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We integrate heterogeneous terminologies into our category-theoretic model of faceted browsing and show that existing terminologies and vocabularies can be reused as facets in a cohesive, interactive system. Commonly found in online search engines and digital libraries, faceted browsing systems depend upon one or more taxonomies which outline the structure and content of the facets available for user...
The data streams in many applications are characterized by imbalanced class distribution. The pattern in data streams may also change over time and therefore, the classification model should be adjusted to maintain performance. Hence, a new set of labeled samples should be provided which is not an easy task, since labeling is expensive and time consuming. In this paper, we propose Reduced Labeled...
Precision agriculture is a data-driven farming practice that uses intra-and inter-field information to optimize farming operations. The "brain" of precision agriculture is a decision support system (DSS) that acquires data from various sources, analyzes them, and recommends actions to farmers. Recently cloud computing has been used to improve the scalability and reliability of a DSS. Cloud-based...
Schema heterogeneity has been perceived as a major challenge towards data integration and exchange for more than two decades. The advent of big data and NoSQL data stores has further led to proliferation of data models thus exacerbating those challenges. It would be useful to have an approach that allows leveraging both schema-based and schemaless data stores. A graph model provides a solution towards...
Machine learning models deployed in real world applications, operate in a dynamic environment where the datadistribution can change constantly. These changes, calledconcept drifts, cause the performance of the learned modelto degrade over time. As such it is essential to detect andadapt to changes in the data, for the model to be of any realuse. While, model adaptation requires labeled data (for retraining),...
Healthcare has and continues to be an integral component in people's lives, especially for the rising elderly population. One such healthcare program that provides for the needs of the elderly is Medicare. It is important that any such program be affordable but, unfortunately, this is not always the case. Out of the many possible factors for the rising cost of healthcare, fraud is a major contributor,...
Personal data storages (PDSs) give individuals the ability to store their personal data in a data unified repository and control release of their data to data consumers. Being able to gather personal data from different data sources (e.g., banks, hospitals), PDSs will play strategic role in individual privacy management. As such, PDS demands for new privacy models for protecting personal data. In...
A tremendous growth and progress has shown the potential of big data (i.e structured, unstructured and semi-structured) to extract valuable information and do reliable prediction for several industries. Social networking data has created additional opportunities for data scientists and researchers to utilize the data points to advance the predictive and mining models and techniques. However, predictive...
Companies in today's world need to cope with an ever greater need for flexible and agile IT systems to keep up with the competition and rapidly changing markets. This leads to increasingly complex system landscapes that are often realized using service-oriented architectures (SOA). Companies often struggle to handle the complexity and the governance activities necessary after this paradigm shift....
Catastrophes have caused tremendous damages in human history and triggered record high post-disaster relief from the governments. The research of catastrophic modeling can help estimate the effects of natural disasters like hurricanes, floods, surges, and earthquakes. In every Atlantic hurricane season, the state of Florida in the United States has the potential to suffer economic and human losses...
In the last years, the large availability of data and schema models formalized through different languages has demanded effective and efficient methodologies to reuse such models. One of the most challenging problem consists in integrating different models in a global conceptualization of a specific knowledge or application domain. This is a hard task to accomplish due to ambiguities, inconsistencies...
The Florida Public Hurricane Loss Model (FPHLM) is a public catastrophe model that integrates and regulates all key components, such as meteorology, engineering, and actuarial components, by following a certain workflow in the execution phase. The validation phase governed by an Automatic Data Validation (ADV) program simulates each modeled execution component with a large number of historical insurance...
While cancer treatments are constantly advancing, there is still a real risk of relapse after potentially curative treatments. At the risk of adverse side effects, certain adjuvant treatments can be given to patients that are at high risk of recurrence. The challenge, however, is in finding the best tradeoff between these two extremes. Patients that are given more potent treatments, such as chemotherapy,...
We consider cluster analysis task on web pages based on various techniques to group the pages. While grouping the web pages based on the semantic meaning expressed in the content is required for some applications, we focus on clustering based on the web page structure and style for applications like categorization, cleaning, schema detection and automatic extractions. This paper describes some of...
Understanding the sentiment conveyed by a person is a crucial task in any social interaction. Moreover, it can be used to gain insight and understanding of views held by many people. Sentiment classification is not limited to human interaction, as text can also convey the sentiment of the author. Opinion mining in text is a long studied field in machine learning. This study focuses on two of the many...
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