OpenAlex
- W1997657677
- Cited by
- 160
- References
- 0
- FWCI
- 59.76
- Type
- conference paper
- Language
- en
- Open access
- gold
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- CoChat. (2026). Citation check: Building a scalable and accurate copy detection mechanism. https://app.cochat.ai/papers/10.1145/226931.226961
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- Shivakumar, N., & Garcia-Molina, H. (1996). Building a scalable and accurate copy detection mechanism. Proceedings of the first ACM international conference on Digital libraries - DL '96. https://doi.org/10.1145/226931.226961
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
