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1. Exploring Semanticity for Content and Function Word Distinction in Catalan

Author

Neus Català, Jaume Baixeries, and Antoni Hernández-Fernández

Subjects
semanticity, function words, content words, semantic networks, Zipf’s law of meaning, word class, Language and Literature
Abstract

In the realm of linguistics, the concept of “semanticity” was recently introduced as a novel measure designed to study linguistic networks. In a given text, semanticity is defined as the ratio of the potential number of meanings associated with a word to the number of different words with which it is linguistically linked. This concept provides a quantitative indicator that reflects a word’s semantic complexity and its role in a language. In this pilot study, we applied the semanticity measure to the Catalan language, aiming to investigate its effectiveness in automatically distinguishing content words from function words. For this purpose, the measure of semanticity has been applied to a large corpus of texts written in Catalan. We show that the semanticity of words allows us to classify the word classes existing in Catalan in a simple way so that both the semantic and syntactic capacity of each word within a language can be integrated under this parameter. By means of this semanticity measure, it has been observed that adverbs behave like function words in Catalan. This approach offers a quantitative and objective tool for researchers and linguists to gain insights into the structure and dynamics of languages, contributing to a deeper understanding of their underlying principles. The application of semanticity to Catalan is a promising pilot study, with potential applications in other languages, which will allow progress to be made in the field of theoretical linguistics and contribute to the development of automated linguistic tools.

Published
2024
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2. Zipf's laws of meaning in Catalan.

Author

Neus Català, Jaume Baixeries, Ramon Ferrer-I-Cancho, Lluís Padró, and Antoni Hernández-Fernández

Subjects
Medicine, Science
Abstract

In his pioneering research, G. K. Zipf formulated a couple of statistical laws on the relationship between the frequency of a word with its number of meanings: the law of meaning distribution, relating the frequency of a word and its frequency rank, and the meaning-frequency law, relating the frequency of a word with its number of meanings. Although these laws were formulated more than half a century ago, they have been only investigated in a few languages. Here we present the first study of these laws in Catalan. We verify these laws in Catalan via the relationship among their exponents and that of the rank-frequency law. We present a new protocol for the analysis of these Zipfian laws that can be extended to other languages. We report the first evidence of two marked regimes for these laws in written language and speech, paralleling the two regimes in Zipf's rank-frequency law in large multi-author corpora discovered in early 2000s. Finally, the implications of these two regimes will be discussed.

Published
2021
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3. Size of the Whole versus Number of Parts in Genomes

Author

Núria Forns, Ramon Ferrer-i-Cancho, Jaume Baixeries, and Antoni Hernández-Fernández

Subjects
Menzerath-Altmann law, genome size, chromosomes, Science, Astrophysics, QB460-466, Physics, QC1-999
Abstract

It is known that chromosome number tends to decrease as genome size increases in angiosperm plants. Here the relationship between number of parts (the chromosomes) and size of the whole (the genome) is studied for other groups of organisms from different kingdoms. Two major results are obtained. First, the finding of relationships of the kind “the more parts the smaller the whole” as in angiosperms, but also relationships of the kind “the more parts the larger the whole”. Second, these dependencies are not linear in general. The implications of the dependencies between genome size and chromosome number are two-fold. First, they indicate that arguments against the relevance of the finding of negative correlations consistent with Menzerath-Altmann law (a linguistic law that relates the size of the parts with the size of the whole) in genomes are seriously flawed. Second, they unravel the weakness of a recent model of chromosome lengths based upon random breakage that assumes that chromosome number and genome size are independent.

Published
2011
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4. The evolution of the exponent of Zipf's law in language ontogeny.

