Please use this identifier to cite or link to this item:
Title: A Comparison of Recent Information Retrieval Term-Weighting Models Using Ancient Datasets
Authors: Alkılınç, Ahmet
Arslan, Ahmet
Keywords: information retrieval
term-weighting model
Issue Date: 2018
Publisher: IEEE
Abstract: With the development of technology, human computer interaction is continuously increasing. Parallel to this, information from web sites, social media, blogs and other applications reach enormous dimensions. It becomes a big problem to obtain the desired information from this mass of data. One way of solving this problem is to keep the information correctly indexed and searched by using information retrieval methods. Information retrieval is the study of finding documents of unstructured material which should satisfy users' information needs. Various term-weighting models have been proposed for information retrieval. This work is carried out to analyze and evaluate the retrieval effectiveness of recently developed term-weighting models (after the 2000s) using the earlier datasets (dating back as far as the 1980s) with the motivation of such comparison has not been done. The open source library Apache Lucene is used for all experiments and evaluation. As a result, we observe that the DFIC model is in general more effective than the other models. We note also that, although one model can be the most effective for one dataset, the same model can be the least effective for another dataset.
Description: International Conference on Artificial Intelligence and Data Processing (IDAP) -- SEP 28-30, 2018 -- Inonu Univ, Malatya, TURKEY
ISBN: 978-1-5386-6878-8
Appears in Collections:Kimya Mühendisliği Bölümü Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu
WoS İndeksli Yayınlar Koleksiyonu

Show full item record

CORE Recommender

Page view(s)

checked on Oct 3, 2022

Google ScholarTM



Items in GCRIS Repository are protected by copyright, with all rights reserved, unless otherwise indicated.