Perceptual navigation in web mining

Abstract

Purpose

This 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/approach

The 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.

Findings

Four 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 implications

When 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/value

The 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.

Citation

Elsayed, A. (2008), "Perceptual navigation in web mining", Online Information Review, Vol. 32 No. 2, pp. 211-220. https://doi.org/10.1108/14684520810879836