Deep Stylometry and Lexical & Syntactic Features Based Author Attribution on PLoS Digital Repository

2017 ◽  
pp. 119-127 ◽  
Author(s):  
Saeed-Ul Hassan ◽  
Mubashir Imran ◽  
Tehreem Iftikhar ◽  
Iqra Safder ◽  
Mudassir Shabbir
Keyword(s):  
Digital Repository ◽  
Syntactic Features

More's usage of Latin verbal predicates: the particular case of fio

Moreana ◽  
2019 ◽  
Vol 56 (Number 211) (1) ◽  
pp. 97-120
Author(s):  
Concepción Cabrillana
Keyword(s):  
General Framework ◽  
Medieval Latin ◽  
Lexical Semantic ◽  
Syntactic Features ◽  
Comparative Review ◽  
Poetic Text

This article addresses Thomas More's use of an especially complex Latin predicate, fio, as a means of examining the degree of classicism in this aspect of his writing. To this end, the main lexical-semantic and syntactic features of the verb in Classical Latin are presented, and a comparative review is made of More's use of the predicate—and also its use in texts contemporaneous to More, as well as in Late and Medieval Latin—in both prose and poetry. The analysis shows that he works within a general framework of classicism, although he introduces some of his own idiosyncrasies, these essentially relating to the meaning of the verb that he employs in a preferential way and to the variety of verbal forms that occur in his poetic text.

Syntactic features of Englishization in Korean

1994 ◽  
Vol 13 (2) ◽  
pp. 155-166 ◽  
Author(s):  
MARTIN JONGHAK BAIK
Keyword(s):  
Syntactic Features

Interaction, Satisfaction, and the PCC

2021 ◽  
pp. 1-80
Author(s):  
Amy Rose Deal
Keyword(s):  
Special Interest ◽  
Dynamic Interaction ◽  
Agree Ii ◽  
Indirect Object ◽  
Syntactic Features ◽  
Testing Ground ◽  
Person Case Constraint ◽  
Satisfaction Theory ◽  
The Way

Abstract The person-case constraint (PCC) is a family of restrictions on the relative person of the two objects of a ditransitive. PCC effects offer a testing ground for theories of the Agree operation and of syntactic features, both those on nominals and (of special interest here) those found on agreement probes. In this paper, I offer a new theory of PCC effects in an interaction/satisfaction theory of Agree (Deal 2015a) and show the advantages of this framework in capturing PCC typology. On this model, probes are specified for interaction features, determining which features will be copied to them, and satisfaction features, determining which features will cause probing to stop. Applied to PCC, this theory (i) captures all four types of PCC effect recognized by Nevins (2007) under a unified notion of Agree; (ii) captures the restriction of PCC effects to contexts of “Double Weakness” in many prominent examples, e.g. in Italian, Greek, and Basque, where PCC effects hold only in cases where both the direct and indirect object are expressed with clitics; (iii) naturally extends to PCC effects in syntactic environments without visible clitics or agreement for one or both objects, as well as the absence of PCC effects in some languages with clitics or agreement for both the direct and indirect object. Two refinements of the interaction/satisfaction theory are offered. The first is a new notation for probes’ interaction and satisfaction specifications, clarifying the absence from this theory of uninterpretable/unvalued features as drivers of Agree. The second is a proposal for the way that probes’ behavior may change over the course of a derivation, dubbed dynamic interaction.

Multi-Graph Cooperative Learning Towards Distant Supervised Relation Extraction

2021 ◽  
Vol 12 (5) ◽  
pp. 1-21
Author(s):  
Changsen Yuan ◽  
Heyan Huang ◽  
Chong Feng
Keyword(s):  
Cooperative Learning ◽  
State Of The Art ◽  
Relation Extraction ◽  
Sentence Length ◽  
Universal Relation ◽  
Dependency Parsing ◽  
Convolutional Network ◽  
Syntactic Features ◽  
Use Dependency

The Graph Convolutional Network (GCN) is a universal relation extraction method that can predict relations of entity pairs by capturing sentences’ syntactic features. However, existing GCN methods often use dependency parsing to generate graph matrices and learn syntactic features. The quality of the dependency parsing will directly affect the accuracy of the graph matrix and change the whole GCN’s performance. Because of the influence of noisy words and sentence length in the distant supervised dataset, using dependency parsing on sentences causes errors and leads to unreliable information. Therefore, it is difficult to obtain credible graph matrices and relational features for some special sentences. In this article, we present a Multi-Graph Cooperative Learning model (MGCL), which focuses on extracting the reliable syntactic features of relations by different graphs and harnessing them to improve the representations of sentences. We conduct experiments on a widely used real-world dataset, and the experimental results show that our model achieves the state-of-the-art performance of relation extraction.

Import Metadata through EPrints for Institutional Digital Repository

2019 ◽  
Vol 9 (2) ◽  
pp. 1-4
Author(s):  
Sukumar Mandal
Keyword(s):  
Open Source ◽  
Digital Library ◽  
Open Source Software ◽  
Information Services ◽  
Digital Information ◽  
Digital Repository ◽  
Library System ◽  
Different Types ◽  
Digital Library System ◽  
Important Field

Digital library is a collection of electronic objects. Information retrieval is a part of digital library system. Digital library can be developed through open source software and tools. Institutional digital repository is also an important field in present and next generation automated and digital library system. Now, this paper is present how to import metadata formats from different database by EPrints for the development of institutional digital repository. There are different types of metadata formats available in open source environment but this paper is shows some high and matured level software for development and designing this integrated framework. However, in this section has a show how to data import from Koha, Emerald, D-Space, and Vu-Find for the better management of digital information services among the users as well as library professionals.

Using Mobile Technologies in Education

2017 ◽  
Vol 13 (4) ◽  
pp. 77-90 ◽  
Author(s):  
Célio Gonçalo Cardoso Marques ◽  
António Manso ◽  
Ana Paula Ferreira ◽  
Felisbela Morgado
Keyword(s):  
Teaching And Learning ◽  
Reading Skills ◽  
Mobile Technologies ◽  
Ministry Of Education ◽  
Digital Repository ◽  
Learning To Read ◽  
Level Of Satisfaction ◽  
Complex Process ◽  
High Level ◽  
And Training

The acquisition of reading skills is decisive for the academic achievement of students. However, learning to read is a complex process. With this in mind, several attempts have been made to find new educational approaches to enhance students' reading motivation. Considering the enormous potential of ICT for education and training, we have developed a digital repository of teaching and learning materials and a multiplatform application that runs on mobile devices: Letrinhas. This information system was designed to promote the development of reading and to provide tools for monitoring and assessing reading skills against the curricular targets set by the Ministry of Education. Letrinhas was evaluated by specialists and users and a high level of satisfaction was observed among students and teachers as time and effort spent to consolidate reading is considerably reduced with this application. This evaluation also enabled to identify features that will be available in the future.

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