Dissertation
Aggregation and disaggregation of information: a holistic view
Doctor of Philosophy (Ph.D.), Drexel University
Jun 2021
DOI:
https://doi.org/10.17918/00000779
Abstract
This dissertation develops optimization solutions to tackle two challenges in data mining: intelligence aggregation and signal disaggregation. For each challenge, our solution consists of an optimization model and an efficient and robust algorithm to solve it. We first present a model and a solution algorithm that can decompose aggregated information into smaller constituents for multiple systems. For instance, our approach simultaneously disaggregates integrated energy signals from houses into specific measurements of appliances/activities. The results provide managerial insights for energy services without costly installing additional hardware. Unlike some traditional approaches in the literature that require large training datasets, our disaggregation algorithm uses contextual features as inputs combined with a transfer learning approach to improve model accuracy and interpretation. Next, we propose a new optimization approach to aggregating information from multiple information sources. Our model is solved with an alternated quadratic programming optimization and has been evaluated to accurately predict a stock's future trading actions by capturing inter-correlations and quantifying the reliability scores of analysts' recommendations. We further extend our aggregation model with additional time-related relevance features. The extension allows us to improve the prediction accuracy of stock future performance as well as to better understand the impact of time-dimension on aggregation tasks. Although disaggregation is the inverse process of aggregation, we investigate both topics by incorporating various types of inter-correlations in complex systems. The optimization models in this dissertation can be further applied to other research fields such as healthcare, airline business, marketing, and operations management.
Metrics
1612 File views/ downloads
27 Record Views
Details
- Title
- Aggregation and disaggregation of information
- Creators
- Yuyue Chen
- Contributors
- Hande Yurttan Benson (Advisor)
- Awarding Institution
- Drexel University
- Degree Awarded
- Doctor of Philosophy (Ph.D.)
- Publisher
- Drexel University; Philadelphia, Pennsylvania
- Number of pages
- 10, 70 pages
- Resource Type
- Dissertation
- Language
- English
- Academic Unit
- Bennett S. LeBow College of Business; Drexel University
- Other Identifier
- 991015104348604721