1,720,985 research outputs found
NERD: A Framework for Unifying Named Entity Recognition and Disambiguation Extraction Tools
No full textNamed Entity Extraction is a mature task in the NLP field that has yielded numerous services gaining popularity in the Semantic Web community for extracting knowledge from web documents. These services
are generally organized as pipelines, using dedicated APIs and different taxonomy for extracting, classifying and disambiguating named entities. Integrating one of these services in a particular application requires
to implement an appropriate driver. Furthermore, the results of these services are not comparable due to different formats. This prevents the comparison of the performance of these services as well as their pos-
sible combination. We address this problem by proposing NERD, a framework which unifies 10 popular named entity extractors available on the web, and the NERD ontology which provides a rich set of axioms aligning the taxonomies of these tools
Translational Models for Item Recommendation
No full textTranslational models have proven to be accurate and efficient at learning entity and relation representations from knowledge graphs for machine learning tasks such as knowledge graph completion. In the past years, knowledge graphs have shown to be beneficial for recommender systems, efficiently addressing paramount issues such as new items and data sparsity. In this paper, we show that the item recommendation problem can be seen as a specific case of knowledge graph completion problem, where the “feedback” property, which connects users to items that they like, has to be predicted. We empirically compare a set of state-of-the-art knowledge graph embeddings algorithms on the task of item recommendation on the Movielens 1M and on the LibraryThing dataset. The results show that translational models outperform typical baseline approaches based on collaborative filtering and popularity and that the dimension of the embedding vector influences the accuracy of the recommendations
MeMAD multimodal image caption translation model
No full textA multimodal image caption translation model from the paper
Stig-Arne Grönroos, Benoit Huet, Mikko Kurimo, Jorma Laaksonen, Bernard Merialdo, Phu Pham, Mats Sjöberg, Umut Sulubacak, Jörg Tiedemann, Raphael Troncy, and Raúl Vázquez. The MeMAD submission to the WMT18 multimodal translation task. In Proceedings of the Third Conference on Machine Translation. Association for Computational Linguistics, October 2018 [ACL anthology
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
LegalHTML: a representation language for legal acts
No full textThe Publications Office (OP) of European Union (EU) expressed the need to simplify the Official Journal production workflow, which required different formats and, consequently, document instances at different stages of the process. We met this need by developing LegalHTML, which unifies the formal, structural and semantic representation of legal acts, as well allowing for diverse typographic requirements for publication. This streamlines the production workflow and publication/fruition of content as well, since a single document instance is first drafted and then incrementally enriched. LegalHTML consists of an extension of HTML for the structural representation of legal acts (e.g., articles, paragraphs, items, and references), while a supplementary ontology enables the annotation (using RDFa) of domain references (e.g., signatories, people and their role in organizations, the scope of the document). LegalHTML also supports the consolidation of an act and its subsequent changes into a single document using a tree-based representation. Finally, we implemented a CSS stylesheet for the default rendering of the model and a JavaScript file imbuing documents with an API that supports TOC generation, footnote cross-references and point-in-time visualization of legal acts
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