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The interaction paradigm offered by most contemporary Web Information Systems is a <i>search-and-sift</i> paradigm in which users manually seek information using hyperlinked documents. This paradigm is derived from a document-centric model that gives users minimal support for scanning through high volumes of text. We present a novel information exploration(More)
BACKGROUND Literature-based discovery (LBD) is characterized by uncovering hidden associations in non-interacting scientific literature. Prior approaches to LBD include use of: (1) domain expertise and structured background knowledge to manually filter and explore the literature, (2) distributional statistics and graph-theoretic measures to rank interesting(More)
AIMS Many websites provide a means for individuals to share their experiences and knowledge about different drugs. Such User-Generated Content (UGC) can be a rich data source to study emerging drug use practices and trends. This study examined UGC on extra-medical use of loperamide among illicit opioid users. METHODS A website that allows for the free(More)
OBJECTIVES The role of social media in biomedical knowledge mining, including clinical, medical and healthcare informatics, prescription drug abuse epidemiology and drug pharmacology, has become increasingly significant in recent years. Social media offers opportunities for people to share opinions and experiences freely in online communities, which may(More)
We present an application for analyzing temporal and spatial interaction in an Association Network environment based on integrating Global Positioning Systems (GPS) Data, RDF Metadata and Data Mining. We argue that GPS data contains important information about relationships between people, through location and time, and can ultimately provide ideas about(More)
We present ideas for determining the expertise of researchers across various areas of computer science and for finding relevant experts/reviewers in a peer-review setting. We explain how Semantic Web techniques for data collection and data representation using ontologies can be used in addressing this specific " ExpertFinder " problem.
OBJECTIVES This paper presents a methodology for recovering and decomposing Swanson's Raynaud Syndrome-Fish Oil hypothesis semi-automatically. The methodology leverages the semantics of assertions extracted from biomedical literature (called semantic predications) along with structured background knowledge and graph-based algorithms to semi-automatically(More)
In this paper, we present a Data Management Tool called ES3N, which uses Semantic Web techniques to manage and query data collected from a mini-dome Sensor Network. Our tool supports complex queries on both continuous and archival data, by capturing important associations among data, collected and stored in a distributed dynamic ontology. The motivation(More)
Detection of trends is important in a variety of areas. Scientific research is no exception. While several methods have been proposed for trend detection , we argue that there is value on using semantics-based techniques. In particular, we demonstrate the value of using a taxonomy of topics together with data extraction to create a dataset relating(More)
While contemporary semantic search systems offer to improve classical keyword-based search, they are not always adequate for complex domain specific information needs. The domain of prescription drug abuse, for example, requires knowledge of both ontological concepts and "intelligible constructs" not typically modeled in ontologies. These intelligible(More)