Exploiting Synergy Between Ontologies and Recommender Systems

Recommender systems learn about user preferences over time, automatically finding things of similar interest. This reduces the burden of creating explicit queries. Recommender systems do, however, suffer from cold-start problems where no initial information is available early on upon which to base recommendations. Semantic knowledge structures, such as ontologies, can provide valuable domain knowledge and user information. However, acquiring such knowledge and keeping it up to date is not a trivial task and user interests are particularly difficult to acquire and maintain. This paper investigates the synergy between a web-based research paper recommender system and an ontology containing information automatically extracted from departmental databases available on the web. The ontology is used to address the recommender systems cold-start problem. The recommender system addresses the ontology's interest-acquisition problem. An empirical evaluation of this approach is conducted and the performance of the integrated systems measured

Exploiting synergy between ontologies and recommender systems

Recommender systems learn about user preferences over time, automatically finding things of similar interest. This reduces the burden of creating explicit queries. Recommender systems do, however, suffer from cold-start problems where no initial information is available early on upon which to base recommendations.Semantic knowledge structures, such as ontologies, can provide valuable domain knowledge and user information. However, acquiring such knowledge and keeping it up to date is not a trivial task and user interests are particularly difficult to acquire and maintain. This paper investigates the synergy between a web-based research paper recommender system and an ontology containing information automatically extracted from departmental databases available on the web. The ontology is used to address the recommender systems cold-start problem. The recommender system addresses the ontology's interest-acquisition problem. An empirical evaluation of this approach is conducted and the performance of the integrated systems measured

The Stability of an Isotropic Cosmological Singularity in Higher-Order Gravity

We study the stability of the isotropic vacuum Friedmann universe in gravity theories with higher-order curvature terms of the form $(R_{ab}R^{ab})^{n}$ added to the Einstein-Hilbert Lagrangian of general relativity on approach to an initial cosmological singularity. Earlier, we had shown that, when $$, a special isotropic vacuum solution exists which behaves like the radiation-dominated Friedmann universe and is stable to anisotropic and small inhomogeneous perturbations of scalar, vector and tensor type. This is completely different to the situation that holds in general relativity, where an isotropic initial cosmological singularity is unstable in vacuum and under a wide range of non-vacuum conditions. We show that when $n\neq 1$, although a special isotropic vacuum solution found by Clifton and Barrow always exists, it is no longer stable when the initial singularity is approached. We find the particular stability conditions under the influence of tensor, vector, and scalar perturbations for general $n$ for both solution branches. On approach to the initial singularity, the isotropic vacuum solution with scale factor $a(t)=t^{P_{-}/3}$ is found to be stable to tensor perturbations for $0.5<n< 1.1309$ and stable to vector perturbations for $0.861425 < n \leq 1$, but is unstable as $t \to 0$ otherwise. The solution with scale factor $a(t)=t^{P_{+}/3}$ is not relevant to the case of an initial singularity for $n>1$ and is unstable as $t \to 0$ for all $n$ for each type of perturbation.Comment: 25 page

A Feature-Augmented Grammar for Automated Media Production

The IST Polymnia project is creating a fully automated system for personalised video generation, including content creation, selection and composition. This paper presents a linguistically motivated solution using context-free feature-augmented grammar rules to describe editing tasks and hence automate video editing. The solution is media and application independent

Cosmogenic radionuclides on LDEF: An unexpected Be-10 result

Following the discovery of the atmospheric derived cosmogenic radionuclide Be-7 on the Long Duration Exposure Facility (LDEF), a search began for other known nuclides produced by similar mechanisms. None of the others have the narrow gamma-ray line emission of Be-7 decay which enabled its rapid detection and quantification. A search for Be-10 atoms on LDEF clamp plates using accelerator mass spectrometry is described. An unexpected result was obtained