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Article . 2008 . Peer-reviewed
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Perceptual navigation in web mining

Authors: Adel Elsayed;

Perceptual navigation in web mining

Abstract

PurposeThis paper aims to present an epistemological perspective of how web mining can be performed by human agents, and a technical overview of a possible approach to achieve this.Design/methodology/approachThe concept of visual mining of information is based on the principle of creating a fused information space that could be navigated using visual perception, just as is possible within a natural environment. It is argued that, as the information available through human‐created artefacts increases, conventional methods of information acquisition will fail to circumvent the bottle‐neck created by the associated information overflow.FindingsFour types of human‐created artefacts are identified: cognitive externalisations, artistic expressions, communicative accounts, and factual records. It is the communicative artefacts that are responsible for the information overflow. As a possible way forward, it is suggested that an information space could be constructed in two layers: a perceptual layer and a cognitive layer. The information in the perceptual layer could be encoded in iconic cues to create an information landscape that could be navigated visually. The cognitive layer, on the other hand, will operate on the information‐engendering data structures of the communicative artefacts.Practical implicationsWhen developed, the perceptual layer could provide a subject domain landscape that induces social familiarity with frequently traversed information environments. This should be particularly helpful for learning where frequent traversal provides opportunities for repeated rehearsal, a necessary condition for long‐term retention.Originality/valueThe objective of this paper is to facilitate a shift in cognitive loading associated with knowledge acquisition from post‐perceptual to perceptual operations. The appealing nature of perceptual processing underpins the claim about enhancing long‐term retention.

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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