Institute of Formal and Applied Linguistics

Protein Ligandability Recognition

• Sample proteins:  plr.sample.zip
  Important: This sample data should NOT be used for solution of assigned tasks! – Neither for learning, nor for evaluation!  
• Data sets to be used for your exercise:  set.A.zip   set.B.zip   set.C.zip   set.D.zip
• Feature set description: plr.attributes.pdf 
   

Native Language Identification

• Data for clustering
• Development data fv.c.1.gram.rel.traindev.csv, train.txt, dev.txt
• Selected references
  • Hladká Barbora, Holub Martin, Kríž Vincent: Feature Engineering in the NLI Shared Task 2013: Charles University Submission Report. In: Proceedings of the Eighth Workshop on Innovative Use of NLP for Building Educational Applications, ACL, Atlanta, Georgia, USA, pp. 232-241, 2013.
  • Kríž Vincent, Holub Martin, Pecina Pavel: Feature Extraction for Native Language Identification Using Language Modeling. In: Proceedings of Recent Advances in Natural Language Processing, Research Group in Computational Linguistics, University of Wolverhampton, UK, Hisarja, Bulgaria, ISSN 1313-8502, pp. 298-306, 2015.
  • Ircing Pavel, Švec Jan, Zajíc Zbyněk, Hladká Barbora, Holub Martin: Combining Textual and Speech Features in the NLI Task Using State-of-the-Art Machine Learning Techniques. In: Proceedings of the 12th Workshop on Innovative Use of NLP for Building Educational Applications. Stroudsburg, PA, USA, pp. 198-209, 2017

Movie Recommendation Task

• Feature description mov.handout
• Development data mov.development.csv
• Development data for cross-validation mov.data.zip
• Load the data into R using load-mov-data.R

Word Sense Disambiguation

• Feature description wsd.attributes.pdf
• Development data wsd.development.csv
  • data-sample.pdf

Semantic Collocations Identification

• Task description col-description.pdf
• Feature description col.attributes.pdf
• Development data col.development.csv

​Selected data sets

• Auto
  • dim(Auto) # [1] 392   9
  • description
• Baseball players
  • baseball.players.csv
  • examples = read.csv("baseball.players.csv", header=TRUE, sep=";")
  • dim(data) # [1] 1034    6
  • description
• Caravan
  • library(ISLR); dim(Caravan) # [1] 5822   86
  • description
• College
  • library(ISLR); dim(College) # [1] 777   18
  • dataset-29177.csv
  • description
• ​Students
  • examples = read.csv("https://stats.idre.ucla.edu/wp-content/uploads/2016/02/sample.csv", header=T)
  • dim(examples) #[1] 200   6
• USArrests
  • dim(USArrests) # [1] 50   4
  • description
• Titanic data set
  • train.csv (Source: https://www.kaggle.com/c/titanic)
  • test.csv

Example data – evaluation of a written test – data and the description of the fields

ZS.2018 — lectures