Authors are encouraged to submit new papers to INFORMS journals by means of a style file template... more Authors are encouraged to submit new papers to INFORMS journals by means of a style file template, which includes the journal title. However, use of a template does not certify that the paper has been accepted for publication in the named journal. INFORMS journal templates are for the exclusive purpose of submitting to an INFORMS journal and should not be used to distribute the papers in print or online or to submit the papers to another publication.
This research applies machine learning methods, in particular probabilistic topic modeling, to un... more This research applies machine learning methods, in particular probabilistic topic modeling, to understand patterns of interactions for Over-the-Counter (OTC) trading in corporate bonds. The interactions are between broker-dealers (dealers) and clients, or between dealers. From reports of dealer transactions, we create documents representing the daily activity of each dealer. This includes four types of dealer activities: Buy from / Sell to a client, and Buy from / Sell to another dealer. We use Latent Dirichlet Allocation (LDA) based topic models to identify communities of bonds that are bought or sold (co-traded) on the same day. Some communities reflect an industry sector, while others have a concentration of specific bonds. Several topics temporally align to notable financial events. We group dealers around topics to understand their interactions with clients and other dealers. We observe a range of interaction patterns that merit further study, including the centrality of some dealer(s) to some topics. This research illustrates that topic modeling / community detection can indeed provide insight into dealer behavior for OTC trades.
The need for supply chain integration (SCI) methodologies has been increasing as a consequence of... more The need for supply chain integration (SCI) methodologies has been increasing as a consequence of the globalization of production and sales, and the advancement of enabling information technologies. In this paper, we describe our experience with implementing and modeling SCIs. We present the integration architecture and the software components of our prototype implementation. We then discuss a variety of information sharing methodologies. Then, within the framework of a multi-echelon supply chain process model spanning multiple organizations, we summarize research on the benefits of intraorganizational knowledge sharing, and we discuss performance scalability.
Advances in Web technology enable personalization proxies that assist users in satisfying their c... more Advances in Web technology enable personalization proxies that assist users in satisfying their complex information monitoring and aggregation needs through the repeated querying of multiple volatile data sources. Such proxies face a scalability challenge when trying to maximize the number of clients served while at the same time fully satisfying clients' complex user profiles. In this work we use an abstraction of complex execution intervals (CEIs) constructed over simple execution intervals (EIs) represents user profiles and use existing offline approximation as a baseline for maximizing completeness of capturing CEIs. We present three heuristic solutions for the online problem of query scheduling to satisfy complex user profiles. The first only considers properties of individual EIs while the other two exploit properties of all EIs in the CEI. We use an extensive set of experiments on real traces and synthetic data to show that heuristics that exploit knowledge of the CEIs dominate across multiple parameter settings.
Taman Tasik Titiwangsa lakes are popular for water sport activity. Thus, it is important to keep ... more Taman Tasik Titiwangsa lakes are popular for water sport activity. Thus, it is important to keep the health of the lakes at an acceptable level for the optimum usage of water sport activity. The water quality index is used to assess the water quality condition of the lakes. Water quality index (WQI) and interim national water quality standards (INWQS) for Malaysia are used to monitor the health of the lakes. A total of two sample stations were collected at Lake 1 and Lake 2 of Taman Tasik Titiwangsa. Six selected parameters (biological oxygen demand, chemical oxygen demand, dissolved oxygen, pH, suspended solid and ammoniacal nitrogen) were used to calculate the water quality index. From the analysis, it showed that both Lake 1 and Lake 2 are Class II condition and visitors can use it for water sport activity. Several recommendations are noted to improve the WQI value for the use of Taman Tasik Titiwangsa visitors especially for water sport activity.
Accessing many data sources aggravates problems for users of heterogeneous distributed databases.... more Accessing many data sources aggravates problems for users of heterogeneous distributed databases. Database administrators must deal with fragile mediators, that is, mediators with schemas and views that must be significantly changed to incorporate a new data source. When ...
Many real-world data sets are modeled as entity relationship graphs or heterogeneous information ... more Many real-world data sets are modeled as entity relationship graphs or heterogeneous information networks. In these graphs, nodes represent entities and edges mimic relationships. ObjectRank extends the well-known PageRank authority flow-based ranking method to entity relationship graphs using an authority flow weight vector (W). The vector W assigns a different authority flow-based importance (weight) to each edge type based on domain knowledge or personalization. In this paper, our contribution is a framework for Learning to Rank in entity relationship graphs to learn W, in the context of authority flow. We show that the problem is similar to learning a recursive scoring function. We present a two-phase iterative solution and multiple variants of learning. In pointwise learning, we learn W, and hence the scoring function, from the scores of a sample of nodes. In pairwise learning, we learn W from given preferences for pairs of nodes. To demonstrate our contribution in a real setting, we apply our framework to learn the rank, with high accuracy, for a real-world challenge of predicting future citations in a bibliographic archive-that is, the FutureRank score. Our extensive experiments show that with a small amount of training data, and a limited number of iterations, our Learning to Rank approach learns W with high accuracy. Learning works well with pairwise training data in large graphs.
