Network science is the field dedicated to the investigation and analysis of complex systems
via their representations as networks. We normally model such networks as graphs: sets of …

We describe a problem in complex networks we call the Node Vector Distance (NVD)
problem, and we survey algorithms currently able to address it. Complex networks are a …

Time series arise in many different applications in the form of sensor data, stocks data,
videos, and other time-related information. Analysis of this data typically requires searching …

Given a set of entities, the all-pairs similarity search aims at identifying all pairs of entities
that have similarity greater than (or distance smaller than) some user-defined threshold. In …

Earth Mover's Distance (EMD), as a similarity measure, has received a lot of attention in the
fields of multimedia and probabilistic databases, computer vision, image retrieval, machine …

The amount of spatial data in open data portals has increased rapidly, raising the demand
for spatial dataset search in large data repositories. In this paper, we tackle spatial dataset …

The Earth Mover's Distance (EMD) was developed in computer vision as a flexible similarity
model that utilizes similarities in feature space to define a high quality similarity measure in …

In data mining applications such as subspace clustering or feature selection, changes to the
underlying feature set can require the reconstruction of search indices to support …

Querying uncertain data sets (represented as probability distributions) presents many
challenges due to the large amount of data involved and the difficulties comparing …

Concomitant with the digital information age, an increasing amount of multimedia data is
generated, processed, and finally stored in very large multimedia data collections. The …