Search (11 results, page 1 of 1)

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Abstract

This chapter considers fiction retrieval research and initiatives, providing an overview of some of the approaches that have been developed. In particular, it describes two recent approaches to fiction retrieval that have made use of theoretical concepts drawn from literary theory. Fiction is an interesting information domain because it includes documents that serve two purposes, which are reading for pleasure and scholarly study (Beghtol, 1994), but fiction retrieval has not always focused on both aspects. In the 19th century, the approach was to treat fiction from a knowledge perspective within general classification schemes. The Dewey Decimal Classification (DDC), the Library of Congress Classification (LCC) and the Universal Decimal Classification (UDC) contain classes for literature, with the main subdivision in each case being the language in which it is written. Further subdivision is possible based on literary form, historical period or the works of an individual author (Riesthuis, 1997).

Source

Innovations in information retrieval: perspectives for theory and practice. Eds.: A. Foster, u. P. Rafferty

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Abstract

This paper revisits PoeTryMe, a poetry generation platform, and presents its most recent instantiation for producing poetry inspired by trends in the Twitter social network. The presented system searches for tweets that mention a given topic, extracts the most frequent words in those tweets, and uses them as seeds for the generation of new poems. The set of seeds might still be expanded with semantically-relevant words. Generation is performed by the classic PoeTryMe system, based on a semantic network and a grammar, with a previously used generate&test strategy. Illustrative results are presented using different seed expansion settings. They show that the produced poems use semantically-coherent lines with words that, at the time of generation, were associated with the topic. Resulting poems are not really about the topic, but they are a way of expressing, poetically, what the system knows about the semantic domain set by the topic.

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Abstract

This article explores the topic of fiction classification. The first section attempts to define the field, discussing fiction classification, its schemes, objectivity, aboutness, and shelf classification. The second section suggests three new ideas building upon the foundation of the first: a faceted multi-warrant classification, controlled term affective dimension searching, and the design of a user-oriented recommendation-based system.

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Abstract

Purpose - The purpose of this paper is to investigate fiction readers' interest criteria when selecting novels in library catalogs for various search tasks. Design/methodology/approach - The data of the book selection behavior from 80 genuine fiction readers were collected using recorded interviews and conversations. The data were qualitatively analyzed. Reuter's categorization of the components of aesthetic relevance has contributed to the construction of interest dimensions. Findings - A five-dimension categorization of interest criteria is presented based on fiction readers' interpretations of the influential factors in fiction book selection in different search tasks. The findings revealed that readers apply the identified interest criteria in a flexible and multiphase way depending to the search task and the system used. The findings showed a context-related pattern in readers' fiction book selections. A combination of readers' search capacities, "behind the eyes" knowledge, affective factors and a well-functioning interaction with a system used results in a successful book selection. Originality/value - A five-dimension categorization of adult fiction readers' interest criteria was created based on their search behaviors in library catalogs. The results provide a systematic step toward a comprehensive understanding of readers' fiction book selection in digital environments.

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Abstract

Little is known about what factors influence users' continued use of social cataloging sites. This study therefore examines the impacts of key factors from theories of information systems (IS) success and sense of community (SOC) on users' continuance intention in the social cataloging context. Data collected from an online survey of 323 social cataloging users provide empirical support for the research model. The findings indicate that both information quality (IQ) and system quality (SQ) are significant predictors of satisfaction and SOC, which in turn lead to users' intentions to continue using these sites. In addition, SOC was found to affect continuance intention not only directly, but also indirectly through satisfaction. Theoretically, this study draws attention to a largely unexplored but essential area of research in the social cataloging literature and provides a fundamental basis to understand the determinants of continued social cataloging usage. From a managerial perspective, the findings suggest that social cataloging service providers should constantly focus their efforts on the quality control of their contents and system, and the enhancement of SOC among their users.

