scholarly journals Question selection for crowd entity resolution

2013 ◽  
Vol 6 (6) ◽  
pp. 349-360 ◽  
Author(s):  
Steven Euijong Whang ◽  
Peter Lofgren ◽  
Hector Garcia-Molina
Keyword(s):  
Entity Resolution ◽  
Question Selection ◽  
Selection For

scholarly journals On the impact of adaptive test question selection for learning efficiency

2010 ◽  
Vol 55 (2) ◽  
pp. 846-857 ◽  
Author(s):  
Michal Barla ◽  
Mária Bieliková ◽  
Anna Bou Ezzeddinne ◽  
Tomáš Kramár ◽  
Marián Šimko ◽  
...  
Keyword(s):  
Test Question ◽  
Learning Efficiency ◽  
Adaptive Test ◽  
Question Selection ◽  
Selection For ◽  
The Impact

scholarly journals Features Selection for Entity Resolution in Prostitution on Twitter

2021 ◽  
Vol 2 (1) ◽  
pp. 53-61
Author(s):  
Reisa Permatasari ◽  
Nur Aini Rakhmawati
Keyword(s):  
Logistic Regression ◽  
Active Learning ◽  
Real World ◽  
Entity Resolution ◽  
Training Data ◽  
Features Selection ◽  
Selection For ◽  
Maximum Similarity

Entity resolution is the process of determining whether two references to real-world objects refer to the same or different purposes. This study applies entity resolution on Twitter prostitution dataset based on features with the Regularized Logistic Regression training and determination of Active Learning on Dedupe and based on graphs using Neo4j and Node2Vec. This study found that maximum similarity is 1 when the number of features (personal, location and bio specifications) is complete. The minimum similarity is 0.025662627 when the amount of harmful training data. The most influencing similarity feature is the cellphone number with the lowest starting range from 0.997678459 to 0.999993523.  The parameter - length of walk per source has the effect of achieving the best similarity accuracy reaching 71.4% (prediction 14 and yield 10).

TIQS: Targeted Iterative Question Selection for Health Interventions

2018 ◽  
Vol 2 (3) ◽  
pp. 205-227
Author(s):  
Keith Feldman ◽  
Spyros Kotoulas ◽  
Nitesh V. Chawla
Keyword(s):  
Health Interventions ◽  
Question Selection ◽  
Selection For

Question selection for multi-attribute decision-aiding

2003 ◽  
Vol 148 (3) ◽  
pp. 525-533 ◽  
Author(s):  
Hillary A. Holloway ◽  
Chelsea C. White III
Keyword(s):  
Decision Aiding ◽  
Question Selection ◽  
Selection For

Automatic Grading and Adaptive Question Selection for English Language Testing

2020 ◽  
Vol 6 (3) ◽  
pp. 22-29
Author(s):  
Chitra Bhole ◽  
Jahanvi Dave ◽  
Tanaya Surve ◽  
Khushboo Thakkar
Keyword(s):  
English Language ◽  
Language Testing ◽  
Question Selection ◽  
Selection For ◽  
Automatic Grading

scholarly journals Artifact for paper "Question Selection for Interactive Program Synthesis"

2020 ◽  
Author(s):  
Ruyi Ji ◽  
Jingjing Liang ◽  
Yingfei Xiong ◽  
Lu Zhang ◽  
Zhenjiang Hu
Keyword(s):  
Program Synthesis ◽  
Interactive Program ◽  
Question Selection ◽  
Selection For

scholarly journals ConvKN at SemEval-2016 Task 3: Answer and Question Selection for Question Answering on Arabic and English Fora

2016 ◽  
Author(s):  
Alberto Barrón-Cedeño ◽  
Giovanni Da San Martino ◽  
Shafiq Joty ◽  
Alessandro Moschitti ◽  
Fahad Al-Obaidli ◽  
...  
Keyword(s):  
Question Answering ◽  
Question Selection ◽  
Selection For ◽  
Arabic And English
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