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Cover image for Flexible Query Answering Systems 15th International Conference, FQAS 2023, Mallorca, Spain, September 5-7, 2023, Proceedings
Title:
Flexible Query Answering Systems 15th International Conference, FQAS 2023, Mallorca, Spain, September 5-7, 2023, Proceedings
Author:
Larsen, Henrik Legind. editor.
ISBN:
9783031429354
Edition:
1st ed. 2023.
Physical Description:
XXI, 306 p. 94 illus., 51 illus. in color. online resource.
Series:
Lecture Notes in Artificial Intelligence, 14113
Contents:
Flexible Queries over Semantic Systems -- On Reducing Reasoning and Querying in Natural Logic to Database Querying -- Diversifying top-k Answers in a Query by Example Setting -- Flexible Classification, Question-Answering and Retrieval with Siamese -- Neural Networks for Biomedical Texts -- The promise of Query Answering systems in Sexuality: current state, challenges and limitations -- Some Properties of the Left Recursive Form of the Convex Combination Linguistic Aggregator -- Knowledge Graph Enabled Open-Domain Conversational Question Answering -- Advanced methods and applications in Natural Language Processing (NLP) -- Automatic generation of coherent natural language texts -- Interlingual Semantic Validation -- How tasty is this dish? Studying user-recipe interactions with a rating prediction algorithm and Graph Neural Networks -- "Let it BEE": Natural Language Classification of arthropod specimens based on their Spanish description -- New advances in disinformation detection Bot Detection in Twitter: An overview -- A fuzzy approach to detecting suspected disinformtion in videos -- All trolls have one mission: An entropy analysis of political misinformation spreaders -- A First Evolutionary Fuzzy Approach for Change Mining with Smart Bands -- Federated learning in healthcare with unsupervised and semi-supervised methods -- Exploring hidden anomalies in UGR'16 with Kitsune -- An Orthographic Similarity Measure for Graph-based Text Representations -- Applying AI to Social Science and Social Science to AI -- An unsupervised approach to extracting knowledge from the relationships between blame attribution on Twitter -- "Health is the real wealth": Unsupervised approach to improve explainability in health-based recommendation systems -- Are textual recommendations enough? Guiding physicians toward the design of machine learning pipelines through a visual platform -- Who is to blame? Responsibility attribution in AI systems vs human agents -- Artificial intelligence law and regulationMethodology for analyzing the risk of algorithmic discrimination from a legal and technical point of view -- Data as wealth, data markets and its regulation -- ADM in the European Union: An interoperable solution.-.
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