Lida Rashidi

Corpus Bootstrapping for Assessment of the Properties of Effectiveness Measures

J Zobel, L Rashidi

Conference Proceedings  |  2020  |  CIKM '20: Proceedings of the 29th ACM International Conference on Information & Knowledge Management

Bootstrapping is an established tool for examining the behaviour of offline information retrieval (IR) experiments, where it has p..

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 and 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

Lake Urmia—a shallow endemic hypersaline lake in northwest Iran—has undergone a dramatic decline in its water level (WL), by about..

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

T Hashem, L Rashidi, J Bailey, L Kulik

Conference Proceedings  |  2019  |  Similarity Search and Applications, 12th International Conference, SISAP 2019, Newark, NJ, USA, October 2–4, 2019, Proceedings

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

Green spaces are believed to enhance the well-being of residents in urban areas. Although there is research exploring the emotiona..

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

Studying large, widely spread Twitter data has laid the foundation for many novel applications from predicting natural disasters a..

Graph stream mining based anomalous event analysis

M Yang, L Rashidi, S Rajasegarar, C Leckie

Conference Proceedings  |  2018  |  Lecture Notes in Computer Science

© 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

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 INTERNATIONAL CONFERENCE ON DIGITAL IMAGE COMPUTING: TECHNIQUES AND APPLICATIONS (DICTA)

Crowd behaviour monitoring and prediction is an important research topic in video surveillance that has gained increasing attentio..

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  |  Conference on Computer Vision and Pattern Recognition Workshops IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Workshops

In recent years, there has been a growing interest in detecting anomalous behavioral patterns in video. In this work, we address t..