Tag-based dynamic ranking system for organization related news
Özkan, Mustafa Tunahan, author.

Tag-based dynamic ranking system for organization related news

Özkan, Mustafa Tunahan, author.

Yazar Ek Girişi
Özkan, Mustafa Tunahan, author.

Fiziksel Tanımlama
ix, 52 leaves: illustrarions, charts;+ 1 computer laser optical disc.

In information systems, tags are keywords or terms, which represent a piece of information. They provide to define an item and help it to be found again through searching or browsing. Tags have gained popularity due to the growth of social sharing, social bookmarking, organization network and social network websites. In addition, tags are also used to express prominent events and noticeable topics in the news. In this thesis, we propose a tag-based statistical learning approach to predict the shareability of news in an organization network. We represented features with tags by using different methods and adopted several classifiers to predict the shareability of news. We model this problem with a binary classification problem, where shareable news are considered as the positive and non-shareable news are considered as the negative class. The experimental results indicate that there is no general best classifier for the study of shareability prediction for organization related news but depending on the dataset and represented features we can adopt an optimal classifier.

Konu Başlığı
Neural networks (Computer science).
Artificial intelligence.
Machine learning.

Yazar Ek Girişi
Tuğlular, Tuğkan

Tüzel Kişi Ek Girişi
İzmir Institute of Technology. Computer Engineering.

Tek Biçim Eser Adı
Thesis (Master)--İzmir Institute of Technology: Computer Engineering.
İzmir Institute of Technology: Computer Engineering--Thesis (Master).

Elektronik Erişim
Access to Electronic Versiyon.

KütüphaneMateryal TürüDemirbaş NumarasıYer NumarasıDurumu/İade Tarihi
IYTETezT001730QA76.87 .O99 2018Tez Koleksiyonu