Open Access. Powered by Scholars. Published by Universities.®
![Digital Commons Network](http://assets.bepress.com/20200205/img/dcn/DCsunburst.png)
Physical Sciences and Mathematics Commons™
Open Access. Powered by Scholars. Published by Universities.®
- Discipline
-
- Computer Sciences (7)
- Databases and Information Systems (5)
- Communication (2)
- Computer Engineering (2)
- Engineering (2)
-
- Logic and Foundations (2)
- Mathematics (2)
- Numerical Analysis and Scientific Computing (2)
- Social Media (2)
- Social and Behavioral Sciences (2)
- Business (1)
- Communication Technology and New Media (1)
- Computational Linguistics (1)
- Computer and Systems Architecture (1)
- Finance and Financial Management (1)
- Linguistics (1)
- Theory and Algorithms (1)
- Urban Studies and Planning (1)
- Institution
Articles 1 - 9 of 9
Full-Text Articles in Physical Sciences and Mathematics
Secondary Analysis Of Concussion Data, Martin Zwick, Stephanie Kolakowsky-Hayner, Nancy Carney, Maya Balamane, Tracie Nettleton, D. Wright
Secondary Analysis Of Concussion Data, Martin Zwick, Stephanie Kolakowsky-Hayner, Nancy Carney, Maya Balamane, Tracie Nettleton, D. Wright
Systems Science Faculty Publications and Presentations
Clinical studies are expensive & time-consuming. Typically in these studies specific hypotheses are subjected to confirmatory test. Yet the data may harbor evidence of unanticipated relations between variables. It is thus desirable to subject the data to secondary analyses in the hope of discovering novel & valuable associations. Exploratory analysis, however, is tentative: findings should be replicated in new data. This presentation reports some secondary analyses on concussion data. Data mining on 2 datasets will be discussed, & some unexpected findings reported. The analyses use reconstructability analysis (RA), a probabilistic graphical modeling method implemented in the Occam software package developed …
Arise-Pie: A People Information Integration Engine Over The Web, Vincent W. Zheng, Tao Hoang, Penghe Chen, Yuan Fang, Xiaoyan Yang
Arise-Pie: A People Information Integration Engine Over The Web, Vincent W. Zheng, Tao Hoang, Penghe Chen, Yuan Fang, Xiaoyan Yang
Research Collection School Of Computing and Information Systems
Searching for people information on the Web is a common practice in life. However, it is time consuming to search for such information manually. In this paper, we aim to develop an automatic people information search system, named ARISE-PIE. To build such a system, we tackle two major technical challenges: data harvesting and data integration. For data harvesting, we study how to leverage search engine to help crawl the relevant Web pages for a target entity; then we propose a novel learning to query model that can automatically select a set of "best" queries to maximize collective utility (e.g., precision …
Exploratory Modeling Of Tbi Data, Martin Zwick, Stephanie Kolakowsky-Hayner, Sadie Carney, Maya Balamane, Tracie Nettleton, D. Wright
Exploratory Modeling Of Tbi Data, Martin Zwick, Stephanie Kolakowsky-Hayner, Sadie Carney, Maya Balamane, Tracie Nettleton, D. Wright
Systems Science Faculty Publications and Presentations
Most data analyses are confirmatory, but exploratory studies can find unexpected non-linear & many-variable interaction effects. The methodology of reconstructability analysis (RA) is explicitly designed for exploratory modeling. It analyzes both nominal and continuous (binned) variables, is easily interpretable, takes standard text input, is web-accessible, and is available for research use. This presentation reports some results of applying RA to data sets from Preece (auto accidents) and Wright (auto/motorcycle/bike accidents, hit pedestrians, and falls).
