Towards a Topic Discovery and Tracking System with Application to News Items

Autor: Brüggermann, Daniel, Hermey, Yannik, Orth, Carsten, Schneider, Darius, Selzer, Stefan, Spanakis, Gerasimos, Quesada, José F, Martín Mateos, Francisco-Jesús, López Soto, Teresa

Publikováno v: Future and Emerging Trends in Language Technology: Machine Learning and Big Data, FETLT 2016, 183-197
STARTPAGE=183;ENDPAGE=197;TITLE=Future and Emerging Trends in Language Technology: Machine Learning and Big Data, FETLT 2016
Lecture Notes in Computer Science ISBN: 9783319693644
FETLT

Rapid proliferation of the World Wide Web led to an enormous increase in the availability of textual corpora. In this paper, the problem of topic detection and tracking is considered with application to news items. The proposed approach explores two

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2a0ea282c142fb02842a8f8a7c3b97ce
https://cris.maastrichtuniversity.nl/en/publications/68c5ce2b-43e3-42e7-9b21-2d985f02f868