This paper introduces Memory-limited Online Subspace Estimation Scheme (MOSES) for both estimating the principal components of streaming data and reducing its dimension. More specifically, in various applications such as sensor networks, the data vectors a ...
The heterogeneity of today's Web sources requires information retrieval (IR) systems to handle multi-modal queries. Such queries define a user's information needs by different data modalities, such as keywords, hashtags, user profiles, and other media. Rec ...
Computing the count of distinct elements in large data sets is a common task but naive approaches are memory-expensive. The HyperLogLog (HLL) algorithm (Flajolet et al., 2007) estimates a data set's cardinality while using significantly less memory than a ...
For years, immersive interfaces using virtual and augmented reality (AR) for molecular visualization and modeling have promised a revolution in the way how we teach, learn, communicate and work in chemistry, structural biology and related areas. However, m ...
Modern applications accumulate data at an exponentially increasing rate and traditional database systems struggle to keep up.
Decision support systems used in industry, rely heavily on data analysis, and require real-time responses irrespective of data siz ...
Testing mutual independence among several random vectors of arbitrary dimensions is a challenging problem in Statistics, and it has gained considerable interest in recent years. In this article, we propose some nonparametric tests based on different notion ...
Wearable sweat sensing systems offer non-invasive and real-time bio-data streaming solutions. They open the possibility for continuous monitoring of biomarkers' concentrations as well as their variation in sweat, which is a complementary to current passive ...
The Web constitutes a valuable source of information. In recent years, it fostered the construction of large-scale knowledge bases, such as Freebase, YAGO, and DBpedia. The open nature of the Web, with content potentially being generated by everyone, howev ...
The growing demand for data-intensive decision support and the migration to multi-tenant infrastructures put databases under the stress of high analytical query load. The requirement for high throughput contradicts the traditional design of query-at-a-time ...
The Web constitutes a valuable source of information. In recent years, it fostered the construction of large-scale knowledge bases, such as Freebase, YAGO, and DBpedia. The open nature of the Web, with content potentially being generated by everyone, howev ...
The proliferation of phasor measurement units (PMUs) presents new challenges in archiving and processing large amounts of synchrophasor data which necessitates advanced data compression methods. This paper proposes a singular value decomposition (SVD)-base ...
The phenomenal growth of graph data from a wide variety of real-world applications has rendered graph querying to be a problem of paramount importance. Traditional techniques use structural as well as node similarities to find matches of a given query grap ...
Live-streaming platforms broadcast user-generated video in real-time. Recommendation on these platforms shares similarities with traditional settings, such as a large volume of heterogeneous content and highly skewed interaction distributions. However, sev ...
With the current exponential growth of video-based social networks, video retrieval using natural language is receiving ever-increasing attention. Most existing approaches tackle this task by extracting individual frame-level spatial features to represent ...
As one of the Web's primary multilingual knowledge sources, Wikipedia is read by millions of people across the globe every day. Despite this global readership, little is known about why users read Wikipedia's various language editions. To bridge this gap, ...
