Recommendation System for Automatic Recovery of Broken Web Links
IBERAMIA '08 Proceedings of the 11th Ibero-American conference on AI: Advances in Artificial Intelligence
Analyzing information retrieval methods to recover broken web links
ECIR'2010 Proceedings of the 32nd European conference on Advances in Information Retrieval
Updating broken web links: An automatic recommendation system
Information Processing and Management: an International Journal
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In this paper, we describe a design and an implementation of Self-Evolving Database (SEDB), which manages various digital documents with links of five types and supports document management tasks by automating link generation and repair. The SEDB stores only links in a centralized fashion while documents are left in their native formats at their original locations. Each of the links reflects a process-oriented relationship with one of the following five types; process-flow, time-series, classification, detail, and reference. The SEDB can generate links by requirements from systems like groupware when documents have been created or modified. The links are filled in automatically by data from both the systems and the SEDB itself. The SEDB also 'repairs' dangling links which have lost one or both of their own documents by one of the following three repair operations; Link Deletion, Link Merging and Dummy Document Creation.