Author

Jaume Baixeries, Brita Elvevåg, and Ramon Ferrer-i-Cancho

Subjects
Medicine, Science
Abstract

It is well-known that word frequencies arrange themselves according to Zipf's law. However, little is known about the dependency of the parameters of the law and the complexity of a communication system. Many models of the evolution of language assume that the exponent of the law remains constant as the complexity of a communication systems increases. Using longitudinal studies of child language, we analysed the word rank distribution for the speech of children and adults participating in conversations. The adults typically included family members (e.g., parents) or the investigators conducting the research. Our analysis of the evolution of Zipf's law yields two main unexpected results. First, in children the exponent of the law tends to decrease over time while this tendency is weaker in adults, thus suggesting this is not a mere mirror effect of adult speech. Second, although the exponent of the law is more stable in adults, their exponents fall below 1 which is the typical value of the exponent assumed in both children and adults. Our analysis also shows a tendency of the mean length of utterances (MLU), a simple estimate of syntactic complexity, to increase as the exponent decreases. The parallel evolution of the exponent and a simple indicator of syntactic complexity (MLU) supports the hypothesis that the exponent of Zipf's law and linguistic complexity are inter-related. The assumption that Zipf's law for word ranks is a power-law with a constant exponent of one in both adults and children needs to be revised.

Published
2013
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40. Data Analytics and Management in Data Intensive Domains : 25th International Conference, DAMDID/RCDL 2023, Moscow, Russia, October 24–27, 2023, Revised Selected Papers

Author

Jaume Baixeries, Dmitry I. Ignatov, Sergei O. Kuznetsov, Sergey Stupnikov, Jaume Baixeries, Dmitry I. Ignatov, Sergei O. Kuznetsov, and Sergey Stupnikov

Subjects
Data mining, Artificial intelligence, Application software, Social sciences—Data processing, Image processing—Digital techniques, Computer vision, Software engineering
Abstract

This book constitutes the post-conference proceedings of the 25th International Conference on Data Analytics and Management in Data Intensive Domains, DAMDID/RCDL 2023, held in Moscow, Russia, during 24-27 October 2023. The 21 papers presented here were carefully reviewed and selected from 75 submissions. These papers are organized in the following topical sections: Data Models and Knowledge Graphs; Databases in Data Intensive Domains; Machine learning methods and applications; Data Analysis in Astronomy & Information extraction from text. Papers from keynote talks have also been included in this book.

Published
2024

43. Sampling Representation Contexts with Attribute Exploration

Author

Amedeo Napoli, Mehdi Kaytoue, Jaume Baixeries, Victor Codocedo, Universidad Tecnica Federico Santa Maria Santiago de Chile (UTFSM), Universitat Politècnica de Catalunya [Barcelona] (UPC), Data Mining and Machine Learning (DM2L), Laboratoire d'InfoRmatique en Image et Systèmes d'information (LIRIS), Université Lumière - Lyon 2 (UL2)-École Centrale de Lyon (ECL), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Lumière - Lyon 2 (UL2)-École Centrale de Lyon (ECL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA), Infologic, Knowledge representation, reasonning (ORPAILLEUR), Inria Nancy - Grand Est, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Department of Natural Language Processing & Knowledge Discovery (LORIA - NLPKD), Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), Diana Cristea, Florence Le Ber, Baris Sertkaya, Institut National des Sciences Appliquées de Lyon (INSA Lyon), Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-École Centrale de Lyon (ECL), Université de Lyon-Université Lumière - Lyon 2 (UL2)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Université Lumière - Lyon 2 (UL2), Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL), Universidad Tecnica Federico Santa Maria [Valparaiso] (UTFSM), Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Université Lumière - Lyon 2 (UL2)-École Centrale de Lyon (ECL), and Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)

Subjects
Structure (mathematical logic), Theoretical computer science, Computer science, Representation (systemics), Sampling (statistics), Context (language use), 0102 computer and information sciences, 02 engineering and technology, Interval (mathematics), 01 natural sciences, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI], Naive algorithm, 010201 computation theory & mathematics, 0202 electrical engineering, electronic engineering, information engineering, 020201 artificial intelligence & image processing
Abstract

International audience; We tackle the problem of constructing the representation context of a pattern structure. First, we present a naive algorithm that computes the representation context of a pattern structure. Then, we add a sampling technique in order to reduce the size of the output. We show that these techniques reduce significantly the size of the representation context for interval pattern structures.

