112,669 research outputs found
A modular methodology for converting large, complex books into usable, accessible and standards-compliant ebooks
This report describes the methodology used for ebook creation for the Glasgow Digital Library (GDL), and provides detailed instructions on how the same methodology could be used elsewhere. The document includes a description and explanation of the processes for ebook creation followed by a tutorial
From XML to XML: The why and how of making the biodiversity literature accessible to researchers
We present the ABLE document collection, which consists of a set of annotated volumes of the Bulletin of the British Museum (Natural History). These follow our work on automating the markup of scanned copies of the biodiversity literature, for the purpose of supporting working taxonomists. We consider an enhanced TEI XML markup language, which is used as an intermediate stage in translating from the initial XML obtained from Optical Character Recognition to the target taXMLit. The intermediate representation allows additional information from external sources such as a taxonomic thesaurus to be incorporated before the final translation into taXMLit
Harvesting Entities from the Web Using Unique Identifiers -- IBEX
In this paper we study the prevalence of unique entity identifiers on the
Web. These are, e.g., ISBNs (for books), GTINs (for commercial products), DOIs
(for documents), email addresses, and others. We show how these identifiers can
be harvested systematically from Web pages, and how they can be associated with
human-readable names for the entities at large scale.
Starting with a simple extraction of identifiers and names from Web pages, we
show how we can use the properties of unique identifiers to filter out noise
and clean up the extraction result on the entire corpus. The end result is a
database of millions of uniquely identified entities of different types, with
an accuracy of 73--96% and a very high coverage compared to existing knowledge
bases. We use this database to compute novel statistics on the presence of
products, people, and other entities on the Web.Comment: 30 pages, 5 figures, 9 tables. Complete technical report for A.
Talaika, J. A. Biega, A. Amarilli, and F. M. Suchanek. IBEX: Harvesting
Entities from the Web Using Unique Identifiers. WebDB workshop, 201
Delivering the Maori-language newspapers on the Internet
Although any collection of historical newspapers provides a particularly rich and valuable record of events and social and political commentary, the content tends to be difficult to access and extremely time-consuming to browse or search. The advent of digital libraries has meant that for electronically stored text, full-text searching is now a tool readily available for researchers, or indeed anyone wishing to have asscess to specific information in text. Text in this form can be readily distributed via CD-ROM or the Internet, with a significant impact on accessibility over traditional microfiche or hard-copy distribution. For the majority of text being generated de nouveau, availability in electronic form is standard, and hence the increasing use of full-text search facilities. However, for legacy text available only in printed form, the provision of these electronic search tools is dependent on the prior electronic capture of digital facsimile images of the printed text, followed by the conversion of these images to electronic text through the process of optical character recognition (OCR). This article describes a project undertaken at the University of Waikato over the period 1999 to 2001 to produce a full-text searchable version of the Niupepa or Maori- language newspaper collection for delivery over the Internet
Use of Wikipedia Categories in Entity Ranking
Wikipedia is a useful source of knowledge that has many applications in
language processing and knowledge representation. The Wikipedia category graph
can be compared with the class hierarchy in an ontology; it has some
characteristics in common as well as some differences. In this paper, we
present our approach for answering entity ranking queries from the Wikipedia.
In particular, we explore how to make use of Wikipedia categories to improve
entity ranking effectiveness. Our experiments show that using categories of
example entities works significantly better than using loosely defined target
categories
BlogForever D2.6: Data Extraction Methodology
This report outlines an inquiry into the area of web data extraction, conducted within the context of blog preservation. The report reviews theoretical advances and practical developments for implementing data extraction. The inquiry is extended through an experiment that demonstrates the effectiveness and feasibility of implementing some of the suggested approaches. More specifically, the report discusses an approach based on unsupervised machine learning that employs the RSS feeds and HTML representations of blogs. It outlines the possibilities of extracting semantics available in blogs and demonstrates the benefits of exploiting available standards such as microformats and microdata. The report proceeds to propose a methodology for extracting and processing blog data to further inform the design and development of the BlogForever platform
Topic modeling for entity linking using keyphrase
This paper proposes an Entity Linking system that applies a topic modeling ranking. We apply a novel approach in order to provide new relevant elements to the model. These elements are keyphrases related to the queries and gathered from a huge Wikipedia-based knowledge resourcePeer ReviewedPostprint (authorâs final draft
Automatic tagging and geotagging in video collections and communities
Automatically generated tags and geotags hold great promise
to improve access to video collections and online communi-
ties. We overview three tasks offered in the MediaEval 2010
benchmarking initiative, for each, describing its use scenario, definition and the data set released. For each task, a reference algorithm is presented that was used within MediaEval 2010 and comments are included on lessons learned. The Tagging Task, Professional involves automatically matching episodes in a collection of Dutch television with subject labels drawn from the keyword thesaurus used by the archive staff. The Tagging Task, Wild Wild Web involves automatically predicting the tags that are assigned by users to their online videos. Finally, the Placing Task requires automatically assigning geo-coordinates to videos. The specification of each task admits the use of the full range of available information including user-generated metadata, speech recognition transcripts, audio, and visual features
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