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Computer Science

D-Index
35
Citations
7840
World Ranking
11489
National Ranking
377

Overview

Pasquale Lops is affiliated with the University of Bari Aldo Moro in Italy and specializes in computer science with a focus on artificial intelligence and information systems. Their research spans several subfields including communication, management science and operations research, and computer vision and pattern recognition.

The scientist's work covers a range of topics in computer science, with notable emphasis on:

  • Topic Modeling
  • Recommender Systems and Techniques
  • Natural Language Processing Techniques
  • Wikis in Education and Collaboration
  • Advanced Graph Neural Networks
  • Sentiment Analysis and Opinion Mining
  • Technology Use by Older Adults

Pasquale Lops has contributed to publications in various venues, with frequent appearances in:

  • Zenodo (CERN European Organization for Nuclear Research)
  • User Modeling and User-Adapted Interaction
  • Journal of Intelligent Information Systems
  • Information Systems
  • OPAL (Open@LaTrobe) (La Trobe University)

Their recent papers include:

  • "Generating post hoc review-based natural language justifications for recommender systems" (2020), published in User Modeling and User-Adapted Interaction
  • "Context-aware graph-based recommendations exploiting Personalized PageRank" (2021), published in Knowledge-Based Systems
  • "AI-based decision support system for public procurement" (2023), published in Information Systems
  • "Myrror: a platform for holistic user modeling" (2020), published in User Modeling and User-Adapted Interaction
  • "ClayRS: An end-to-end framework for reproducible knowledge-aware recommender systems" (2023), published in Information Systems

Throughout their career, Pasquale Lops has frequently collaborated with several coauthors including:

  • Giovanni Semeraro
  • Pierpaolo Basile
  • Marco de Gemmis
  • Lucia Siciliani
  • Cataldo Musto

Best Publications

  • Content-based Recommender Systems: State of the Art and Trends

    Pasquale Lops;Marco de Gemmis;Giovanni Semeraro

  • Semantics-Aware Content-Based Recommender Systems

    Marco de Gemmis;Pasquale Lops;Cataldo Musto;Fedelucio Narducci

  • A content-collaborative recommender that exploits WordNet-based user profiles for neighborhood formation

    Marco Degemmis;Pasquale Lops;Giovanni Semeraro

  • Introducing Serendipity in a Content-Based Recommender System

    L. Iaquinta;M. de Gemmis;P. Lops;G. Semeraro

  • Integrating tags in a semantic content-based recommender

    Marco de Gemmis;Pasquale Lops;Giovanni Semeraro;Pierpaolo Basile

  • Trends in Content-based Recommendation: Preface to the Special Issue on Recommender Systems based on Rich Item Descriptions

    Pasquale Lops;Dietmar Jannach;Cataldo Musto;Toine Bogers

  • An investigation on the serendipity problem in recommender systems

    Marco de Gemmis;Pasquale Lops;Giovanni Semeraro;Cataldo Musto

  • Learning Word Embeddings from Wikipedia for Content-Based Recommender Systems

    Cataldo Musto;Giovanni Semeraro;Marco de Gemmis;Pasquale Lops

  • Human Decision Making and Recommender Systems

    Li Chen;Marco de Gemmis;Alexander Felfernig;Pasquale Lops

  • Ontologically-Enriched unified user modeling for cross-system personalization

    Bhaskar Mehta;Claudia Niederee;Avare Stewart;Marco Degemmis

  • Combining learning and word sense disambiguation for intelligent user profiling

    Giovanni Semeraro;Marco Degemmis;Pasquale Lops;Pierpaolo Basile

  • Personalized finance advisory through case-based recommender systems and diversification strategies

    Cataldo Musto;Giovanni Semeraro;Pasquale Lops;Marco de Gemmis

  • A Multi-criteria Recommender System Exploiting Aspect-based Sentiment Analysis of Users' Reviews

    Cataldo Musto;Marco de Gemmis;Giovanni Semeraro;Pasquale Lops

  • ExpLOD: A Framework for Explaining Recommendations based on the Linked Open Data Cloud

    Cataldo Musto;Fedelucio Narducci;Pasquale Lops;Marco De Gemmis

  • Knowledge infusion into content-based recommender systems

    Giovanni Semeraro;Pasquale Lops;Pierpaolo Basile;Marco de Gemmis

  • Content-based and collaborative techniques for tag recommendation: an empirical evaluation

    Pasquale Lops;Marco De Gemmis;Giovanni Semeraro;Cataldo Musto

  • Introducing linked open data in graph-based recommender systems

    Cataldo Musto;Pierpaolo Basile;Pasquale Lops;Marco de Gemmis

  • Linked open data-based explanations for transparent recommender systems

    Cataldo Musto;Fedelucio Narducci;Pasquale Lops;Marco de Gemmis

  • Word Embedding techniques for Content-based Recommender Systems: An empirical evaluation

    Cataldo Musto;Giovanni Semeraro;Marco de Gemmis;Pasquale Lops

  • Human decision making and recommender systems

    Anthony Jameson;MC Martijn Willemsen;Alexander Felfernig;Marco de Gemmis

Frequent Co-Authors

Giovanni Semeraro
Giovanni Semeraro University of Bari Aldo Moro
Marco de Gemmis
Marco de Gemmis University of Bari Aldo Moro
Alexander Felfernig
Alexander Felfernig Graz University of Technology
Peter Brusilovsky
Peter Brusilovsky University of Pittsburgh
Francesco Ricci
Francesco Ricci Free University of Bozen-Bolzano
Tommaso Di Noia
Tommaso Di Noia Polytechnic University of Bari
Floriana Esposito
Floriana Esposito University of Bari Aldo Moro
Li Chen
Li Chen Hong Kong Baptist University
Thomas Lukasiewicz
Thomas Lukasiewicz University of Oxford
Barbara Pernici
Barbara Pernici Polytechnic University of Milan

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