39865913
Criminal Cross Correlation Mining and Visualization
Criminals are creatures of habit and their crime activities are geospatially, temporally and thematically correlated. Discovering these correlations is a core component of intelligence-led policing and allows for a deeper insight into the complex nature of criminal behavior. A spatial bivariate correlation measure should be used to discover these patterns from heterogeneous data types. We introduce a bivariate spatial correlation approach for crime analysis that can be extended to extract multivariate cross correlations. It is able to extract the top-k and bottom-k associative features from areal aggregated datasets and visualize the resulting patterns. We demonstrate our approach with real crime datasets and provide a comparison with other techniques. Experimental results reveal the applicability and usefulness of the proposed approach.
28879268
URBAN CRIME ANALYSIS THROUGH AREAL CATEGORIZED MULTIVARIATE ASSOCIATIONS MINING
As geospatial data grows explosively, there is a great demand for the incorporation of data mining techniques into a geospatial context. Association rules mining is a core technique in data mining and is a solid candidate for the associative analysis of large geospatial databases. In this article, we propose a geospatial knowledge discovery framework for automating the detection of multivariate associations based on a given areal base map. We investigate a series of geospatial preprocessing steps involving data conversion and classification so that the traditional Boolean and quantitative association rules mining can be applied. Our framework has been integrated into GISs using a dynamic link library to allow the automation of both the preprocessing and data mining phases to provide greater ease of use for users. Experiments with real-crime datasets quickly reveal interesting frequent patterns and multivariate associations, which demonstrate the robustness and efficiency of our approach.
43179350
Mining Positive Associations of Urban Criminal Activities Using Hierarchical Crime Hot Spots
We present a framework for discovering positive associations in urban crime datasets using hierarchical clustering and an association test based on a hybrid minimum bounding circle and average bounding circle approach. We justify the virtue of our framework by comparing its computational speed and quality of associations using real crime datasets.
41826766
What-if Emergency Management System: A Generalized Voronoi Diagram Approach
As witnessed in many recent disastrous events, emergency management is becoming more and more important to prevent hazards, plan for actions, quickly respond to minimize losses, and to recover from damages. In this paper, we propose the complete higher-order Voronoi diagram based emergency management system for what-if analysis which is particularly useful in highly dynamic environments. This system is based on a unified order-k Delaunay triangle data structure which supports various topological and regional queries, and what-if analysis. The proposed system encompasses: 1) what-if scenarios when new changes are dynamically updated; 2) what-if scenarios when order-k generators (disasters or professional bodies) or their territorial regions are of interest; (3) what-if scenarios when ordered order-k generators or their territorial regions are of interest; 4) what-if scenarios when k-th nearest generators or their territorial regions are of interest; 5) what-if scenarios with mixtures of the above.
36048413
Gaming, Fine Art, and Familiar Strangers
13239679
The conductor interaction method
Computers have increasingly become part of our everyday lives, with many activities either involving their direct use or being supported by one. This has prompted research into developing methods and mechanisms to assist humans in interacting with computers (human-computer interaction, or HCI). A number of HCI techniques have been developed over the years, some of which are quite old but continue to be used, and some more recent and still evolving. Many of these interaction techniques, however, are not natural in their use and typically require the user to learn a new means of interaction. Inconsistencies within these techniques and the restrictions they impose on user creativity can also make such interaction techniques difficult to use, especially for novice users.
 This article proposes an alternative interaction method, the conductor interaction method (CIM), which aims to provide a more natural and easier-to-learn interaction technique. This novel interaction method extends existing HCI methods by drawing upon techniques found in human-human interaction. It is argued that the use of a two-phased multimodal interaction mechanism, using gaze for selection and gesture for manipulation, incorporated within a metaphor-based environment, can provide a viable alternative for interacting with a computer (especially for novice users). Both the model and an implementation of the CIM within a system are presented in this article. This system formed the basis of a number of user studies that have been performed to assess the effectiveness of the CIM, the findings of which are discussed in this work.
8893156
User-driven design of a tangible awareness landscape
This paper describes the design and evolutionary development of a system for supporting informal interactions between geographically-remote members of a group. Based on simple internet technologies, the system described enables the use of novel, tangible devices for the purpose of discrete event notification. A simple system was initially developed for use in an office environment for providing awareness events via a single notification device. Over a four month period this simple system evolved into a suite of low-cost, low-tech notification devices for public and personal use. The numerous devices utilised by the final system constitute a physical landscape of awareness which have been demonstrated to support group and individual awareness of discrete events in both fixed locations and on the move.
16619176
In Search of Salience: A Response-time and Eye-movement Analysis of Bookmark Recognition
Bookmarks are a valuable webpage re-visitation technique, but it is often difficult to find desired items in extensive bookmark collections. This experiment used response-time measures and eye-movement tracking to investigate how different information structures within bookmarks influence their salience and recognizability. Participants were presented with a series of news websites. The task following presentation of each site was to find the bookmark indexing the previously-seen page as quickly as possible. The Informational Structure of bookmarks was manipulated (top-down vs. bottom-up verbal organizations), together with the Number of Informational Cues present (one, two or three). Only this latter factor affected gross search times: Two cues were optimal, one cue was highly sub-optimal. However, more detailed eye-movement analyses of fixation behaviour on target items revealed interactive effects of both experimental factors, suggesting that the efficacy of bookmark recognition is crucially dependent on having an optimal combination of information quantity and information organization.
35945312
Exponential Cluster Smearing