Microblogs data is the microlength user-generated data that is posted on the web, eg,
tweets, online reviews, comments on news and social media. It has gained considerable …

Location factor of recommender systems has been extensively studied in the past decade.
However, there is no research thoroughly analyzing location's role in news …

A multi-model database (MMDB) is designed to support multiple data models against a
single, integrated back-end. Examples of data models include document, graph, relational …

We introduce Auto-Surprise1, an automated recommender system library. Auto-Surprise is
an extension of the Surprise recommender system library and eases the algorithm selection …

Today, in information technologies, the direction associated with the use of Data Warehouse
(DW) is evolving very dynamically. Using DW, it is possible to implement two types of data …

Graph is a famous data structure that has prevalent applications in the real world, including
social networks, biological networks, and computer networks. In these applications, graph …

Estimating the join selectivity is a crucial problem in many aspects of query processing, such
as query optimization and query refinement. Selectivity estimation has been extensively …

Recommendation systems are a key part of almost every modern consumer website.
Recommender systems include techniques to filter, explore and rank a huge amount of …

Key-value databases are widely used to store the features or metadata generated from the
neural network based video processing platforms. Due to the large volumes of video data …

Recommender systems are ubiquitous in the modern internet, where they help users find
items they might like. A widely deployed recommendation approach is item-based …