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Abstract

Purpose - Library Director Jarmo Saarti introduced a wide or ideal model for fiction in literature in his dissertation, published in 1999. It introduces those aspects that should be included in an information system for fiction. Such aspects include literary prose and its intertextual references to other works, the writer, readers' and critics' receptions of the work as well as a researcher's view. It is also important to note how libraries approach a literary work by means of inventory, classification and content description. The most ambiguous of the aspects relates to that context in cultural history, which the work reflects and is a part of. The paper aims to discuss these issues. Design/methodology/approach - Since the model consists of several components which are not found in present library information systems and cannot be implemented by them, a new way had to be found to produce, save, process and present fiction-related metadata. The Semantic Computing Research Group of Aalto University has developed several Semantic Web services for use in the field of culture, so cooperation with it and the use of Semantic Web tools were a natural starting point for the construction of the new service. Kirjasampo will be based on the Semantic Web RDF data model. The model enables a flexible linking of metadata derived from different sources, and it can be used to build a Semantic Web that can be approached contextually from different angles. Findings - The "semantically enriched" ideal model for fiction has hence been realised, at least to some extent: Kirjasampo supports literature-related metadata that is more varied than earlier and aims to account for different contexts within literature and connections with regard to other cultural phenomena. It also includes contemporary reviews of works and, as such, readers' receptions as well. Modern readers can share their views on works, once the user interface of the server is completed. It will include several features from the Kirjasto 2.0-application, which enables the evaluation, description and recommendations of works. The service should be online by the end of Spring 2011. Research limitations/implications - The project involves novel collaboration between a public library and a computer science research unit, and utilises a novel approach to the description of fiction. Practical implications - The system encourages user participation in the description of fiction and is of practical benefit to librarians in understanding both how fiction is organised and how users interpret the same. Originality/value - Upon completion, the service will be the first Finnish information system for libraries built with the tools of the Semantic Web which offers a completely new user environment and application for data produced by libraries. It also strives to create a new model for saving and producing data, available to both library professionals and readers. The aim is to save, accumulate and distribute literary knowledge, experiences and silent information.

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Abstract

Kirjasampo.fi is a Web service for fiction. It was constructed after rethinking all the phases of metadata production, and is the first Finnish information system for libraries to be built with the tools of the Semantic Web. Kirjasampo is based on a metadata schema for fiction that uses a Resource Description Framework (RDF) data model. A user-friendly annotation editor enables library professionals to save, accumulate, and distribute literary knowledge and tacit information. The goal of Kirjasampo is to describe the contents of literary works based on the Functional Requirements for Bibliographic Records. Content description is done using ontologies, which enable a flexible linking of metadata.

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Abstract

Die vorliegende Masterarbeit setzt sich mit dem Information Retrieval anhand der Repräsentation von Charakteren der Kinder und Jugendbuchserie "Die drei ???" mit dem Datenbanksystem Access auseinander. Dabei werden sämtliche Aspekte von der Informations- und Datenbeschaffung aus 55 "Die drei ???"-Büchern über die Datenbankerstellung und -aufbereitung bis hin zu den abschließenden Evaluationen beschrieben. Insbesondere versucht die Arbeit die Nutzergruppe Autoren abzudecken, so dass die Datenbank ihnen eine erleichterte Figurenübersicht und eine Hilfestellung bei der Figurensuche geben soll.

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Abstract

This paper presents a Web intelligence portal that captures and aggregates news and social media coverage about "Game of Thrones", an American drama television series created for the HBO television network based on George R.R. Martin's series of fantasy novels. The system collects content from the Web sites of Anglo-American news media as well as from four social media platforms: Twitter, Facebook, Google+ and YouTube. An interactive dashboard with trend charts and synchronized visual analytics components not only shows how often Game of Thrones events and characters are being mentioned by journalists and viewers, but also provides a real-time account of concepts that are being associated with the unfolding storyline and each new episode. Positive or negative sentiment is computed automatically, which sheds light on the perception of actors and new plot elements.

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Abstract

Fiction content analysis and retrieval are interesting specific topics for two major reasons: 1) the extensive use of fictional works; and, 2) the multimodality and interpretational nature of fiction. The primary challenge in the analysis of fictional content is that there is no single meaning to be analysed; the analysis is an ongoing process involving an interaction between the text produced by author, the reader and the society in which the interaction occurs. Furthermore, different audiences have specific needs to be taken into consideration. This article explores the topic of fiction knowledge organization, including both classification and indexing. It provides a broad and analytical overview of the literature as well as describing several experimental approaches and developmental projects for the analysis of fictional content. Traditional fiction indexing has been mainly based on the factual aspects of the work; this has then been expanded to handle different aspects of the fictional work. There have been attempts made to develop vocabularies for fiction indexing. All the major classification schemes use the genre and language/culture of fictional works when subdividing fictional works into subclasses. The evolution of shelf classification of fiction and the appearance of different types of digital tools have revolutionized the classification of fiction, making it possible to integrate both indexing and classification of fictional works.