Published
2019
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44. The polysemy of the words that children learn over time

Author

Jaume Baixeries, Bernardino Casas, Neus Català, Antoni Hernández-Fernández, Ramon Ferrer-i-Cancho, Universitat Politècnica de Catalunya. Departament de Ciències de la Computació, Universitat Politècnica de Catalunya. Institut de Ciències de l'Educació, Universitat Politècnica de Catalunya. LARCA - Laboratori d'Algorísmia Relacional, Complexitat i Aprenentatge, and Universitat Politècnica de Catalunya. GPLN - Grup de Processament del Llenguatge Natural

Subjects
FOS: Computer and information sciences, Linguistics and Language, Vocabulary, Physics - Physics and Society, Computer science, Children--Language, media_common.quotation_subject, FOS: Physical sciences, Verb, Physics and Society (physics.soc-ph), 050105 experimental psychology, Language and Linguistics, 03 medical and health sciences, 0302 clinical medicine, Learning biases, Informàtica::Aplicacions de la informàtica [Àrees temàtiques de la UPC], Noun, 0501 psychology and cognitive sciences, CHILDES, Polysemy, media_common, Llenguatge i llengües -- Adquisició, Computer Science - Computation and Language, Lingüística, Communication, 05 social sciences, Quantitative linguistics, Ensenyament i aprenentatge::Aprenentatge de llengües [Àrees temàtiques de la UPC], Linguistics, Adverb, Language acquisition, Child language evolution, Preference, Infants -- Llenguatge, Lingüistica, Semantics, Human-Computer Interaction, Semàntica, Syntactic category, Children -- Language, Animal Science and Zoology, Vocabulary learning, Computation and Language (cs.CL), Adjective, 030217 neurology & neurosurgery
Abstract

Here we study polysemy as a potential learning bias in vocabulary learning in children. Words of low polysemy could be preferred as they reduce the disambiguation effort for the listener. However, such preference could be a side-effect of another bias: the preference of children for nouns in combination with the lower polysemy of nouns with respect to other part-of-speech categories. Our results show that mean polysemy in children increases over time in two phases, i.e. a fast growth till the 31st month followed by a slower tendency towards adult speech. In contrast, this evolution is not found in adults interacting with children. This suggests that children have a preference for non-polysemous words in their early stages of vocabulary acquisition. Interestingly, the evolutionary pattern described above weakens when controlling for syntactic category (noun, verb, adjective or adverb) but it does not disappear completely, suggesting that it could result from acombination of a standalone bias for low polysemy and a preference for nouns., Substantially revised version based on referee comments from Interaction Studies

Published
2018

45. Characterizing approximate-matching dependencies in formal concept analysis with pattern structures

Author

Amedeo Napoli, Mehdi Kaytoue, Victor Codocedo, Jaume Baixeries, Universitat Politècnica de Catalunya. Departament de Ciències de la Computació, Universitat Politècnica de Catalunya. LARCA - Laboratori d'Algorísmia Relacional, Complexitat i Aprenentatge, Universitat Politècnica de Catalunya [Barcelona] (UPC), Inria Chile, Universidad de Valparaiso [Chile]-Universidad Tecnica Federico Santa Maria [Valparaiso] (UTFSM)-Universidad Adolfo Ibáñez [Santiago]-Pontificia Universidad Católica de Valparaíso (PUCV)-Institut National de Recherche en Informatique et en Automatique (Inria)-Pontificia Universidad Católica de Chile (UC)-Universidad de Concepción [Chile]-Universidad de la frontera [Chile]-Universidad Diego Portales [Santiago] (UDP), Data Mining and Machine Learning (DM2L), Laboratoire d'InfoRmatique en Image et Systèmes d'information (LIRIS), Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-École Centrale de Lyon (ECL), Université de Lyon-Université Lumière - Lyon 2 (UL2)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Université Lumière - Lyon 2 (UL2), Infologic, Knowledge representation, reasonning (ORPAILLEUR), Inria Nancy - Grand Est, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Department of Natural Language Processing & Knowledge Discovery (LORIA - NLPKD), Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL), Universidad Diego Portales [Santiago] (UDP)-Universidad de la frontera [Chile]-Universidad de Concepción [Chile]-Pontificia Universidad Católica de Chile (UC)-Institut National de Recherche en Informatique et en Automatique (Inria)-Pontificia Universidad Católica de Valparaíso (PUCV)-Universidad Adolfo Ibáñez [Santiago]-Universidad de Valparaiso [Chile]-Universidad Tecnica Federico Santa Maria [Valparaiso] (UTFSM), Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), Universidad Diego Portales [Santiago] (UDP)-Universidad de la frontera [Chile]-Pontificia Universidad Católica de Chile (UC)-Institut National de Recherche en Informatique et en Automatique (Inria)-Pontificia Universidad Católica de Valparaíso (PUCV)-Universidad Adolfo Ibáñez [Santiago]-Universidad de Valparaiso [Chile]-Universidad Tecnica Federico Santa Maria [Valparaiso] (UTFSM)-Universidad de Concepción - University of Concepcion [Chile], Université Lumière - Lyon 2 (UL2)-École Centrale de Lyon (ECL), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Université Lumière - Lyon 2 (UL2)-École Centrale de Lyon (ECL), and Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)