Detection Of Cyberbullying In Sms Messaging, Bryan W. Bradley
Detection Of Cyberbullying In Sms Messaging, Bryan W. Bradley
Computer Science Summer Fellows
Cyberbullying is a type of bullying that uses technology such as cell phones to harass or malign another person. To detect acts of cyberbullying, we are developing an algorithm that will detect cyberbullying in SMS (text) messages. Over 80,000 text messages have been collected by software installed on cell phones carried by participants in our study. This paper describes the development of the algorithm to detect cyberbullying messages, using the cell phone data collected previously. The algorithm works by first separating the messages into conversations in an automated way. The algorithm then analyzes the conversations and scores the severity and …
Robust Median Reversion Strategy For Online Portfolio Selection, Dingjiang Huang, Junlong Zhou, Bin Li, Hoi, Steven C. H., Shuigeng Zhou
Robust Median Reversion Strategy For Online Portfolio Selection, Dingjiang Huang, Junlong Zhou, Bin Li, Hoi, Steven C. H., Shuigeng Zhou
Research Collection School Of Computing and Information Systems
On-line portfolio selection has been attracting increasing interests from artificial intelligence community in recent decades. Mean reversion, as one most frequent pattern in financial markets, plays an important role in some state-of-the-art strategies. Though successful in certain datasets, existing mean reversion strategies do not fully consider noises and outliers in the data, leading to estimation error and thus non-optimal portfolios, which results in poor performance in practice. To overcome the limitation, we propose to exploit the reversion phenomenon by robust L1-median estimator, and design a novel on-line portfolio selection strategy named "Robust Median Reversion" (RMR), which makes optimal portfolios based …
Euclidean Co-Embedding Of Ordinal Data For Multi-Type Visualization, Dung D. Le, Hady W. Lauw
Euclidean Co-Embedding Of Ordinal Data For Multi-Type Visualization, Dung D. Le, Hady W. Lauw
Research Collection School Of Computing and Information Systems
Embedding deals with reducing the high-dimensional representation of data into a low-dimensional representation. Previous work mostly focuses on preserving similarities among objects. Here, not only do we explicitly recognize multiple types of objects, but we also focus on the ordinal relationships across types. Collaborative Ordinal Embedding or COE is based on generative modelling of ordinal triples. Experiments show that COE outperforms the baselines on objective metrics, revealing its capacity for information preservation for ordinal data.
Mining And Clustering Mobility Evolution Patterns From Social Media For Urban Informatics, Chien-Cheng Chen, Meng-Fen Chiang, Wen-Chih Peng
Mining And Clustering Mobility Evolution Patterns From Social Media For Urban Informatics, Chien-Cheng Chen, Meng-Fen Chiang, Wen-Chih Peng
Research Collection School Of Computing and Information Systems
In this paper, given a set of check-in data, we aim at discovering representative daily movement behavior of users in a city. For example, daily movement behavior on a weekday may show users moving from one to another spatial region associated with time information. Since check-in data contain both spatial and temporal information, we propose a mobility evolution pattern to capture the daily movement behavior of users in a city. Furthermore, given a set of daily mobility evolution patterns, we formulate their similarity distances and then discover representative mobility evolution patterns via the clustering process. Representative mobility evolution patterns are …
A Cloud-Based Framework For Smart Permit System For Buildings, Magdalini Eirinaki, Subhankar Dhar, Shishir Mathur
A Cloud-Based Framework For Smart Permit System For Buildings, Magdalini Eirinaki, Subhankar Dhar, Shishir Mathur
Faculty Publications
In this paper we propose a novel cloud-based platform for building permit system that is efficient, user-friendly, transparent, and has quick turn-around time for homeowners. Compared to the existing permit systems, the proposed smart city permit framework provides a pre-permitting decision workflow, and incorporates a data analytics and mining module that enables the continuous improvement of a) the end user experience, by analyzing explicit and implicit user feedback, and b) the permitting and urban planning process, allowing a gleaning of key insights for real estate development and city planning purposes, by analyzing how users interact with the system depending on …
Iot+Small Data: Transforming In-Store Shopping Analytics And Services, Meera Radhakrishnan, Sougata Sen, Vigneshwaran Subbaraju, Archan Misra, Rajesh Balan
Iot+Small Data: Transforming In-Store Shopping Analytics And Services, Meera Radhakrishnan, Sougata Sen, Vigneshwaran Subbaraju, Archan Misra, Rajesh Balan
Research Collection School Of Computing and Information Systems
We espouse a vision of small data-based immersive retail analytics, where a combination of sensor data, from personal wearable-devices and store-deployed sensors & IoT devices, is used to create real-time, individualized services for in-store shoppers. Key challenges include (a) appropriate joint mining of sensor & wearable data to capture a shopper’s product level interactions, and (b) judicious triggering of power-hungry wearable sensors (e.g., camera) to capture only relevant portions of a shopper’s in-store activities. To explore the feasibility of our vision, we conducted experiments with 5 smartwatch-wearing users who interacted with objects placed on cupboard racks in our lab (to …