Paris Attacks November 2015 (36), Barack Obama (5), Premier League (37), Cypriot Financial Crisis 2012-2013 (5), Rolling Stones (1), Debt Crisis in Greece (5), Samsung Galaxy S5 (35), Greek Elections June 2012 (5), smartphone (5), Malaysia Airlines Flight 370 (39), Stephen Hawking (1), Michelle Obama (38), Tohoku earthquake and tsunami (5), NBA draft (1), U2 (1), Wall Street (1). The topics Barack Obama, Cypriot Financial Crisis 2012-2013, Rolling Stones, Debt Crisis in Greece, Greek Elections June 2012, smartphone, Stephen Hawking, Tohoku earthquake and tsunami, NBA draft, U2 and Wall Street appear no more than 5 times and therefore, they are regarded as noise. The remaining 5 topics of WikiRef220 are:

• Paris Attacks November 2015
• Premier League
• Malaysia Airlines Flight 370
• Samsung Galaxy S5
• Michelle Obama

The WikiRef186 dataset (4 topics) is the WikiRef220 without 34 documents related to “Malaysia Airlines Flight 370” and the WikiRef150 dataset (3 topics) is the WikiRef186 without the 36 documents related to “Paris Attacks”.

If you use this dataset, please cite: Gialampoukidis, I., Vrochidis, S., & Kompatsiaris, I. (2016). A Hybrid Framework for News Clustering Based on the DBSCAN-Martingale and LDA. In Machine Learning and Data Mining in Pattern Recognition (pp. 170-184). Springer International Publishing

• Barack Obama(5),
• Premier League(37),
• Cypriot Financial Crisis 2013(5),
• Rolling Stones(1),
• Debt Crisis in Greece(5),
• Samsung Galaxy S5(35),
• Greek Elections June 2012(5),
• smartphone(5),
• Malaysia Airlines Flight 370(5),
• Stephen Hawking(1),
• Michelle Obama(38),
• Tohoku earthquake and tsunami(5),
• NBA draft(1),
• U2(1),
• Wall Street(1)

If you use this dataset, please cite: Gialampoukidis, I., Vrochidis, S., & Kompatsiaris, I. (2016). A Hybrid Framework for News Clustering Based on the DBSCAN-Martingale and LDA. In Machine Learning and Data Mining in Pattern Recognition (pp. 170-184). Springer International Publishing

• Economy-Business-Finance,
• Lifestyle-Leisure,
• Science-Technology and Sports.

It should be noted that the articles are classified to a single topic.

If you use this dataset in your research, please cite the following article:

D. Liparas, Y. Hacohen-Kerner, A. Moumtzidou, S. Vrochidis and I. Kompatsiaris, “News articles classification using Random Forests and weighted multimodal features”, 3rd Open Interdisciplinary MUMIA Conference and 7th Information Retrieval Facility Conference (IRFC2014), Copenhagen, Denmark, November 10-12, 2014.

• Nature_Environment,
• Politics,
• Science_Technology,
• Economy_Business_Finance,
• Health and Lifestyle_leisure.

It should be noted that the articles are classified to a single topic.

• Nature_Environment,
• Politics,
• Science_Technology,
• Economy_Business_Finance,
• Health and Lifestyle_Leisure.

It should be noted that the articles are classified to a single topic.

The dataset contains 106 videos from news reports. Videos are categorised into nine concepts/events. Keyframes for the concept and event detection are extracted. The total number of key frames in this dataset is 2826. DCNN features are extracted from the key frames based on the Caffe models trained in the work of (Markatopoulou et al., 2016). Using a random balanced split on the dataset for each concept/event, where the videos are divided into three chunks, a three-fold CV is performed using two chunks for training purposes and the remaining chunk for testing. The classification algorithm used in this code is SVM, where the “c” parameter is tuned using grid search. Output of this module is the evaluation per concept/event on videos in terms of accuracy and F-score.