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  • SOBA: Semi-automated Ontology Builder for Aspect-based sentiment analysis
    J. Web Semant. (IF 2.429) Pub Date : 2019-12-11
    Lisa Zhuang; Kim Schouten; Flavius Frasincar

    This research explores the possibility of improving knowledge-driven aspect-based sentiment analysis (ABSA) in terms of efficiency and effectiveness. This is done by implementing a Semi-automated Ontology Builder for Aspect-based sentiment analysis (SOBA). Semi-automatization of the ontology building process could produce more extensive ontologies, whilst shortening the building time. Furthermore,

    更新日期:2020-03-20
  • Large-scale relation extraction from web documents and knowledge graphs with human-in-the-loop
    J. Web Semant. (IF 2.429) Pub Date : 2019-12-30
    Petar Ristoski; Anna Lisa Gentile; Alfredo Alba; Daniel Gruhl; Steven Welch

    The Semantic Web movement has produced a wealth of curated collections of entities and facts, often referred as Knowledge Graphs. Creating and maintaining such Knowledge Graphs is far from being a solved problem: it is crucial to constantly extract new information from the vast amount of heterogeneous sources of data on the Web. In this work we address the task of Knowledge Graph population. Specifically

    更新日期:2020-03-20
  • The Internet of Musical Things Ontology
    J. Web Semant. (IF 2.429) Pub Date : 2020-01-22
    Luca Turchet; Francesco Antoniazzi; Fabio Viola; Fausto Giunchiglia; György Fazekas

    The Internet of Musical Things (IoMusT) is an emerging research area consisting of the extension of the Internet of Things paradigm to the music domain. Interoperability represents a central issue within this domain, where heterogeneous objects dedicated to the production and/or reception of musical content (Musical Things) are envisioned to communicate between each other. This paper proposes an ontology

    更新日期:2020-03-20
  • Relaxing relationship queries on graph data
    J. Web Semant. (IF 2.429) Pub Date : 2020-03-03
    Shuxin Li; Gong Cheng; Chengkai Li

    In many domains we have witnessed the need to search a large entity-relation graph for direct and indirect relationships between a set of entities specified in a query. A search result, called a semantic association (SA), is typically a compact (e.g., diameter-constrained) connected subgraph containing all the query entities. For this problem of SA search, efficient algorithms exist but will return

    更新日期:2020-03-20
  • Curriculum learning for distant supervision relation extraction
    J. Web Semant. (IF 2.429) Pub Date : 2020-02-29
    Qiongxin Liu; Peng Wang; Jiasheng Wang; Jing Ma

    Relation extraction under distant supervision leverages the existing knowledge base to label data automatically, thus greatly reduced the consumption of human labors. Although distant supervision is an efficient method to obtain a large amount of labeled data, the training dataset labeled by distant supervision suffers from noise problem resulting in poor generalization ability of the relation extractor

    更新日期:2020-03-20
  • DABGEO: A reusable and usable global energy ontology for the energy domain
    J. Web Semant. (IF 2.429) Pub Date : 2020-02-05
    Javier Cuenca; Felix Larrinaga; Edward Curry

    The heterogeneity of energy ontologies hinders the interoperability between ontology-based energy management applications to perform a large-scale energy management. Thus, there is the need for a global ontology that provides common vocabularies to represent the energy subdomains. A global energy ontology must provide a balance of reusability–usability to moderate the effort required to reuse it in

    更新日期:2020-03-20
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