Lida Rashidi

Corpus Bootstrapping for Assessment of the Properties of Effectiveness Measures

J Zobel, L Rashidi

Conference Proceedings  |  2020  |  Proceedings of the 29th ACM International Conference on Information & Knowledge Management

PRESS: A personalised approach for mining top-k groups of objects with subspace similarity

Tahrima Hashem, Lida Rashidi, Lars Kulik, James Bailey

Journal article  |  2020  |  Data & Knowledge Engineering

Personalised analytics is a powerful technology that can be used to improve the career, lifestyle, and health of individuals by pr..

Climatic or regionally induced by humans? Tracing hydro-climatic and land-use changes to better understand the Lake Urmia tragedy

Bahram Khazaei, Sina Khatami, Seyed Hamed Alemohammad, Lida Rashidi, Changshan Wu, Kaveh Madani, Zahra Kalantari, Georgia Destouni, Amir Aghakouchak

Journal article  |  2019  |  Journal of Hydrology

Characteristics of Local Intrinsic Dimensionality (LID) in Subspaces: Local Neighbourhood Analysis

T Hashem, L Rashidi, J Bailey, L Kulik

Conference Proceedings  |  2019  |  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

The local intrinsic dimensionality (LID) model enables assessment of the complexity of the local neighbourhood around a specific q..

Understanding sentiments and activities in green spaces using a social data-driven approach

KH Lim, KE Lee, D Kendal, L Rashidi, E Naghizade, Y Feng, J Wang

Book Chapter  |  2019

Gathering cutting-edge research and insights from academics, practitioners and policy-makers around the globe, Transitioning to Sm..

Happiness is a Choice: Sentiment and Activity-Aware Location Recommendation

J Wang, Y Feng, E Naghizade, L Rashidi, KH Lim, K Lee

Conference Proceedings  |  2018  |  Companion of the The Web Conference 2018 on The Web Conference 2018 - WWW '18

Studying large, widely spread Twitter data has laid the foundation for many novel applications from predicitng natural distasters ..

Graph stream mining based anomalous event analysis

M Yang, L Rashidi, S Rajasegarar, C Leckie

Conference Proceedings  |  2018  |  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

© Springer Nature Switzerland AG 2018. A major challenge in video surveillance is how to accurately detect anomalous behavioral pa..

The grass is greener on the other side: understanding the effects of green spaces on Twitter user sentiments

Kwan Hui Lim, K Lee, Dave Kendal, Lida Rashidi, Elham Naghi Zadeh Kakhki, stephan Winter, maria Vasardani

Conference Proceedings  |  2018  |  The Web Conference 2018 - Companion of the World Wide Web Conference, WWW 2018

Green spaces are believed to improve the well-being of users in urban areas. While there are urban research exploring the emotiona..

Cluster-based Crowd Movement Behavior Detection

Meng Yang, Lida Rashidi, Aravinda S Rao, Sutharshan Rajasegarar, Mohadeseh Ganji, Marimuthu Palaniswami, Christopher Leckie

Conference Proceedings  |  2018  |  2018 Digital Image Computing: Techniques and Applications (DICTA)

Crowd Activity Change Point Detection in Videos via Graph Stream Mining

Meng Yang, Lida Rashidi, Sutharshan Rajasegarar, Christopher Leckie, Aravinda S Rao, Marimuthu Palaniswami

Conference Proceedings  |  2018  |  2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)