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A Semantic Approach for Automatic Recovery of Software Architecture
(2014)
and reusing open source software systems. The limitation is primarily due to the lack of an automatic approach to recovering architecture models from source code. In particular, the increasing size of most open source systems makes it a challenge to manually...
Deep Assertion discovery using word embeddings
(University of Missouri -- Kansas City, 2018)
In recent years, there has been explosive growth in the amount of biomedical data
(e.g., publications, notes from EHRs, clinical trial results), with the majority being
unstructured data. As the volume of data is ...
iHear – Lightweight Machine Learning Engine with Context Aware Audio Recognition Model
(University of Missouri–Kansas City, 2016)
With the increasing popularity and affordability of smartphones, there is a high demand to add
machine-learning engines to smartphones. However, Machine Learning with smartphones is typically
not feasible due to the heavy ...
KB4DL: Building a Knowledge Base for Deep Learning
(University of Missouri -- Kansas City, 2019)
Deep Learning (DL) has received considerable attention from the AI community. However, we
suffer from the lack of ability in interpretation and annotation of the outcomes from
extensive and exhausting learning efforts. ...
A Graph Analytics Framework for Knowledge Discovery
(2016)
In the current data movement, numerous efforts have been made to convert and normalize
a large number of traditionally structured and unstructured data to semi-structured data
(e.g., RDF, OWL). With the increasing number ...
A Pervasive Middleware for Activity Recognition with Smartphones
(2015)
Activity Recognition (AR) is an important research topic in pervasive computing. With the rapid increase in the use of pervasive devices, huge sensor data is generated from diverse devices on a daily basis. Analysis of the sensor data is a...
Semantic Frameworks for Document and Ontology Clustering
(University of Missouri--Kansas City, 2011-01-20)
prove the effectiveness of this model in extracting citation semantics. For the clustering stage, the Citonomy framework offers two approaches: (1) CS-VS: Combining Citation Semantics and VSM (Vector Space Model) Measures and (2) CS2CS: From Citation...
Evidence based medical query system on large scale data
(2014-07-30)
query systems based on Ontology, Medical Subject Headings (MeSH), or keyword searches are available, query systems based on evidence and effective retrieval of data from large collections of clinical data are not sufficiently available. This thesis...
MDRED: Multi-Modal Multi-Task Distributed Recognition for Event Detection
(University of Missouri -- Kansas City, 2018)
Understanding users’ context is essential in emerging mobile sensing applications, such
as Metal Detector, Glint Finder, Facefirst. Over the last decade, Machine Learning (ML)
techniques have evolved dramatically for ...
Deep Learning for Semi-Automated Brain Claustrum Segmentation on Magnetic Resonance (MR) Images
(University of Missouri--Kansas City, 2018)
In recent years, Deep Learning (DL) has shown promising results with regard to
conducting AI tasks such as computer vision and speech recognition. Specifically, DL
demonstrated the state-of-the-art in computer vision ...
SigsSpace-Text: Parallel and Distributed Signature Learning in Text Analytics
(University of Missouri--Kansas City, 2016)
Big data analytics uncover hidden patterns and useful information from big data. It is a complex and time-consuming process. Recent advancements in parallel and distributed approaches have led to the evolution of big data analytics. It also claimed...
Event driven querying of semantic sensor web services
(University of Missouri--Kansas City, 2012-05-15)
containing dozens of sensor nodes. The observed data from the various sensors need to be thoroughly analyzed for understanding the content they carry. Human analysis of the observed data is not always feasible or convincible, and hence, although there has...
Social Bridge: searching beyond Friend of a Friend networks
(University of Missouri--Kansas City, 2012-06-11)
Social networking has turned into an integral constituent in our lives. There appears
to be an imperative demand for finding and linking with others to share one's day-to-day
activities. However, currently available ...
Active Mobile Interface for smart health
(2013)
Computer interfaces are rapidly evolving beyond the traditional keyboard-mouse-monitor triad. The widespread availability of touch screens and voice recognition software has made it possible to execute commands in many ...
A semantic framework for event-driven service composition
(University of Missouri--Kansas City, 2011-09-14)
Service Oriented Architecture (SOA) has become a popular paradigm for designing
distributed systems where loosely coupled services (i.e. computational entities) can be
integrated seamlessly to provide complex composite ...
SAF-DL: Semantic Analysis Framework for Deep Learning Open Source Projects
(University of Missouri--Kansas City, 2018)
There are a lot of open source projects available on the internet. Specifically, due to the
increasing interest of Deep Learning (DL), the number of DL open source projects is also
increased. This project is motivated ...
VirtualMindTrial: An Intelligent Questionnaire System for Clinical Trail Recruitment
(University of Missouri--Kansas City, 2010)
redundancy and inconsistency. In this thesis, an intelligent approach to questionnaire flow called VirtualMindTrial is proposed. Given a set of textual inclusion/exclusion clinical trial eligibility criteria and data available from diverse sources...
PPDQ-BG: Parallel Partition and Distributed Query Processing for Big Graphs
(University of Missouri--Kansas City, 2016)
In recent years, there has been an explosive growth of the linked data of a global
information space that often requires expensive computations to perform big graph analysis
and query processing. Graph data represent ...
Dynamic Model Generation and Semantic Search for Open Source Projects using Big Data Analytics
(2015)
the code and build an accurate model that represents the software system of the open source.
The objective of this thesis is to provide a solution to this problem by building a framework that can extract the features, identify components, connectors from...
Feature-based Analysis for Open Source using Big Data Analytics
(2015)
The open source code base has increased enormously and hence understanding the functionality of the projects has become extremely difficult. The existing approaches of feature discovery that aim to identify functionality ...