Search results for "natural language processing"
showing 10 items of 413 documents
A Hidden Markov Model for Automatic Generation of ER Diagrams from OWL Ontology
2014
Connecting ontological representations and data models is a crucial need in enterprise knowledge management, above all in the case of federated enterprises where corporate ontologies are used to share information coming from different databases. OWL to ERD transformations are a challenging research field in this scenario, due to the loss of expressiveness arising when OWL axioms have to be represented using ERD notation. In this paper we propose an innovative technique for estimating the most likely composition of ERD constructs that correspond to a given sequence of OWL axioms. We model such a process using a Hidden Markov Model (HMM) where the OWL inputs are the observable states, while E…
Graphical Template Language for Transformation Synthesis
2010
Higher-Order Transformations (HOT) have become an important support for the development of model transformations in various transformation languages. Most frequently HOTs are used to synthesize transformations from different kinds of models, for example, mapping models. This means that model driven development (MDD) is being successfully applied to transformations themselves too. The standard HOT solution is to create the transformation as a model using the abstract syntax. However, for graphical transformation languages a significantly more efficient solution would be to create the transformation using its graphical (concrete) syntax. An analogy could be the textual template languages such…
Comments on “Overviews of Models Defined with Charts of Concepts” by X. Castellani
2000
This paper has introduced a simplified model for the representation of system development methods. The model forms charts of concepts. Different from other metamodels that are made to explain methods in details, the charts of concepts are to help understanding of the concepts of methods using graphic presentation.
Correction: Mechanical properties of provisional dental materials: A systematic review and meta-analysis.
2018
Provisional restorations represent an important phase during the rehabilitation process, knowledge of the mechanical properties of the available materials allows us to predict their clinical performance. At present, there is no systematic review, which supports the clinicians’ criteria, in the selection of a specific material over another for a particular clinical situation. The purpose of this systematic review and meta-analysis was to assess and compare the mechanical properties of dimethacrylates and monomethacrylates used in fabricating direct provisional restorations, in terms of flexural strength, fracture toughness and hardness. This review followed the PRISMA guidelines. The searche…
Analysis and Comparison of Deep Learning Networks for Supporting Sentiment Mining in Text Corpora
2020
In this paper, we tackle the problem of the irony and sarcasm detection for the Italian language to contribute to the enrichment of the sentiment analysis field. We analyze and compare five deep-learning systems. Results show the high suitability of such systems to face the problem by achieving 93% of F1-Score in the best case. Furthermore, we briefly analyze the model architectures in order to choose the best compromise between performances and complexity.
Automatic Dictionary Creation by Sub-symbolic Encoding of Words
2006
This paper describes a technique for automatic creation of dictionaries using sub-symbolic representation of words in cross-language context. Semantic relationship among words of two languages is extracted from aligned bilingual text corpora. This feature is obtained applying the Latent Semantic Analysis technique to the matrices representing terms co-occurrences in aligned text fragments. The technique allows to find the “best translation” according to a properly defined geometric distance in an automatically created semantic space. Experiments show an interesting correctness of 95% obtained in the best case.
Review of Non-English Corpora Annotated for Emotion Classification in Text
2020
In this paper we try to systematize the information about the available corpora for emotion classification in text for languages other than English with the goal to find what approaches could be used for low-resource languages with close to no existing works in the field. We analyze the corresponding volume, emotion classification schema, language of each corresponding corpus and methods employed for data preparation and annotation automation. We’ve systematized twenty-four papers representing the corpora and found that corpora were mostly for the most spoken world languages: Hindi, Chinese, Turkish, Arabic, Japanese etc. A typical corpus contained several thousand of manually-annotated ent…
A Methodology for Bilingual Lexicon Extraction from Comparable Corpora
2015
Dictionary extraction using parallel corpora is well established. However, for many language pairs parallel corpora are a scarce resource which is why in the current work we discuss methods for dictionary extraction from comparable corpora. Hereby the aim is to push the boundaries of current approaches, which typically utilize correlations between co-occurrence patterns across languages, in several ways: 1) Eliminating the need for initial lexicons by using a bootstrapping approach which only requires a few seed translations. 2) Implementing a new approach which first establishes alignments between comparable documents across languages, and then computes cross-lingual alignments between wor…
Supporting Emotion Automatic Detection and Analysis over Real-Life Text Corpora via Deep Learning: Model, Methodology, and Framework
2021
This paper describes an approach for supporting automatic satire detection through effective deep learning (DL) architecture that has been shown to be useful for addressing sarcasm/irony detection problems. We both trained and tested the system exploiting articles derived from two important satiric blogs, Lercio and IlFattoQuotidiano, and significant Italian newspapers.
The computation of word associations
2002
It is shown that basic language processes such as the production of free word associations and the generation of synonyms can be simulated using statistical models that analyze the distribution of words in large text corpora. According to the law of association by contiguity, the acquisition of word associations can be explained by Hebbian learning. The free word associations as produced by subjects on presentation of single stimulus words can thus be predicted by applying first-order statistics to the frequencies of word co-occurrences as observed in texts. The generation of synonyms can also be conducted on co-occurrence data but requires second-order statistics. The reason is that synony…