An oddly-positioned position paper on context and ontology

Proceedings of the 2008 IEEE International Conference on Semantic Computing,This paper is a theoretical analysis of formal annotation and ontology for the expression of the semantics of document. They are found wanting in this respect, not only for technical reasons, but because they embody a fundamentally misunderstood model of the process of signification. The author proposes an alternative model in which the interpretation context plays a fundamental role, and briefly discuss it and its current technical embodiment

Semantic computing in multimedia: ACM multimedia tutorial

This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in Proceedings of the 19th ACM international conference on Multimedia, http://dx.doi.org/10.1145/2072298.2072401This short overview describes the contents of the tutorial Semantic computing in multimedia, which was offered to the participants of ACM Multimedia 2011. Given the impossibility of summarizing properly the contents of the tutorial in just two pages, the purpose of this overview is mainly to introduce the reader to the relevant bibliography

Benchmarking without ground truth

Simone Santini, "Benchmarking without ground truth", Proc. SPIE 6061, Internet Imaging VII, 60610I (2006). Copyright 2006 Society of Photo‑Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibitedMany evaluation techniques for content based image retrieval are based on the availability of a ground truth, that is on a "correct" categorization of images so that, say, if the query image is of category A, only the returned images in category A will be considered as "hits." Based on such a ground truth, standard information retrieval measures such as precision and recall and given and used to evaluate and compare retrieval algorithms. Coherently, the assemblers of benchmarking data bases go to a certain length to have their images categorized. The assumption of the existence of a ground truth is, in many respect, naive. It is well known that the categorization of the images depends on the a priori (from the point of view of such categorization) subdivision of the semantic field in which the images are placed (a trivial observation: a plant subdivision for a botanist is very different from that for a layperson). Even within a given semantic field, however, categorization by human subjects is subject to uncertainty, and it makes little statistical sense to consider the categorization given by one person as the unassailable ground truth. In this paper I propose two evaluation techniques that apply to the case in which the ground truth is subject to uncertainty. In this case, obviously, measures such as precision and recall as well will be subject to uncertainty. The paper will explore the relation between the uncertainty in the ground truth and that in the most commonly used evaluation measures, so that the measurements done on a given system can preserve statistical significance

Intractable problems in novelty and diversity

Versión electrónica de la ponencia presentada en la XVI Jornadas de Ingeniería del Software y de Bases de Datos (JISBD 2011), celebrada en 2011 en A CoruñaInformation retrieval’s basic problem is retrieving a set of documents relevant for a given query. Here, we present three classes of methods that appeared in the liteature, as well as a new one, which is an improvement of the one the three, to retrieve result sets that, in addition to relevance, try to maximize diversity and novelty. We analyze the complexity of these problems and show that whenever relevance, diversity, and novelty are considered together, the methods are all NP-complete.This work was supported in part by the Ministerio de Educaci´on y Ciencia under the grant N. MEC TIN2008-06566-C04-02