The problem of inducing, learning or inferring grammars has been studied for decades, but only in recent years has grammatical inference emerged as an independent field with connections to many scientific disciplines, including bio-informatics, computational linguistics and pattern recognition. This book meets the need for a comprehensive and unified summary of the basic techniques and results, suitable for researchers working in these various areas. In Part I, the objects of use for grammatical inference are studied in detail: strings and their topology, automata and grammars, whether probabilistic or not. Part II carefully explores the main questions in the field: What does learning mean? How can we associate complexity theory with learning? In Part III the author describes a number of techniques and algorithms that allow us to learn from text, from an informant, or through interaction with the environment. These concern automata, grammars, rewriting systems, pattern languages or transducers.

Grammatical Inference: Learning Automata and Grammars

A bibliographical study of grammatical inference

In this paper, we introduce the Lefff , a freely available, accurate and large-coverage morphological and syntactic lexicon for French, used in many NLP tools such as large-coverage parsers. We ﬁrst describe Alexina, the lexical framework in which the Lefff is developed as well as the linguistic notions and formalisms it is based on. Next, we describe the various sources of lexical data we used for building the Lefff , in particular semi-automatic lexical development techniques and conversion and merging of existing resources. Finally, we illustrate the coverage and precision of the resource by comparing it with other resources and by assessing its impact in various NLP tools.

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The Lefff, a freely available and large-coverage morphological and syntactic lexicon for French

This is the first part of a large survey paper in which we analyze recent literature on Formal Concept Analysis (FCA) and some closely related disciplines using FCA. We collected 1072 papers published between 2003 and 2011 mentioning terms related to Formal Concept Analysis in the title, abstract and keywords. We developed a knowledge browsing environment to support our literature analysis process. We use the visualization capabilities of FCA to explore the literature, to discover and conceptually represent the main research topics in the FCA community. In this first part, we zoom in on and give an extensive overview of the papers published between 2003 and 2011 on developing FCA-based methods for knowledge processing. We also give an overview of the literature on FCA extensions such as pattern structures, logical concept analysis, relational concept analysis, power context families, fuzzy FCA, rough FCA, temporal and triadic concept analysis and discuss scalability issues.

https://publications.hse.ru/mirror/pubs/share/folder/hgte0pjz18/direct/114480023.pdf

Review: Formal Concept Analysis in knowledge processing: A survey on models and techniques

Invited Papers.- Formal Ontology, Knowledge Representation and Conceptual Modelling: Old Inspirations, Still Unsolved Problems.- The Persuasive Expansion - Rhetoric, Information Architecture, and Conceptual Structure.- Revision Forever!.- Ontological Constitutions for Classes and Properties.- Peirce's Contributions to the 21st Century.- Two Iconicity Notions in Peirce's Diagrammatology.- Contributed Papers.- Simple Conceptual Graphs and Simple Concept Graphs.- Rules Dependencies in Backward Chaining of Conceptual Graphs Rules.- Thresholds and Shifted Attributes in Formal Concept Analysis of Data with Fuzzy Attributes.- Formal Concept Analysis with Constraints by Closure Operators.- Mining a New Fault-Tolerant Pattern Type as an Alternative to Formal Concept Discovery.- The MIEL++ Architecture When RDB, CGs and XML Meet for the Sake of Risk Assessment in Food Products.- Some Notes on Proofs with Alpha Graphs.- DOGMA-MESS: A Meaning Evolution Support System for Interorganizational Ontology Engineering.- FCA-Based Browsing and Searching of a Collection of Images.- Semantology: Basic Methods for Knowledge Representations.- The Teridentity and Peircean Algebraic Logic.- Transaction Agent Modelling: From Experts to Concepts to Multi-Agent Systems.- Querying Formal Contexts with Answer Set Programs.- Towards an Epistemic Logic of Concepts.- Development of Intelligent Systems and Multi-Agents Systems with Amine Platform.- Ontologies in Amine Platform: Structures and Processes.- Building a Pragmatic Methodology for KR Tool Research and Development.- Simple Conceptual Graphs with Atomic Negation and Difference.- A Pattern-Based Approach to Conceptual Clustering in FOL.- Karl Popper's Critical Rationalism in Agile Software Development.- On Lattices in Access Control Models.- An Application of Relation Algebra to Lexical Databases.- A Framework for Analyzing and Testing Requirements with Actors in Conceptual Graphs.- Query-Based Multicontexts for Knowledge Base Browsing: An Evaluation.- Representation and Reasoning on Role-Based Access Control Policies with Conceptual Graphs.- Representing Wholes by Structure.

Conceptual structures : inspiration and application : 14th International Conference on Conceptual Structures, ICCS 2006, Aalborg, Denmark, July 16-21, 2006 : proceedings

In this paper, we define Dependency Structure Grammars (DSG), which are rewriting rule grammars generating sentences together with their dependency structures, are more expressive than CF-grammars and non-equivalent to mildly context-sensitive grammars

We show that DSG are weakly equivalent to Categorial Dependency Grammars (CDG) recently introduced in [6,3] In particular, these dependency grammars naturally express long distance dependencies and enjoy good mathematical properties

Dependency structure grammars

In this paper we give some learnability results in the field of categorial grammars. We show that in contrast to k-valued classical categorial grammars, different classes of Lambek grammars are not learnable from strings following Gold's model. The results are obtained by the construction of limit points in each considered class: non associative Lambek grammars with empty sequences and Lambek grammars without empty sequences and without product. Such results express the difficulty of learning categorial grammars from unstructured strings and the need for structured examples.

On Limit Points for Some Variants of Rigid Lambek Grammars

This paper is concerned with learning in the model of Gold the Categorial Dependency Grammars (CDG), which express discontin- uous (non-projective) dependencies. We show that rigid and k-valued CDG (without optional and iterative types) are learnable from strings. In fact, we prove that the languages of dependency nets coding rigid CDGs have nite elasticity, and we show a learning algorithm. As a standard corollary, this result leads to the learnability of rigid or k- valued CDGs (without optional and iterative types) from strings.

https://hal.archives-ouvertes.fr/hal-00487058/document

On learning discontinuous dependencies from positive data

Pregroup grammars are a context-free grammar formalism which may be used to describe the syntax of natural languages. However, this formalism is not able to naturally define types corresponding to optional and iterated arguments such as optional complements of verbs or verbs' adverbial modifiers. This paper introduces two constructions that make up for this deficiency.

Optional and Iterated Types for Pregroup Grammars

We study the learnability problem in the family of Categorial Dependency Grammars (CDG), a class of categorial grammars defining unlimited dependency structures. CDG satisfying a reasonable condition on iterated (i.e., repeatable and optional) dependencies are shown to be incrementally learnable in the limit.

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Annie Foret

Papers

Dependency structure grammars

On Limit Points for Some Variants of Rigid Lambek Grammars

On learning discontinuous dependencies from positive data

Optional and Iterated Types for Pregroup Grammars

Two models of learning iterated dependencies