Subjects
Theoretical computer science, Informàtica::Sistemes d'informació::Bases de dades [Àrees temàtiques de la UPC], Data Dependencies, 02 engineering and technology, Formal Concept Analysis (FCA), Estructures de dades (Informàtica), [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI], Bases de dades, Database management, [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG], Knowledge extraction, 020204 information systems, Lattice (order), Informàtica, 0202 electrical engineering, electronic engineering, information engineering, Formal concept analysis, Discrete Mathematics and Combinatorics, Data partitioning, Informàtica::Arquitectura de computadors [Àrees temàtiques de la UPC], Mathematics, Computational intelligence, Formal methods (Computer science), [INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB], Applied Mathematics, Pattern Structures, Knowledge Discovery, Computer science, [INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR], Data quality, Informació, Teoria de la, Approximate matching, 020201 artificial intelligence & image processing, Tuple, Functional dependency
Abstract

International audience; Functional dependencies (FDs) provide valuable knowledge on the relations between the attributes of a data table. A functional dependency holds when the values of an attribute can be determined by another. It is shown that FDs can be expressed in terms of partitions of tuples that are in agreement w.r.t. the values taken by some subsets of attributes. To extend the use of FDs, several generalizations are proposed. In this work, we study approximate-matching dependencies that generalize FDs by relaxing the constraints on the attributes, i.e. agreement is based on a similarity relation rather than on equality. Such dependencies are attracting attention in the database field since they allow to uncrisp the basic notion of FDs, and can be applied in many different fields, e.g. data quality, data mining, behavior analysis, data cleaning or data partition... Here we show that these dependencies can be formalized in the framework of Formal Concept Analysis (FCA). Such a formalization was previously introduced for basic FDs, but needs to be adapted and extended for approximate-matching dependencies. Our new result states that, starting from the conceptual structure of a pattern structure and generalizing the notion of relation between tuples, approximate-matching dependencies can be characterized as implications in a pattern concept lattice. We finally show how to adapt basic FCA algorithms to construct a pattern concept lattice that entails these dependencies after a slight and tractable transformation of the original data.

Published
2018
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46. Formal Concept Analysis : 13th International Conference, ICFCA 2015, Nerja, Spain, June 23-26, 2015, Proceedings

Author

Jaume Baixeries, Christian Sacarea, Manuel Ojeda-Aciego, Jaume Baixeries, Christian Sacarea, and Manuel Ojeda-Aciego

Subjects
Artificial intelligence, Software engineering, Data mining, Machine theory, Computer science—Mathematics, Discrete mathematics, Algebra
Abstract

This book constitutes the refereed proceedings of the 13th International Conference on Formal Concept Analysis, ICFCA 2015, held in Neja, Spain, in June 2015. The 16 revised full papers presented were carefully reviewed and selected from 38 submissions. The topics in this volume cover theoretical aspects of FCA; methods and applications of FCA to different fields and enhanced FCA that show new trends in FCA, for instance, pattern structures of fuzzy FCA.

