Outputs (4)

Exploiting various word embedding models for query expansion in microblog (2020)
Presentation / Conference Contribution
Ahmed, S., Chy, A. N., & Ullah, M. Z. (2020). Exploiting various word embedding models for query expansion in microblog. In 2020 IEEE 8th R10 Humanitarian Technology Conference (R10-HTC). https://doi.org/10.1109/R10-HTC49770.2020.9357016

Microblogs, especially Twitter, make it easier to communicate with others in a real-time manner and is treated as a valuable information source. With the increasing amount of tweets, it would be fascinating to be able to extract essential information... Read More about Exploiting various word embedding models for query expansion in microblog.

An ML Model for Predicting Information Check-Worthiness using a Variety of Features (2020)
Presentation / Conference Contribution
Ullah, M. Z. (2020). An ML Model for Predicting Information Check-Worthiness using a Variety of Features. In Proceedings of the Workshop on Machine Learning for Trend and Weak Signal Detection in Social Networks and Social Media (56-61)

In this communication, we introduce the important problem of information check-worthiness. We present the method we developed to automatically answer this problem. This method makes use of an elaborated information representation that combines the “i... Read More about An ML Model for Predicting Information Check-Worthiness using a Variety of Features.

Prediction and Visual Intelligence for Security Information: The PREVISION H2020 Project (2020)
Presentation / Conference Contribution
Demestichas, K., Hoang, T. B. N., Mothe, J., Teste, O., & Ullah, M. Z. (2020, July). Prediction and Visual Intelligence for Security Information: The PREVISION H2020 Project. Presented at CIRCLE'20, Samatan, France

This paper presents the on going work within PREVISION H2020 project. The mission of PREVISION is to empower the analysts and investigators of agencies with tools and solutions not commercially available today, to handle and capitalize on the massive... Read More about Prediction and Visual Intelligence for Security Information: The PREVISION H2020 Project.

Forward and backward feature selection for query performance prediction (2020)
Presentation / Conference Contribution
Déjean, S., Ionescu, R. T., Mothe, J., & Ullah, M. Z. (2020, March). Forward and backward feature selection for query performance prediction. Presented at 35th Annual ACM Symposium on Applied Computing, Brno, Czech Republic

The goal of query performance prediction (QPP) is to automatically estimate the effectiveness of a search result for any given query, without relevance judgements. Post-retrieval features have been shown to be more effective for this task while being... Read More about Forward and backward feature selection for query performance prediction.