scholarly journals On reduction and relation type of an ideal

2021 ◽  
Vol 65 (5) ◽  
pp. 217-221
Author(s):  
PRITI SINGH ◽  
AVINASH KUMAR
Keyword(s):  
2015 ◽  
Vol 40 (3) ◽  
pp. 535-544
Author(s):  
A. V. Jayanthan ◽  
Ramakrishna Nanduri
Keyword(s):  

2021 ◽  
Vol 12 (2) ◽  
pp. 69-87
Author(s):  
Siriwon Taewijit ◽  
Thanaruk Theeramunkong

Hyperbolic embedding has been recently developed to allow us to embed words in a Cartesian product of hyperbolic spaces, and its efficiency has been proved in several works of literature since the hierarchical structure is the natural form of texts. Such a hierarchical structure exhibits not only the syntactic structure but also semantic representation. This paper presents an approach to learn meaningful patterns by hyperbolic embedding and then extract adverse drug reactions from electronic medical records. In the experiments, the public source of data from MIMIC-III (Medical Information Mart for Intensive Care III) with over 58,000 observed hospital admissions of the brief hospital course section is used, and the result shows that the approach can construct a set of efficient word embeddings and also retrieve texts of the same relation type with the input. With the Poincaré embeddings model and its vector sum (PC-S), the authors obtain up to 82.3% in the precision at ten, 85.7% in the mean average precision, and 93.6% in the normalized discounted cumulative gain.


2012 ◽  
Vol 2012 ◽  
pp. 1-15 ◽  
Author(s):  
Hemant Kumar Nashine ◽  
Zoran Kadelburg ◽  
Poom Kumam

We introduce an implicit-relation-type cyclic contractive condition for a map in a metric space and derive existence and uniqueness results of fixed points for such mappings. Examples are given to support the usability of our results. At the end of the paper, an application to the study of existence and uniqueness of solutions for a class of nonlinear integral equations is presented.


2017 ◽  
Vol 43 (4) ◽  
pp. 683-722 ◽  
Author(s):  
Shafiq Joty ◽  
Francisco Guzmán ◽  
Lluís Màrquez ◽  
Preslav Nakov

In this article, we explore the potential of using sentence-level discourse structure for machine translation evaluation. We first design discourse-aware similarity measures, which use all-subtree kernels to compare discourse parse trees in accordance with the Rhetorical Structure Theory (RST). Then, we show that a simple linear combination with these measures can help improve various existing machine translation evaluation metrics regarding correlation with human judgments both at the segment level and at the system level. This suggests that discourse information is complementary to the information used by many of the existing evaluation metrics, and thus it could be taken into account when developing richer evaluation metrics, such as the WMT-14 winning combined metric DiscoTK party. We also provide a detailed analysis of the relevance of various discourse elements and relations from the RST parse trees for machine translation evaluation. In particular, we show that (i) all aspects of the RST tree are relevant, (ii) nuclearity is more useful than relation type, and (iii) the similarity of the translation RST tree to the reference RST tree is positively correlated with translation quality.


Corpora ◽  
2017 ◽  
Vol 12 (1) ◽  
pp. 23-54 ◽  
Author(s):  
Paula C.F. Cardoso ◽  
Thiago A.S. Pardo ◽  
Maite Taboada

Subtopic segmentation aims to break documents into subtopical text passages, which develop a main topic in a text. Being capable of automatically detecting subtopics is very useful for several Natural Language Processing applications. For instance, in automatic summarisation, having the subtopics at hand enables the production of summaries with good subtopic coverage. Given the usefulness of subtopic segmentation, it is common to assemble a reference-annotated corpus that supports the study of the envisioned phenomena and the development and evaluation of systems. In this paper, we describe the subtopic annotation process in a corpus of news texts written in Brazilian Portuguese, following a systematic annotation process and answering the main research questions when performing corpus annotation. Based on this corpus, we propose novel methods for subtopic segmentation following patterns of discourse organisation, specifically using Rhetorical Structure Theory. We show that discourse structures mirror the subtopic changes in news texts. An important outcome of this work is the freely available annotated corpus, which, to the best of our knowledge, is the only one for Portuguese. We demonstrate that some discourse knowledge may significantly help to find boundaries automatically in a text. In particular, the relation type and the level of the tree structure are important features.


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