Published
2015

47. Pattern Structures and Concept Lattices for Data Mining and Knowledge Processing

Author

Aleksey Buzmakov, Jaume Baixeries, Sergei O. Kuznetsov, Amedeo Napoli, Mehdi Kaytoue, Victor Codocedo, Data Mining and Machine Learning (DM2L), Laboratoire d'InfoRmatique en Image et Systèmes d'information (LIRIS), Université Lumière - Lyon 2 (UL2)-École Centrale de Lyon (ECL), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Université Lumière - Lyon 2 (UL2)-École Centrale de Lyon (ECL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS), Knowledge representation, reasonning (ORPAILLEUR), Inria Nancy - Grand Est, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Department of Natural Language Processing & Knowledge Discovery (LORIA - NLPKD), Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), Universitat Politècnica de Catalunya [Barcelona] (UPC), Department of Applied Mathematics - State University Higher School of Economics, State University Higher School of Economics, Bifet, Albert and May, Michael and Zadrozny, Bianca and Gavalda, Ricard and Pedreschi, Dino and Bonchi, Francesco and Cardoso, Jaime and Spiliopoulou, Myra, Universitat Politècnica de Catalunya. Departament de Ciències de la Computació, Universitat Politècnica de Catalunya. LARCA - Laboratori d'Algorísmia Relacional, Complexitat i Aprenentatge, Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-École Centrale de Lyon (ECL), Université de Lyon-Université Lumière - Lyon 2 (UL2)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Université Lumière - Lyon 2 (UL2), Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL), and Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL)

Subjects
Complex data type, Artificial intelligence, Information retrieval, Computer science, Intel·ligència artificial, Knowledge processing, computer.software_genre, Data science, Local pattern, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI], Information fusion, Informació -- Sistemes d'emmagatzematge i recuperació, Informàtica::Sistemes d'informació::Emmagatzematge i recuperació de la informació [Àrees temàtiques de la UPC], Formal concept analysis, Informàtica::Intel·ligència artificial [Àrees temàtiques de la UPC], Data mining, Management information systems, Knowledge Discovery. Data Mining. Formal Concept Analysis, Mineria de dades, Functional dependency, computer
Abstract

International audience; This article aims at presenting recent advances in Formal Concept Analysis (2010-2015), especially when the question is dealing with complex data (numbers, graphs, sequences, etc.) in domains such as databases (functional dependencies), data-mining (local pattern discovery), information retrieval and information fusion. As these advances are mainly published in artificial intelligence and FCA dedicated venues, a dissemination towards data mining and machine learning is worthwhile.

Published
2015
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48. Characterization of database dependencies with FCA and pattern structures

Author

Mehdi Kaytoue, Amedeo Napoli, Jaume Baixeries, Universitat Politècnica de Catalunya. Departament de Ciències de la Computació, Universitat Politècnica de Catalunya. LARCA - Laboratori d'Algorísmia Relacional, Complexitat i Aprenentatge, Departament de Llenguatges i Sistemes Informatics, Llenguatges i Sistemes Informàtics (LSI), Universitat Politècnica de Catalunya [Barcelona] (UPC)-Universitat Politècnica de Catalunya [Barcelona] (UPC), Data Mining and Machine Learning (DM2L), Laboratoire d'InfoRmatique en Image et Systèmes d'information (LIRIS), Université Lumière - Lyon 2 (UL2)-École Centrale de Lyon (ECL), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Université Lumière - Lyon 2 (UL2)-École Centrale de Lyon (ECL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS), Knowledge representation, reasonning (ORPAILLEUR), Inria Nancy - Grand Est, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Department of Natural Language Processing & Knowledge Discovery (LORIA - NLPKD), Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-École Centrale de Lyon (ECL), Université de Lyon-Université Lumière - Lyon 2 (UL2)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Université Lumière - Lyon 2 (UL2), Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL), and Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL)

Subjects
Artificial intelligence, Theoretical computer science, Computer science, pattern structures, data analysis, Informàtica::Sistemes d'informació::Bases de dades [Àrees temàtiques de la UPC], 0102 computer and information sciences, 02 engineering and technology, computer.software_genre, 01 natural sciences, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI], formal concept analysis, 0202 electrical engineering, electronic engineering, information engineering, Formal concept analysis, data dependencies, Attribute implications, Relational databases, Database, Intel·ligència artificial, Bases de dades relacionals, Formalism (philosophy of mathematics), 010201 computation theory & mathematics, 020201 artificial intelligence & image processing, Informàtica::Intel·ligència artificial [Àrees temàtiques de la UPC], Functional dependency, computer
Abstract

In this review paper, we present some recent results on the characterization of Functional Dependencies and variations with the formalism of Pattern Structures and Formal Concept Analysis. Although these dependencies have been paramount in database theory, they have been used in different fields: artificial intelligence and knowledge discovery, among others.

