no code implementations • 21 Mar 2018 • Tu Nguyen, Nattiya Kanhabua, Wolfgang Nejdl
Entity aspect recommendation is an emerging task in semantic search that helps users discover serendipitous and prominent information with respect to an entity, of which salience (e. g., popularity) is the most important factor in previous work.
no code implementations • 28 Jan 2017 • Nattiya Kanhabua, Philipp Kemkes, Wolfgang Nejdl, Tu Ngoc Nguyen, Felipe Reis, Nam Khanh Tran
Significant parts of cultural heritage are produced on the web during the last decades.
no code implementations • 14 Jan 2017 • Tuan Tran, Claudia Niederée, Nattiya Kanhabua, Ujwal Gadiraju, Avishek Anand
In this work, we present a novel approach for timeline summarization of high-impact events, which uses entities instead of sentences for summarizing the event at each individual point in time.
no code implementations • 10 Nov 2016 • Avaré Stewart, Sara Romano, Nattiya Kanhabua, Sergio Di Martino, Wolf Siberski, Antonino Mazzeo, Wolfgang Nejdl, Ernesto Diaz-Aviles
Many studies have shown that this also holds for the medical domain, where Twitter is considered a viable tool for public health officials to sift through relevant information for the early detection, management, and control of epidemic outbreaks.
no code implementations • 23 Jun 2016 • Nattiya Kanhabua, Huamin Ren, Thomas B. Moeslund
In general, event-related information needs can be observed in query streams through various temporal patterns of user search behavior, e. g., spiky peaks for popular events, and periodicities for repetitive events.
no code implementations • 1 Jul 2014 • Dimitrios Kotsakos, Theodoros Lappas, Dimitrios Kotzias, Dimitrios Gunopulos, Nattiya Kanhabua, Kjetil Nørvåg
A large number of mainstream applications, like temporal search, event detection, and trend identification, assume knowledge of the timestamp of every document in a given textual collection.
Ranked #3 on Document Dating on APW