Search results for "Natural language"
showing 10 items of 650 documents
Minimal forbidden words and factor automata
1998
International audience; Let L(M) be the (factorial) language avoiding a given antifactorial language M. We design an automaton accepting L(M) and built from the language M. The construction is eff ective if M is finite. If M is the set of minimal forbidden words of a single word v, the automaton turns out to be the factor automaton of v (the minimal automaton accepting the set of factors of v). We also give an algorithm that builds the trie of M from the factor automaton of a single word. It yields a non-trivial upper bound on the number of minimal forbidden words of a word.
Project thesaurus 2020 — Linguistic and ontological aspects
2011
Structures and linguistic concepts of thesauri are analyzed and compared. Proposals for the improvement of thesauri are developed.
Using Topic Modeling Methods for Short-Text Data: A Comparative Analysis
2020
With the growth of online social network platforms and applications, large amounts of textual user-generated content are created daily in the form of comments, reviews, and short-text messages. As a result, users often find it challenging to discover useful information or more on the topic being discussed from such content. Machine learning and natural language processing algorithms are used to analyze the massive amount of textual social media data available online, including topic modeling techniques that have gained popularity in recent years. This paper investigates the topic modeling subject and its common application areas, methods, and tools. Also, we examine and compare five frequen…
Learning the structure of HMM's through grammatical inference techniques
2002
A technique is described in which all the components of a hidden Markov model are learnt from training speech data. The structure or topology of the model (i.e. the number of states and the actual transitions) is obtained by means of an error-correcting grammatical inference algorithm (ECGI). This structure is then reduced by using an appropriate state pruning criterion. The statistical parameters that are associated with the obtained topology are estimated from the same training data by means of the standard Baum-Welch algorithm. Experimental results showing the applicability of this technique to speech recognition are presented. >
Use of Machine Learning and Artificial Intelligence to Drive Personalized Medicine Approaches for Spine Care
2020
Personalized medicine is a new paradigm of healthcare in which interventions are based on individual patient characteristics rather than on “one-size-fits-all” guidelines. As epidemiological datasets continue to burgeon in size and complexity, powerful methods such as statistical machine learning and artificial intelligence (AI) become necessary to interpret and develop prognostic models from underlying data. Through such analysis, machine learning can be used to facilitate personalized medicine via its precise predictions. Additionally, other AI tools, such as natural language processing and computer vision, can play an instrumental part in personalizing the care provided to patients with …
Morphometrics of Second Iron Age ceramics - strengths, weaknesses, and comparison with traditional typology.
2014
12 pages; International audience; Although the potential of geometric morphometrics for the study of archaeological artefacts is recognised, quantitative evaluations of the concordance between such methods and traditional typology are rare. The present work seeks to fill this gap, using as a case study a corpus of 154 complete ceramic vessels from the Bibracte oppidum (France), the capital of the Celtic tribe Aedui from the Second Iron Age. Two outline-based approaches were selected: the Elliptic Fourier Analysis and the Discrete Cosine Transform. They were combined with numerous methods of standardisation/normalisation. Although standardisations may use either perimeter or surface, the res…
UML Style Graphical Notation and Editor for OWL 2
2010
OWL is becoming the most widely used knowledge representation language. It has several textual notations but no standard graphical notation apart from verbose ODM UML. We propose an extension to UML class diagrams (heavyweight extension) that allows a compact OWL visualization. The compactness is achieved through the native power of UML class diagrams extended with optional Manchester encoding for class expressions thus largely eliminating the need for explicit anonymous class visualization. To use UML class diagram notation we had to modify its semantics to support Open World Assumption that is central to OWL. We have implemented the proposed compact visualization for OWL 2 in a UML style …
Modeling and Query Language for Hospitals
2013
So far the traditional process modeling languages have found a limited use in the hospital settings. One of the reasons behind this delay has been the lack of clear definition of the sequence of activities that are carried out in the hospital. We propose a new modeling language (as a profile of UML Class diagrams) that captures all the useful features from various UML diagrams and can be used in modeling of the hospitals. Based on the modeling language, we have developed an easy-to-perceive graphical query language, which allows the physicians to retrieve directly from the various hospital databases information they need to better understand the flow of clinical processes.
Vagueness expressions in Italian, Spanish and English task-oriented dialogues
2017
In this article, we present a corpus-based analysis on the use of Vagueness Expressions (VEs) in Italian, Spanish and English in Task-oriented Dialogues. Following the distinction among informational, relational and discourse vagueness (Voghera 2012), we compare the width of the functional space of the most frequent VEs. In particular we investigate whether and to what extent the VEs cover all the types of vagueness in the three languages. Quantitative and qualitative analysis brings evidence about a high convergence in the vagueness functions expressed by the VEs of the three languages.
Extracting Features from Social Media Networks Using Semantics
2016
This paper focuses on the analysis of social media content generated by social networks (e.g. Twitter) in order to extract semantic features. By using text categorization to sort text feeds into categories of similar feeds, it has been proved to reduce the overhead that is required to retrieve these feeds and at the same time, it provides smaller pools in which further investigations can be made easier. The aim of this survey is to draw a user profile, by analysing his or her tweets. In this early stage of research, being a pre-processing phase, a dictionary based approach is considered. Moreover, the paper describes an algorithm used in analysing the text and its preliminary results. This …