Premium
Scheduling aspects in keyword extraction problem
Author(s) -
Zimniewicz Michał,
Kurowski Krzysztof,
Węglarz Jan
Publication year - 2018
Publication title -
international transactions in operational research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.032
H-Index - 52
eISSN - 1475-3995
pISSN - 0969-6016
DOI - 10.1111/itor.12368
Subject(s) - computer science , correctness , scalability , scheduling (production processes) , artificial intelligence , software , machine learning , theoretical computer science , programming language , database , operations management , economics
The amount of big data collected during human–computer interactions requires natural language processing (NLP) applications to be executed efficiently, especially in parallel computing environments. Scalability and performance are critical in many NLP applications such as search engines or web indexers. However, there is a lack of mathematical models helping users to design and apply scheduling theory for NLP approaches. Moreover, many researchers and software architects reported various difficulties related to common NLP benchmarks. Therefore, this paper aims to introduce and demonstrate how to apply a scheduling model for a class of keyword extraction approaches. Additionally, we propose methods for the overall performance evaluation of different algorithms, which are based on processing time and correctness (quality) of answers. Finally, we present a set of experiments performed in different computing environments together with obtained results that can be used as reference benchmarks for further research in the field.