A framework for automatic semantic video annotation

The rapidly increasing quantity of publicly available videos has driven research into developing automatic tools for indexing, rating, searching and retrieval. Textual semantic representations, such as tagging, labelling and annotation, are often important factors in the process of indexing any video, because of their user-friendly way of representing the semantics appropriate for search and retrieval. Ideally, this annotation should be inspired by the human cognitive way of perceiving and of describing videos. The difference between the low-level visual contents and the corresponding human perception is referred to as the ‘semantic gap’. Tackling this gap is even harder in the case of unconstrained videos, mainly due to the lack of any previous information about the analyzed video on the one hand, and the huge amount of generic knowledge required on the other. This paper introduces a framework for the Automatic Semantic Annotation of unconstrained videos. The proposed framework utilizes two non-domain-specific layers: low-level visual similarity matching, and an annotation analysis that employs commonsense knowledgebases. Commonsense ontology is created by incorporating multiple-structured semantic relationships. Experiments and black-box tests are carried out on standard video databases for action recognition and video information retrieval. White-box tests examine the performance of the individual intermediate layers of the framework, and the evaluation of the results and the statistical analysis show that integrating visual similarity matching with commonsense semantic relationships provides an effective approach to automated video annotation

MATHsAiD: Automated Mathematical Theory Exploration

The aim of the MATHsAiD project is to build a tool for automated theorem-discovery; to design and build a tool to automatically conjecture and prove theorems (lemmas, corollaries, etc.) from a set of user-supplied axioms and definitions. No other input is required. This tool would, for instance, allow a mathematician to try several versions of a particular definition, and in a relatively small amount of time, be able to see some of the consequences, in terms of the resulting theorems, of each version. Moreover, the automatically discovered theorems could perhaps help the users to discover and prove further theorems for themselves. The tool could also easily be used by educators (to generate exercise sets, for instance) and by students as well. In a similar fashion, it might also prove useful in enabling automated theorem provers to dispatch many of the more difficult proof obligations arising in software verification, by automatically generating lemmas which are needed by the prover, in order to finish these proofs

The universal ontology: A vision for conceptual modeling and the semantic web

This paper puts forward a vision of a universal ontology (UO) aiming at solving, or at least greatly alleviating, the semantic integration problem in the field of conceptual modeling and the understandability problem in the field of the semantic web. So far it has been assumed that the UO is not feasible in practice, but we think that it is time to revisit that assumption in the light of the current state-of-the-art. This paper aims to be a step in this direction. We try to make an initial proposal of a feasible UO. We present the scope of the UO, the kinds of its concepts, and the elements that could comprise the specification of each concept. We propose a modular structure for the UO consisting of four levels. We argue that the UO needs a complete set of concept composition operators, and we sketch three of them. We also tackle a few issues related to the feasibility of the UO, which we think that they could be surmountable. Finally, we discuss the desirability of the UO, and we explain why we conjecture that there are already organizations that have the knowledge and resources needed to develop it, and that might have an interest in its development in the near future.Peer ReviewedPostprint (author's final draft