Literary texts in an electronic age: Scholarly implications and library services [papers presented at the 1994 Clinic on Library applications of Data Processing, April 10-12, 1994]

Authors and readers in an age of electronic texts / Jay David Bolter -- Electronic texts in the humanities : a coming of age / Susan Hockey -- The Text Encoding Initiative : electronic text markup for research / C.M. Sperberg-McQueen -- Electronic texts and multimedia in the academic library : a view from the front line / Anita K. Lowry -- Humanizing information technology : cultural evolution and the institutionalization of electronic text processing / Mark Tyler Day -- Cohabiting with copyright on the nets / Mary Brandt Jensen -- The role of the scholarly publisher in an electronic environment / Lorrie LeJeune -- The feasibility of wide-area textual analysis systems in libraries : a practical analysis / John Price-Wilkin -- The scholar and his library in the computer age / James W. Marchand -- The challenges of electronic texts in the library : bibliographic control and access / Rebecca S. Guenther -- Durkheim???s imperative : the role of humanities faculty in the information technologies revolution / Robert Alun Jones -- The materiality of the book : another turn of the screw / Terry Belanger.published or submitted for publicatio

Full Report: Use and Users of Digital Resources: A Focus on Undergraduate Education in the Humanities and Social Sciences

A "build it and they will come" approach to many university digitization initiatives has precluded systematic investigations of the demand for these resources. Those who fund and develop digital resources have identified the general lack of knowledge about the level and quality of their use in educational settings as pressing concerns. This full report describes our research and the complete results of a large 2-year study. The purpose of our research was (1) to map the universe of digital resources available to a subset of undergraduate educators in the humanities and social sciences, and (2) to investigate how and if available digital resources are actually being used in undergraduate teaching environments. We employed multiple methods, including surveys and focus groups. Our definition of digital resources was intentionally broad and included rich media objects (e.g., maps, video, images, etc.) as well as text

Affordances and limitations of algorithmic criticism

Humanities scholars currently have access to unprecedented quantities of machine-readable texts, and, at the same time, the tools and the methods with which we can analyse and visualise these texts are becoming more and more sophisticated. As has been shown in numerous studies, many of the new technical possibilities that emerge from fields such as text mining and natural language processing can have useful applications within literary research. Computational methods can help literary scholars to discover interesting trends and correlations within massive text collections, and they can enable a thoroughly systematic examination of the stylistic properties of literary works. While such computer-assisted forms of reading have proven invaluable for research in the field of literary history, relatively few studies have applied these technologies to expand or to transform the ways in which we can interpret literary texts. Based on a comparative analysis of digital scholarship and traditional scholarship, this thesis critically examines the possibilities and the limitations of a computer-based literary criticism. It argues that quantitative analyses of data about literary techniques can often reveal surprising qualities of works of literature, which can, in turn, lead to new interpretative readings

Recuperação de informação baseada em frases para textos biomédicos

Mestrado em Engenharia de Computadores e TelemáticaO desenvolvimento de novos métodos experimentais e tecnologias de alto rendimento no campo biomédico despoletou um crescimento acelerado do volume de publicações científicas na área. Inúmeros repositórios estruturados para dados biológicos foram criados ao longo das últimas décadas, no entanto, os utilizadores estão cada vez mais a recorrer a sistemas de recuperação de informação, ou motores de busca, em detrimento dos primeiros. Motores de pesquisa apresentam-se mais fáceis de usar devido à sua flexibilidade e capacidade de interpretar os requisitos dos utilizadores, tipicamente expressos na forma de pesquisas compostas por algumas palavras. Sistemas de pesquisa tradicionais devolvem documentos completos, que geralmente requerem um grande esforço de leitura para encontrar a informação procurada, encontrando-se esta, em grande parte dos casos, descrita num trecho de texto composto por poucas frases. Além disso, estes sistemas falham frequentemente na tentativa de encontrar a informação pretendida porque, apesar de a pesquisa efectuada estar normalmente alinhada semanticamente com a linguagem usada nos documentos procurados, os termos usados são lexicalmente diferentes. Esta dissertação foca-se no desenvolvimento de técnicas de recuperação de informação baseadas em frases que, para uma dada pesquisa de um utilizador, permitam encontrar frases relevantes da literatura científica que respondam aos requisitos do utilizador. O trabalho desenvolvido apresenta-se em duas partes. Primeiro foi realizado trabalho de investigação exploratória para identificação de características de frases informativas em textos biomédicos. Para este propósito foi usado um método de aprendizagem automática. De seguida foi desenvolvido um sistema de pesquisa de frases informativas. Este sistema suporta pesquisas de texto livre e baseadas em conceitos, os resultados de pesquisa apresentam-se enriquecidos com anotações de conceitos relevantes e podem ser ordenados segundo várias estratégias de classificação.Modern advances of experimental methods and high-throughput technology in the biomedical domain are causing a fast-paced, rising growth of the volume of published scientific literature in the field. While a myriad of structured data repositories for biological knowledge have been sprouting over the last decades, Information Retrieval (IR) systems are increasingly replacing them. IR systems are easier to use due to their flexibility and ability to interpret user needs in the form of queries, typically formed by a few words. Traditional document retrieval systems return entire documents, which may require a lot of subsequent reading to find the specific information sought, frequently contained in a small passage of only a few sentences. Additionally, IR often fails to find what is wanted because the words used in the query are lexically different, despite semantically aligned, from the words used in relevant sources. This thesis focuses on the development of sentence-based information retrieval approaches that, for a given user query, allow seeking relevant sentences from scientific literature that answer the user information need. The presented work is two-fold. First, exploratory research experiments were conducted for the identification of features of informative sentences from biomedical texts. A supervised machine learning method was used for this purpose. Second, an information retrieval system for informative sentences was developed. It supports free text and concept-based queries, search results are enriched with relevant concept annotations and sentences can be ranked using multiple configurable strategies