... Interoperable query processing for relational and object-oriented databases: a mapping approa... more ... Interoperable query processing for relational and object-oriented databases: a mapping approach using canonical representations. Authors: Ya-Hui Chang, Co-Advisers: Louiqa Raschid, Bonnie J. Dorr, ... top of page AUTHORS. Ya-Hui Chang No contact information provided yet. ...
During the last decade, life sciences researchers have gained access to the entire human genome, ... more During the last decade, life sciences researchers have gained access to the entire human genome, reliable high-throughput biotechnologies, affordable computational resources, and public network access. This has produced vast amounts of data and knowledge captured in the life sciences Web, and has created the need for new tools to analyze this knowledge and make discoveries. Consider a simplified Web of three publicly accessible data resources Entrez Gene, PubMed and OMIM. Data records in each resource are annotated with terms from multiple controlled vocabularies (CVs). The links between data records in two resources form a relationship between the two resources. Thus, a record in Entrez Gene, annotated with GO terms, can have links to multiple records in PubMed that are annotated with MeSH terms. Similarly, OMIM records annotated with terms from SNOMED CT may have links I would like to convey my gratitude to the following individuals for supporting me with the inspiration to embark on my Ph.D. Dissertation. My deepest appreciation goes to the advisor, Dr. Louiqa Raschid, who shepherded me through the bulk of the work. Her kind but rigorous oversight of this thesis constantly boosted my knowledge to the completion of the work. I was very fortunate to have been able to work with her since undertaking my previous research topics. I also thank my co-advisor, Dr. Chau-Wen Tseng for inspiring me to bridge computer science and life sciences. He always made himself available for invaluable help and precious advice.
As the amount of information grows and as users become more sophisticated, ranking techniques bec... more As the amount of information grows and as users become more sophisticated, ranking techniques become important building blocks to meet user needs when answering queries. PageRank is one of the most successful link-based ranking methods, which iteratively computes the importance scores for web pages based on the importance scores of incoming pages. Due to its success, PageRank has been applied in a number of applications that require customization. We address the scalability challenges for two types of customized ranking. The first challenge is to compute the ranking of a subgraph. Various Web applications focus on identifying a subgraph, such as focused crawlers and localized search engines. The second challenge is to compute online personalized ranking. Personalized search improves the quality of search results for each user. The user needs are represented by a personalized set of pages or personalized link importance in an entity relationship graph. This requires an efficient online computation. To solve the subgraph ranking problem efficiently, we estimate the ranking scores for a subgraph. We propose a framework of an exact solution (IdealRank) and
Authors are encouraged to submit new papers to INFORMS journals by means of a style file template... more Authors are encouraged to submit new papers to INFORMS journals by means of a style file template, which includes the journal title. However, use of a template does not certify that the paper has been accepted for publication in the named journal. INFORMS journal templates are for the exclusive purpose of submitting to an INFORMS journal and should not be used to distribute the papers in print or online or to submit the papers to another publication.
This research applies machine learning methods, in particular probabilistic topic modeling, to un... more This research applies machine learning methods, in particular probabilistic topic modeling, to understand patterns of interactions for Over-the-Counter (OTC) trading in corporate bonds. The interactions are between broker-dealers (dealers) and clients, or between dealers. From reports of dealer transactions, we create documents representing the daily activity of each dealer. This includes four types of dealer activities: Buy from / Sell to a client, and Buy from / Sell to another dealer. We use Latent Dirichlet Allocation (LDA) based topic models to identify communities of bonds that are bought or sold (co-traded) on the same day. Some communities reflect an industry sector, while others have a concentration of specific bonds. Several topics temporally align to notable financial events. We group dealers around topics to understand their interactions with clients and other dealers. We observe a range of interaction patterns that merit further study, including the centrality of some dealer(s) to some topics. This research illustrates that topic modeling / community detection can indeed provide insight into dealer behavior for OTC trades.
The need for supply chain integration (SCI) methodologies has been increasing as a consequence of... more The need for supply chain integration (SCI) methodologies has been increasing as a consequence of the globalization of production and sales, and the advancement of enabling information technologies. In this paper, we describe our experience with implementing and modeling SCIs. We present the integration architecture and the software components of our prototype implementation. We then discuss a variety of information sharing methodologies. Then, within the framework of a multi-echelon supply chain process model spanning multiple organizations, we summarize research on the benefits of intraorganizational knowledge sharing, and we discuss performance scalability.
Advances in Web technology enable personalization proxies that assist users in satisfying their c... more Advances in Web technology enable personalization proxies that assist users in satisfying their complex information monitoring and aggregation needs through the repeated querying of multiple volatile data sources. Such proxies face a scalability challenge when trying to maximize the number of clients served while at the same time fully satisfying clients' complex user profiles. In this work we use an abstraction of complex execution intervals (CEIs) constructed over simple execution intervals (EIs) represents user profiles and use existing offline approximation as a baseline for maximizing completeness of capturing CEIs. We present three heuristic solutions for the online problem of query scheduling to satisfy complex user profiles. The first only considers properties of individual EIs while the other two exploit properties of all EIs in the CEI. We use an extensive set of experiments on real traces and synthetic data to show that heuristics that exploit knowledge of the CEIs dominate across multiple parameter settings.
