Exploring Extensive Linguistic Feature Sets in Near-Synonym Lexical Choice

2012 ◽  
pp. 1-12
Author(s):  
Mari-Sanna Paukkeri ◽  
Jaakko Väyrynen ◽  
Antti Arppe
Keyword(s):  
Linguistic Feature ◽  
Feature Sets ◽  
Lexical Choice

Arabic named entity recognition using optimized feature sets

2008 ◽  
Author(s):  
Yassine Benajiba ◽  
Mona Diab ◽  
Paolo Rosso
Keyword(s):  
Named Entity Recognition ◽  
Entity Recognition ◽  
Feature Sets ◽  
Named Entity

Hybrid Model using Firefly and BBO for Feature Selection in Software Product Line

2020 ◽  
Vol 13 ◽  
Author(s):  
Hitesh Yadav ◽  
Rita Chhikara ◽  
Charan Kumari
Keyword(s):  
Hybrid Model ◽  
High Performance ◽  
Software Product Line ◽  
Product Line ◽  
Feature Model ◽  
Software Systems ◽  
Feature Sets ◽  
Research Article ◽  
Software Product ◽  
Multiple Variants

Background: Software Product Line is the group of multiple software systems which share the similar set of features with multiple variants. Feature model is used to capture and organize features used in different multiple organization. Objective: The objective of this research article is to obtain an optimized subset of features which are capable of providing high performance. Methods: In order to achieve the desired objective, two methods have been proposed. a) An improved objective function which is used to compute the contribution of each feature with weight based methodology. b) A hybrid model is employed to optimize the Software Product Line problem. Results: Feature sets varying in size from 100 to 1000 have been used to compute the performance of the Software Product Line. Conclusion: The results shows that proposed hybrid model outperforms the state of art metaheuristic algorithms.

Discourse, Context, and Coherence

2018 ◽  
Author(s):  
Una Stojnić
Keyword(s):  
Prima Facie ◽  
Context Sensitivity ◽  
Linguistic Meaning ◽  
Linguistic Features ◽  
Linguistic Feature ◽  
Discourse Context ◽  
Context Sensitive ◽  
Pure Indexicals

On the received view, the resolution of context-sensitivity is at least partly determined by non-linguistic features of utterance situation. If I say ‘He’s happy’, what ‘he’ picks out is underspecified by its linguistic meaning, and is only fixed through extra-linguistic supplementation: the speaker’s intention, and/or some objective, non-linguistic feature of the utterance situation. This underspecification is exhibited by most context-sensitive expressions, with the exception of pure indexicals, like ‘I.’ While this received view is prima facie appealing, I argue it is deeply mistaken. I defend an account according to which context-sensitivity resolution is governed by linguistic mechanisms determining prominence of candidate resolutions of context-sensitive items. Thus, on this account, the linguistic meaning of a context-sensitive expression fully specifies its resolution in a context, automatically selecting the resolution antecedently set by the prominence-governing linguistic mechanisms.

Inverse agreement in Hungarian

2017 ◽  
Author(s):  
András Bárány
Keyword(s):  
First Person ◽  
Personal Pronouns ◽  
Second Person ◽  
Morphological Effect ◽  
Object A ◽  
Feature Sets ◽  
Explicit Analysis ◽  
The Subject ◽  
Agreement Morphology ◽  
Object Agreement

This chapter turns to object agreement with personal pronouns in Hungarian. Pronouns are interesting because they do not always trigger agreement with the verb: first person objects never trigger object agreement (morphology), and second person pronouns only do with first person singular subjects. It is proposed that the distribution of object agreement is a morphological effect and argues that all personal pronouns do in fact trigger agreement, but agreement is not always spelled out. This means that Hungarian has an inverse agreement system, where the spell-out of agreement is determined by the relative person feature (or person feature sets) of the subject and the object. A formally explicit analysis of the syntax and the morphological spell-out of agreement is provided.

scholarly journals A Unified View of Causal and Non-causal Feature Selection

2021 ◽  
Vol 15 (4) ◽  
pp. 1-46
Author(s):  
Kui Yu ◽  
Lin Liu ◽  
Jiuyong Li
Keyword(s):  
Feature Selection ◽  
Bayesian Network ◽  
Synthetic Data ◽  
Selection Methods ◽  
Bayesian Network Model ◽  
Real World Data ◽  
Feature Sets ◽  
Unified View ◽  
Optimal Feature ◽  
Different Levels

In this article, we aim to develop a unified view of causal and non-causal feature selection methods. The unified view will fill in the gap in the research of the relation between the two types of methods. Based on the Bayesian network framework and information theory, we first show that causal and non-causal feature selection methods share the same objective. That is to find the Markov blanket of a class attribute, the theoretically optimal feature set for classification. We then examine the assumptions made by causal and non-causal feature selection methods when searching for the optimal feature set, and unify the assumptions by mapping them to the restrictions on the structure of the Bayesian network model of the studied problem. We further analyze in detail how the structural assumptions lead to the different levels of approximations employed by the methods in their search, which then result in the approximations in the feature sets found by the methods with respect to the optimal feature set. With the unified view, we can interpret the output of non-causal methods from a causal perspective and derive the error bounds of both types of methods. Finally, we present practical understanding of the relation between causal and non-causal methods using extensive experiments with synthetic data and various types of real-world data.

scholarly journals Linguistic feature of anorexia nervosa: a prospective case–control pilot study

2021 ◽  
Author(s):  
Vittoria Cuteri ◽  
Giulia Minori ◽  
Gloria Gagliardi ◽  
Fabio Tamburini ◽  
Elisabetta Malaspina ◽  
...  
Keyword(s):  
Anorexia Nervosa ◽  
Language Processing ◽  
Statistical Significance ◽  
Case Control ◽  
Pathological Process ◽  
Linguistic Features ◽  
Level Of Evidence ◽  
Linguistic Feature ◽  
Linguistic Markers ◽  
Clinical Conditions

Abstract Purpose Attention has recently been paid to Clinical Linguistics for the detection and support of clinical conditions. Many works have been published on the “linguistic profile” of various clinical populations, but very few papers have been devoted to linguistic changes in patients with eating disorders. Patients with Anorexia Nervosa (AN) share similar psychological features such as disturbances in self-perceived body image, inflexible and obsessive thinking and anxious or depressive traits. We hypothesize that these characteristics can result in altered linguistic patterns and be detected using the Natural Language Processing tools. Methods We enrolled 51 young participants from December 2019 to February 2020 (age range: 14–18): 17 girls with a clinical diagnosis of AN, and 34 normal-weighted peers, matched by gender, age and educational level. Participants in each group were asked to produce three written texts (around 10–15 lines long). A rich set of linguistic features was extracted from the text samples and the statistical significance in pinpointing the pathological process was measured. Results Comparison between the two groups showed several linguistics indexes as statistically significant, with syntactic reduction as the most relevant trait of AN productions. In particular, the following features emerge as statistically significant in distinguishing AN girls and their normal-weighted peers: the length of the sentences, the complexity of the noun phrase, and the global syntactic complexity. This peculiar pattern of linguistic erosion may be due to the severe metabolic impairment also affecting the central nervous system in AN. Conclusion These preliminary data showed the existence of linguistic parameters as probable linguistic markers of AN. However, the analysis of a bigger cohort, still ongoing, is needed to consolidate this assumption. Level of evidence III Evidence obtained from case–control analytic studies.

Sign in / Sign up

Export Citation Format

Share Document