Search

As data in many disciplines continues to grow at a frantic pace, a more heterogeneous set of information sources both can and need to be connected in innovative ways to improve information search and recommendation systems. Using information retrieval (IR) as an example, classical search techniques are based on limited information, including query terms, the content of documents, and basic user characteristics. However, recent studies have started to investigate additional information resources, including semantic web data, knowledge graphs, linguistic features, user email account content, social networks, user behavior, the search context, and other sources. Intuitively, a heterogeneous graph integrating all these information sources could enhance search performance. However, the complexity of such graphs challenge most existing graph mining algorithms. In this study, we propose a novel approach for a personalized random walk over a complex heterogeneous graph; which we refer to as Personalized Graph Navigation (PGN). Unlike earlier expert-guided random walk approaches, by using an EM framework, PGN estimates the personalized usefulness probability distribution for each edge type (the latent variable), which can be used as a random walk navigation profile for a user on a heterogeneous graph. While PGN can cope with information retrieval/recommendation problems at a low cost, this method also transforms a complex heterogeneous graph into a homogeneous graph, allowing existing homogeneous graph mining algorithms to be applied to a heterogeneous graph.

Digital repositories are grappling with an influx of scientific data brought about by the well publicized "data deluge" in science, business, and society. One particularly perplexing problem is the long-term archival and reuse of complex data sets. This paper presents an integrated approach to data discovery over heterogeneous data resources in social-ecological systems research. Social-ecological systems data is complex because the research draws from both social and natural sciences. Using a sample set of data resources from the domain, we explore an approach to discovery and representation of this data. Specifically, we develop an ontology-based process of organization and visualization from a data-centric perspective. We define data resources broadly and identify six key categories of resources that include data collected from site visits to shared ecological resources, the structure of research instruments, domain concepts, research designs, publications, theories and models. We identify the underlying relationships and construct an ontology that captures these relationships using semantic web languages. The ontology and a NoSQL data store at the back end store the data resource instances. These are integrated into a portal architecture we refer to as the Integrated Visualization of Social-Ecological Resources (IViSER) that allows users to both browse the relationships captured in the ontology and easily visualize the granular details of data resources.

The mobile handset (and now tablet) market is coming a tangled mess, with strong advocates for device specific applications on the one hand and strong web standards within the browser on the other. This talk will reflect a bit on the history of mobile applications, focusing on the user issues involved in this debate. This is critical as too often the debate focuses on the business needs of application development.The mobile space has gone through, and will continue to go through profound shifts in technology and user capabilities. This talk will focus on the heterogeneous set of devices that will descend upon us all, a 'zombie apocalypse' of devices that will swarm upon us and upset the simple 'one app, one device' model that we still so quaintly adhere to today.

We are developing a system to be implemented at Continuing Care Retirement Communities (CCRCs) throughout the United States in an effort to encourage ride-sharing among residents in order to decrease their carbon emissions. We are focusing on senior citizens for two reasons. they are a growing segment of the population with driving habits that result in higher pollution, but they are also a population that is at risk of isolation and the mental and physical harm that can result from being isolated. Our system addresses both of these issues while leveraging the infrastructure and culture of CCRCs in addition to hiding the technology from the senior residents themselves.