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  1. No Access

    Chapter and Conference Paper

    Sarcastic RoBERTa: A RoBERTa-Based Deep Neural Network Detecting Sarcasm on Twitter

    Sarcastic RoBERTa is an approach to recognizing sarcastic tweets written in English. It is based on a pre-trained RoBERTa model supported by a 3-layer feed-forward fully-connected neural network. It establishe...

    Maciej Hercog, Piotr Jaroński, Jan Kolanowski… in Big Data Analytics and Knowledge Discovery (2022)

  2. No Access

    Chapter and Conference Paper

    Quality Versus Speed in Energy Demand Prediction

    Effective heat energy demand prediction is essential in combined heat power systems. The algorithms considered so far do not sufficiently take into account the computational costs and ease of implementation in...

    Witold Andrzejewski, Jędrzej Potoniec… in Database and Expert Systems Applications (2022)

  3. Chapter and Conference Paper

    Finding Unexplainable Triples in an RDF Graph

    We consider how to select a subgraph of an RDF graph in an ontology learning problem in order to avoid learning redundant axioms. We propose to address this by selecting RDF triples that can not be inferred us...

    Jedrzej Potoniec in The Semantic Web: ESWC 2018 Satellite Events (2018)

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  4. No Access

    Chapter and Conference Paper

    Towards Mining Patterns for Exploratory Search with Keval Algorithm

    For a given set of URIs, finding their common graph patterns may provide useful knowledge. We present an algorithm searching for the best patterns while trying to extend the set of relevant URIs. It involves i...

    Tomasz Sosnowski, Jedrzej Potoniec in Knowledge Engineering and Knowledge Management (2017)

  5. No Access

    Chapter and Conference Paper

    Swift Linked Data Miner Extension for WebProtégé

    Swift Linked Data Miner (SLDM) is a data mining algorithm capable to infer new knowledge and thus extend an ontology by mining a Linked Data dataset. We present an extension to WebProtégé providing SLDM ...

    Tomasz Sosnowski, Jedrzej Potoniec… in Knowledge Engineering and Knowledge Manage… (2017)

  6. No Access

    Chapter and Conference Paper

    Towards Ontology Refinement by Combination of Machine Learning and Attribute Exploration

    We propose a new method for knowledge acquisition and ontology refinement for the Semantic Web. The method is based on a combination of the attribute exploration algorithm from the formal concept analysis and ...

    Jedrzej Potoniec in Knowledge Engineering and Knowledge Management (2015)

  7. No Access

    Chapter and Conference Paper

    Hypothesis-Driven Interactive Classification Based on AVO

    We consider a classification process, that the representation precision of new examples is interactively increased. We use an attribute value ontology (AVO) to represent examples at different levels of abstrac...

    Tomasz Łukaszewski, Jedrzej Potoniec, Szymon Wilk in Man-Machine Interactions 3 (2014)

  8. No Access

    Chapter and Conference Paper

    ASPARAGUS - A System for Automatic SPARQL Query Results Aggregation Using Semantics

    We present a prototype system, named ASPARAGUS, that performs aggregation of SPARQL query results on a semantic baseline, that is by an exploitation of the background ontology expressing the semantics of the r...

    Agnieszka Ławrynowicz, Jedrzej Potoniec… in Computational Collective Intelligence. Tec… (2011)

  9. No Access

    Chapter and Conference Paper

    Fr-ONT: An Algorithm for Frequent Concept Mining with Formal Ontologies

    The paper introduces a task of frequent concept mining: mining frequent patterns of the form of (complex) concepts expressed in description logic. We devise an algorithm for mining frequent patterns expressed ...

    Agnieszka Ławrynowicz, Jedrzej Potoniec in Foundations of Intelligent Systems (2011)