Taman Tasik Titiwangsa lakes are popular for water sport activity. Thus, it is important to keep ... more Taman Tasik Titiwangsa lakes are popular for water sport activity. Thus, it is important to keep the health of the lakes at an acceptable level for the optimum usage of water sport activity. The water quality index is used to assess the water quality condition of the lakes. Water quality index (WQI) and interim national water quality standards (INWQS) for Malaysia are used to monitor the health of the lakes. A total of two sample stations were collected at Lake 1 and Lake 2 of Taman Tasik Titiwangsa. Six selected parameters (biological oxygen demand, chemical oxygen demand, dissolved oxygen, pH, suspended solid and ammoniacal nitrogen) were used to calculate the water quality index. From the analysis, it showed that both Lake 1 and Lake 2 are Class II condition and visitors can use it for water sport activity. Several recommendations are noted to improve the WQI value for the use of Taman Tasik Titiwangsa visitors especially for water sport activity.
Accessing many data sources aggravates problems for users of heterogeneous distributed databases.... more Accessing many data sources aggravates problems for users of heterogeneous distributed databases. Database administrators must deal with fragile mediators, that is, mediators with schemas and views that must be significantly changed to incorporate a new data source. When ...
Many real-world data sets are modeled as entity relationship graphs or heterogeneous information ... more Many real-world data sets are modeled as entity relationship graphs or heterogeneous information networks. In these graphs, nodes represent entities and edges mimic relationships. ObjectRank extends the well-known PageRank authority flow-based ranking method to entity relationship graphs using an authority flow weight vector (W). The vector W assigns a different authority flow-based importance (weight) to each edge type based on domain knowledge or personalization. In this paper, our contribution is a framework for Learning to Rank in entity relationship graphs to learn W, in the context of authority flow. We show that the problem is similar to learning a recursive scoring function. We present a two-phase iterative solution and multiple variants of learning. In pointwise learning, we learn W, and hence the scoring function, from the scores of a sample of nodes. In pairwise learning, we learn W from given preferences for pairs of nodes. To demonstrate our contribution in a real setting, we apply our framework to learn the rank, with high accuracy, for a real-world challenge of predicting future citations in a bibliographic archive-that is, the FutureRank score. Our extensive experiments show that with a small amount of training data, and a limited number of iterations, our Learning to Rank approach learns W with high accuracy. Learning works well with pairwise training data in large graphs.
... Interoperable query processing for relational and object-oriented databases: a mapping approa... more ... Interoperable query processing for relational and object-oriented databases: a mapping approach using canonical representations. Authors: Ya-Hui Chang, Co-Advisers: Louiqa Raschid, Bonnie J. Dorr, ... top of page AUTHORS. Ya-Hui Chang No contact information provided yet. ...
During the last decade, life sciences researchers have gained access to the entire human genome, ... more During the last decade, life sciences researchers have gained access to the entire human genome, reliable high-throughput biotechnologies, affordable computational resources, and public network access. This has produced vast amounts of data and knowledge captured in the life sciences Web, and has created the need for new tools to analyze this knowledge and make discoveries. Consider a simplified Web of three publicly accessible data resources Entrez Gene, PubMed and OMIM. Data records in each resource are annotated with terms from multiple controlled vocabularies (CVs). The links between data records in two resources form a relationship between the two resources. Thus, a record in Entrez Gene, annotated with GO terms, can have links to multiple records in PubMed that are annotated with MeSH terms. Similarly, OMIM records annotated with terms from SNOMED CT may have links I would like to convey my gratitude to the following individuals for supporting me with the inspiration to embark on my Ph.D. Dissertation. My deepest appreciation goes to the advisor, Dr. Louiqa Raschid, who shepherded me through the bulk of the work. Her kind but rigorous oversight of this thesis constantly boosted my knowledge to the completion of the work. I was very fortunate to have been able to work with her since undertaking my previous research topics. I also thank my co-advisor, Dr. Chau-Wen Tseng for inspiring me to bridge computer science and life sciences. He always made himself available for invaluable help and precious advice.
As the amount of information grows and as users become more sophisticated, ranking techniques bec... more As the amount of information grows and as users become more sophisticated, ranking techniques become important building blocks to meet user needs when answering queries. PageRank is one of the most successful link-based ranking methods, which iteratively computes the importance scores for web pages based on the importance scores of incoming pages. Due to its success, PageRank has been applied in a number of applications that require customization. We address the scalability challenges for two types of customized ranking. The first challenge is to compute the ranking of a subgraph. Various Web applications focus on identifying a subgraph, such as focused crawlers and localized search engines. The second challenge is to compute online personalized ranking. Personalized search improves the quality of search results for each user. The user needs are represented by a personalized set of pages or personalized link importance in an entity relationship graph. This requires an efficient online computation. To solve the subgraph ranking problem efficiently, we estimate the ranking scores for a subgraph. We propose a framework of an exact solution (IdealRank) and
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