Slicepedia: Towards Long Tail Resource Production through Open Corpus Reuse Killian Levacher, Seamus Lawless, Vincent Wade Trinity College Dublin Abstract. The production of resources supporting the needs of Adap- tive Hypermedia Systems (AHS) is labor-intensive (e.g. in areas such as educational, news media etc...). As a result, content production is focused upon meeting the needs of resources with higher demand, which limits the extent upon which long tail content requirement niches of AHS can be met. Open corpus slicing attempts to convert the wealth of information available on the World Wide Web, into customizable information objects. This approach could provide the basis of an open corpus supply service meeting long tail content requirements of AHS. This paper takes a case study approach, focusing on an educational sector of adaptive hyperme- dia, to test out the effect of using Slicepedia, a service which enables the discovery, reuse and customization of open corpus resources. An architec- ture and implementation of the system is presented along with a user-trial evaluation suggesting slicing techniques could represent a valid candidate for long tail content production supply of AHS. 1 Introduction Adaptive Hypermedia Systems (AHS) have traditionally attempted to respond to the demand for personalized interactive learning experiences through the support of adaptivity, which sequences re-composable pieces of information into personal- ized presentations for individual users. While their effectiveness and benefits have been proven in numerous studies [1], the ability of AHS to reach the mainstream audience has been limited [2]. For example, in educational hypermedia systems, this has been in part due to their reliance upon large volumes of one-size-fits-all educational resources available at high production costs [3]. Although extensively studied, solutions proposed so far (section 2) do not address the fundamental problem directly which is the labor-intensive manual production of such resources. As a result, content creation is naturally focused upon addressing the needs of targeted resources in higher demand (area 1 in figure 1). AHS content requirements however, naturally follow a long tail distribution. They require large varieties of unique niche content supplies needed for once-off usages only (area 2), which traditional content production approaches desist due to prohibitive costs. In parallel to these developments, the field of Open Adaptive Hypermedia (OAH) has attempted to leverage the wealth of information, which has now become accessible on the WWW as open corpus information. Open Corpus Slicing (OCS) techniques [4] in particular aim at automatically converting native open corpus resources into customizable content objects meeting various specific AHS content requirement needs (topic covered, style, granularity, delivery format, annotations). We believe that, in order to serve AHS long tail content requirements, the cost intensive, manual production and/or adaptation of educational resources