Researchers claim to have developed a new software which is hailed to be capable of fixing broken links on the internet – provided the resources are still on the site’s server. All right, so in plain English, you know those 404 errors you sometimes encounter when clicking on an interesting link or trying to access an important bit of information on a website? They’re the work of the devil. Everyone knows the frustration of following a link to an interesting website only to discover the target page is no longer there and to be presented with an error page, the Iranian researchers said.
Introduced by Mohammad Pourzaferani and Mohammad Ali Nematbakhsh from the Department of Computer Engineering, University of Isfahan, the software does not attempt to fix a broken link at the destination point. Instead, the algorithm depends on the source point of that link and detects the new address of the entity (web page) that is detached or misplaced. A ‘superior’ and an ‘inferior’ dataset are built with this purpose in mind.
According to researchers, this could cause problems when a computer was processing large amounts of data in a financial or scientific analysis, for instance. If the resource continued to exist on servers, then it should be retrievable given, a sufficiently effective algorithm could recreate the missing links.
“The proposed algorithm uses the fact that entities preserve their structure event after movement to another location. Therefore, the algorithm creates an exclusive graph structure for each entity,” explains Pourzaferani. This graph consists of two types of entity called ‘Superior’ and ‘Inferior’. Which are entities point to the detached entity and point by it, respectively. When the broken link is detected the algorithm starts its task to find the new location for detached entity or the best similar candidate for it. To this end, the crawler controller module searches for the superiors of each entity in the inferior dataset, and vice versa. After some steps the search space is narrowed and the best candidate is chosen.”
Researchers tested the algorithm on two snapshots of DBpedia within which are contained almost 300,000 person entities. Their algorithm identified almost 5,000 entities that changed between the first and second snapshot recorded some time later. The algorithm relocated 9 out of 10 of the broken links. The details are reported in the International Journal Web Engineering and Technology, in a paper titled: “Repairing broken RDF links in the web of data”.
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