Published
2014
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49. When is Menzerath-Altmann law mathematically trivial? A new approach

Author

Łukasz Dębowski, Antoni Hernández-Fernández, Ramon Ferrer-i-Cancho, Ján Mačutek, Jaume Baixeries, Universitat Politècnica de Catalunya. Departament de Ciències de la Computació, Universitat Politècnica de Catalunya. Institut de Ciències de l'Educació, and Universitat Politècnica de Catalunya. LARCA - Laboratori d'Algorísmia Relacional, Complexitat i Aprenentatge

Subjects
Statistics and Probability, Montecarlo, Mètode de, FOS: Physical sciences, Power law, Quantitative Biology - Quantitative Methods, Power-laws, Genetics, Quantitative Biology - Genomics, Taxonomic rank, Genomes, Molecular Biology, Scaling, Quantitative Methods (q-bio.QM), Mathematics, Parametric statistics, Genomics (q-bio.GN), Menzerath-Altmann law, Models, Statistical, Group (mathematics), Uniformly most powerful test, Probability and statistics, Correlation ratio, Monte Carlo method, Computational Mathematics, Matemàtiques i estadística::Estadística matemàtica [Àrees temàtiques de la UPC], Law, Physics - Data Analysis, Statistics and Probability, FOS: Biological sciences, Algorithms, Data Analysis, Statistics and Probability (physics.data-an)
Abstract

Menzerath's law, the tendency of Z, the mean size of the parts, to decrease as X, the number of parts, increases is found in language, music and genomes. Recently, it has been argued that the presence of the law in genomes is an inevitable consequence of the fact that Z = Y/X, which would imply that Z scales with X as Z ~ 1/X. That scaling is a very particular case of Menzerath-Altmann law that has been rejected by means of a correlation test between X and Y in genomes, being X the number of chromosomes of a species, Y its genome size in bases and Z the mean chromosome size. Here we review the statistical foundations of that test and consider three non-parametric tests based upon different correlation metrics and one parametric test to evaluate if Z ~ 1/X in genomes. The most powerful test is a new non-parametric based upon the correlation ratio, which is able to reject Z ~ 1/X in nine out of eleven taxonomic groups and detect a borderline group. Rather than a fact, Z ~ 1/X is a baseline that real genomes do not meet. The view of Menzerath-Altmann law as inevitable is seriously flawed., Comment: version improved with a new table, new histograms and a more accurate statistical analysis; a new interpetation of the results is offered; notation has undergone minor corrections

Published
2014

50. The evolution of polysemy in child language

Author

Jaume Baixeries i Juvillà, Ramon Ferrer Cancho, Neus Catala Roig, Bernardino Casas Fernández, Universitat Politècnica de Catalunya. Departament de Llenguatges i Sistemes Informàtics, Universitat Politècnica de Catalunya. LARCA - Laboratori d'Algorísmia Relacional, Complexitat i Aprenentatge, and Universitat Politècnica de Catalunya. GPLN - Grup de Processament del Llenguatge Natural

Subjects
Universal Networking Language, Informàtica::Aplicacions de la informàtica [Àrees temàtiques de la UPC], Sociology of language, Adquisició del llenguatge, Computer science, Comprehension approach, Language education, Language acquisition, Polysemy, Linguistics, Infants -- Llenguatge
Abstract

BERNARDINO CASAS, NEUS CATALA, RAMON FERRER-I-CANCHO, JAUME BAIXERIES Complexity and Quantitative Linguistics Lab. LARCA Research Group. Departament de Llenguatges i Sistemes Informatics. Universitat Politecnica de Catalunya. Campus Nord, Edifici Omega, Jordi Girona Salgado 1–3. Barcelona 08034, Catalonia. 2 Complexity and Quantitative Linguistics Lab. TALP Research Center. Departament de Llenguatges i Sistemes Informatics. Universitat Politecnica de Catalunya. Campus Nord, Edifici Omega, Jordi Girona Salgado 1–3. Barcelona 08034, Catalonia.

Published
2014

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