Zohreh Nazeri

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A multi-mode network typically consists of multiple heterogeneous social actors among which various types of interactions could occur. Identifying communities in a multi-mode network can help understand the structural properties of the network, address the data shortage and unbalanced problems, and assist tasks like targeted marketing and finding(More)
This paper describes our latest experiment with application of data mining to analyzing severe weather impacts on National Airspace System (NAS) performance. We show the importance of data preparation and feature extraction in our work. Two types of data, weather and air traffic data were used in this experiment. Weather data are represented as binary(More)
This paper discusses a method for incorporating available domain knowledge into data mining techniques in order to improve the interestingness of the discovered rules. Existing domain knowledge is represented by a simple grammar and is used within the algorithms in order to reduce the search space and generate more interesting results. We implemented the(More)
The goal of data analysis in aviation safety is simple: improve safety. However, the path to this goal is hard to identify. What data mining methods are most applicable to this task? What data are available and how should they be analyzed? How do we focus on the most interesting results? Our answers to these questions are based on a recent research project(More)
Identifying patterns of factors associated with aircraft accidents is of high interest to the aviation safety community. However, accident data is not large enough to allow a significant discovery of repeating patterns of the factors. We applied the STUCCO algorithm to analyze aircraft accident data in contrast to the aircraft incident data in major(More)
Air transportation systems are designed to ensure that aircraft accidents are rare events. To minimize these accidents, factors causing or contributing to accidents must be understood and prevented. Previous research has studied accident data to determine these factors. The low rate of accidents however, makes it difficult to discover repeating patterns of(More)
In this paper we present the results of applying data mining techniques to identify patterns and anomalies in air traffic control operational errors (OEs). Reducing the OE rate is of high importance and remains a challenge in the aviation safety community. Existing studies, which use traditional methods and focus on individual aspects of OEs, are limited to(More)
Over 2 million serious side effects, including 100,000 deaths, occur due to adverse drug reactions (ADR) every year in the US. Though various NGOs monitor ADRs through self reporting systems, earlier detection can be achieved using patient electronic health record (EHR) data available at many medical facilities. This paper presents an algorithm which allow(More)