Flexible Query Answering Systems 15th International Conference, FQAS 2023, Mallorca, Spain, September 5-7, 2023, Proceedings
by
 
Larsen, Henrik Legind. editor.

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.-.

Added Author
Larsen, Henrik Legind.
 
Martin-Bautista, Maria J.
 
Ruiz, M. Dolores.
 
Andreasen, Troels.
 
Bordogna, Gloria.
 
De Tré, Guy.

Added Corporate Author
SpringerLink (Online service)

Electronic Access
https://doi.org/10.1007/978-3-031-42935-4


LibraryMaterial TypeItem BarcodeShelf Number[[missing key: search.ChildField.HOLDING]]Status
Online LibraryE-Book521126-1001XX(521126.1)Elektronik Kütüphane