• Citations Per Year
Learn More
The big data era is witnessing a prevalent shift of data from homogeneous to heterogeneous, from isolated to linked. Exemplar outcomes of this shift are a wide range of graph data such as information, social, and knowledge graphs. The unique characteristics of graph data are challenging traditional search techniques like SQL and keyword search. Graph query(More)
Social media data are amenable to representation by directed graphs. A node represents an entity in the social network such as a person, organization, location, or event. A link between two nodes represents a relationship such as communication, participation, or financial support. When stored in a database, these graphs can be searched and analyzed for(More)
Millions of people exchange user-generated information through online social media (SM) services. The prevalence of SM use globally and its growing significance to the evolution of events has attracted the attention of many agencies, from humanitarian non-government organizations (NGOs) and disaster response agencies to homeland security and(More)
Expert networks are formed by a group of expert-professionals with different specialties to collaboratively resolve specific queries posted to the network. In expert networks, decentralized search, operating purely on each expert's local information without any knowledge of network global structure, represents the most basic and scalable routing mechanism.(More)
Examining the relation between global microlending and corruption may inform how trust and influence propogate through crowds. Building this understanding may help U.S. Army intelligence officers leverage crowds for humanitarian efforts as well as, to detect signs of adversarial influence. A dataset was created combining open source data from Kiva, a(More)
Measures of sentiment can help refine a Warfighter’s knowledge and understanding of an unfamiliar operational environment, for example, the sentiment of civilians and insurgents to the Army, its operations, or its adversaries. In addition, observing changes in expressed sentiment about topics over time may provide baselines from which to detect if and when(More)
Expert networks are formed by a group of expert-profes\-sionals with different specialties to collaboratively resolve specific queries. In such networks, when a query reaches an expert who does not have sufficient expertise, this query needs to be routed to other experts for further processing until it is completely solved; therefore, query answering(More)
We investigate the problem of query answering in expert networks, which are composed of inter-connected experts with various specialties. Upon receiving a query, the expert network is tasked to route this query to experts with sufficient expertise in a timely and reliable manner. However, the efficiency of query answering depends on the underlying query(More)
  • 1