Automatic Extraction of Thai-English Term Translations and Synonyms from Medical Web using Iterative Candidate Generation with Association Measures

Author(s):  
Kobkrit Viriyayudhakorn ◽  
Thanaruk Theeramunkong ◽  
Cholwich Nattee ◽  
Thepchai Supnithi ◽  
Manabu Okumura
Author(s):  
Yoav Bar-Anan ◽  
Brian A. Nosek ◽  
Michelangelo Vianello

The sorting paired features (SPF) task measures four associations in a single response block. Using four response options (e.g., good-Republicans, bad-Republicans, good-Democrats, and bad-Democrats), each trial requires participants to categorize two stimuli at once to a category pair (e.g., wonderful-Clinton to good-Democrats). Unlike other association measures, the SPF requires simultaneous categorization of both components of the association in the same trial. Providing measurement flexibility, it is sensitive to both focal, attended concepts and nonfocal, unattended stimulus features (e.g., gender of individuals in a politics SPF). Three studies measure race, gender, and political evaluations, differentiate automatic evaluations between known groups, provide evidence of convergent and discriminant validity with other attitude measures, and illustrate the SPF’s unique measurement qualities.


2020 ◽  
Author(s):  
Stuart Yeates

A brief introduction to acronyms is given and motivation for extracting them in a digital library environment is discussed. A technique for extracting acronyms is given with an analysis of the results. The technique is found to have a low number of false negatives and a high number of false positives. Introduction Digital library research seeks to build tools to enable access of content, while making as few as possible assumptions about the content, since assumptions limit the range of applicability of the tools. Generally, the broader the assumptions the more widely applicable the tools. For example, keyword based indexing [5] is based on communications theory and applies to all natural human textual languages (allowances for differences in character sets and similar localisation issues not withstanding) . The algorithm described in this paper makes much stronger assumptions about the content. It assumes textual content that contains acronyms, an assumption which is known to hold for...


2013 ◽  
Vol 15 (4) ◽  
pp. 618 ◽  
Author(s):  
Yanling DING ◽  
Kai ZHAO ◽  
Xiaofeng LI ◽  
Xingming ZHENG

2014 ◽  
Author(s):  
Mónica Domínguez ◽  
Mireia Farrús ◽  
Alicia Burga ◽  
Leo Wanner

Author(s):  
Etsuji KITAGAWA ◽  
Ryo KATO ◽  
Satoshi ABIKO ◽  
Takumi TSUMURA ◽  
Yusuke NAKATANI

2021 ◽  
Vol 13 (14) ◽  
pp. 2810
Author(s):  
Joanna Gudowicz ◽  
Renata Paluszkiewicz

The rapid development of remote sensing technology for obtaining high-resolution digital elevation models (DEMs) in recent years has made them more and more widely available and has allowed them to be used for morphometric assessment of concave landforms, such as valleys, gullies, glacial cirques, sinkholes, craters, and others. The aim of this study was to develop a geographic information systems (GIS) toolbox for the automatic extraction of 26 morphometric characteristics, which include the geometry, hypsometry, and volume of concave landforms. The Morphometry Assessment Tools (MAT) toolbox in the ArcGIS software was developed. The required input data are a digital elevation model and the form boundary as a vector layer. The method was successfully tested on an example of 21 erosion-denudation valleys located in the young glacial area of northwest Poland. Calculations were based on elevation data collected in the field and LiDAR data. The results obtained with the tool showed differences in the assessment of the volume parameter at the average level of 12%, when comparing the field data and LiDAR data. The algorithm can also be applied to other types of concave forms, as well as being based on other DEM data sources, which makes it a universal tool for morphometric evaluation.


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