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From Vector Space Models to Vector Space Models of Semantics
- Source :
- Text Processing ISBN: 9783319736051, FIRE Workshop
- Publication Year :
- 2018
- Publisher :
- Springer International Publishing, 2018.
-
Abstract
- This paper assesses the performance of frequency and concept based text representation in Mixed Script Information Retrieval and Classification tasks. In text analytics, representation serves as an unresolved research problem to progress further towards different applications. In this paper observations from different text representation methods in text classification and information retrieval are presented. The data set from the Mixed Script Information Retrieval shared task is used in this experiment and the performance of final submitted model is evaluated by task organizers. It is observed that distributional representation performs better than the frequency based text representation methods. The final system attained first place in task 2 and was 3.89% lesser than the top scored system in task 1.
- Subjects :
- business.industry
Computer science
Representation (systemics)
020207 software engineering
02 engineering and technology
Semantics
computer.software_genre
Task (project management)
Data set
Text mining
020204 information systems
0202 electrical engineering, electronic engineering, information engineering
Artificial intelligence
business
computer
Natural language processing
Vector space
Subjects
Details
- ISBN :
- 978-3-319-73605-1
- ISBNs :
- 9783319736051
- Database :
- OpenAIRE
- Journal :
- Text Processing ISBN: 9783319736051, FIRE Workshop
- Accession number :
- edsair.doi...........625fc9d3c504a8ff43dc0f936b693ec7