Combining Textual and Visual Cues for Content-based Image Retrieval on the World Wide Web

Some WWW image engines allow the user to form a query in terms of text keywords. To build the image index, keywords are extracted heuristically from HTML documents containing each image, and/or from the image URL and file headers. Unfortunately, text-based image engines have merely retro-fitted standard SQL database query methods, and it is difficult to include images cues within such a framework. On the other hand, visual statistics (e.g., color histograms) are often insufficient for helping users find desired images in a vast WWW index. By truly unifying textual and visual statistics, one would expect to get better results than either used separately. In this paper, we propose an approach that allows the combination of visual statistics with textual statistics in the vector space representation commonly used in query by image content systems. Text statistics are captured in vector form using latent semantic indexing (LSI). The LSI index for an HTML document is then associated with each of the images contained therein. Visual statistics (e.g., color, orientedness) are also computed for each image. The LSI and visual statistic vectors are then combined into a single index vector that can be used for content-based search of the resulting image database. By using an integrated approach, we are able to take advantage of possible statistical couplings between the topic of the document (latent semantic content) and the contents of images (visual statistics). This allows improved performance in conducting content-based search. This approach has been implemented in a WWW image search engine prototype.

Textual criticism and medieval Irish studies

Many textual scholars will be aware that the title of the present thesis has been composed in a conscious revisionary relation to Tim William Machan’s influential Textual Criticism and Middle English Texts. (Tim William Machan, Textual Criticism and Middle English Texts (Charlottesville, 1994)). The primary subjects of Machan’s study are works written in English between the fourteenth and sixteenth centuries, the latter part of the period conventionally labelled Middle English. In contrast, the works with which I am primarily concerned are those written by scholars of Old and Middle Irish in the nineteenth, twentieth and twenty-first centuries. Where Machan aims to articulate the textual and cultural factors that characterise Middle English works as Middle English, the purposes of this thesis are (a) to identify the underlying ideological and epistemological perspectives which have informed much of the way in which medieval Irish documents and texts are rendered into modern editions, and (b) to begin to place the editorial theory and methodology of medieval Irish studies within the broader context of Biblical, medieval and modern textual criticism. Hence, the title is Textual Criticism and Medieval Irish Studies, rather than Textual Criticism and Medieval Irish Texts

Estudio de la satisfacción de los estudiantes de Interpretación Textual de la Escuela Superior de Arte Dramático de Córdoba

El estudio de la satisfacción de los estudiantes es fundamental para conocer los errores y aciertos de una institución educativa superior con el fin de poner en práctica estrategias que conduzcan a una mejora en la calidad de su enseñanza. Con este fin, en este artículo hemos evaluado el grado de satisfacción de los estudiantes de Interpretación Textual de la Escuela Superior de Arte Dramático de Córdoba “Miguel Salcedo Hierro”. Alejándonos de los modelos habituales de medir la satisfacción, principalmente de carácter cuantitativo, hemos utilizado como eje metodológico la Teoría Fundamentada en Datos, y como técnicas, la entrevista comprehensiva de Kaufmann y los grupos de discusión. Los resultados han sido muy positivos, pues han mostrado que estos estudiantes tienen un alto nivel de satisfacción, lo que resulta muy valioso para conocer la calidad de esta enseñanza en el momento presente, así como para desarrollar planes específicos que conduzcan a su mejora en el futuro cercano.

Visualising Textual Knowledge about Risks to Aid Risk Communication

This paper demonstrates a potential application for latent semantic analysis and similar techniques in visualising the differences between two levels of knowledge about a risk issue. The HIV/AIDS risk issue will be examined and the semantic clusters of key words in a technical corpora derived from specific literature about HIV/AIDS will be compared with the semantic clusters of those in more general corpora. It is hoped that these comparisons will create a fast and efficient complementary approach to the articulation of mental models of risk issues that could be used to target possible inconsistencies between expert and lay mental models.

Nana, Prostitution and the Textual Foundations of Zola’s 'Au Bonheur des Dames'

This article considers the textual forces operating in Au Bonheur des Dames, Zola's 1883 novel on modern commerce. It proposes that, with its echoes of the disorderly impulses that governed the infamous prostitute Nana earlier in the Rougon-Macquart cycle, coupled with its appreciation of the benefits of regulation, the dynamics of controlled and contained prostitution constitute the energy which fuels an efficient and successful business model in Au Bonheur des Dames. By closely analyzing both texts as well as Zola's preparatory documents, and borrowing from Genette's theories of intertextuality, this study reads Nana as a pre-historic hypotext, buried in the textual chantier from which the structure of Au Bonheur des Dames emerges.

Integrating textual analysis and evidential reasoning for decision making in Engineering design

Decision making is an important element throughout the life-cycle of large-scale projects. Decisions are critical as they have a direct impact upon the success/outcome of a project and are affected by many factors including the certainty and precision of information. In this paper we present an evidential reasoning framework which applies Dempster-Shafer Theory and its variant Dezert-Smarandache Theory to aid decision makers in making decisions where the knowledge available may be imprecise, conflicting and uncertain. This conceptual framework is novel as natural language based information extraction techniques are utilized in the extraction and estimation of beliefs from diverse textual information sources, rather than assuming these estimations as already given. Furthermore we describe an algorithm to define a set of maximal consistent subsets before fusion occurs in the reasoning framework. This is important as inconsistencies between subsets may produce results which are incorrect/adverse in the decision making process. The proposed framework can be applied to problems involving material selection and a Use Case based in the Engineering domain is presented to illustrate the approach. © 2013 Elsevier B.V. All rights reserved.