Building a scalable and accurate copy detection mechanism

Abstract

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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No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 161 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.