HieNet: a user-centered approach for automatic link generation

Most hypertext systems facilitate one-at-a-time link creation, but only a few support automatic link generation. In systems that do support automatic link generation, user interests are either ignored or explicit user actions are required to enter a set of keywords and queries. In this paper we present a new linking mechanism called HieNet, implemented on top of a commercial hypertext system, that generates new links based on previously-created user links. Our approach allows users direct control over similarity thresholds, node granularity, and the extent of linking in composite nodes. Our work derives from Salton’s work on automatic generation of links using term vectors, and extends the ideas incorporated in Bernstein’s Link Apprentice and Lotus SmarText. Preliminary tests show that HieNet generates plausible links with acceptable performance and that users can learn to control the link generation parameters.

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