The world is becoming a more conjunct place and the number of data sources such as
social networks, online transactions, web search engines, and mobile devices is increasing …

Besides its NP-completeness, the strict constraints of subgraph isomorphism are making it
impractical for graph pattern matching (GPM) in the context of big data. As a result, relaxed …

Graph is a fundamental data structure that captures relationships between different data
entities. In practice, graphs are widely used for modeling complicated data in different …

RDF has constantly gained attention for data publishing due to its flexible data model,
raising the need for distributed querying. However, existing approaches using general …

Producing sports highlights is a labor-intensive work that requires some degree of
specialization. We propose a model capable of automatically generating sports highlights …

Graphs are commonly used for representing complex structures such as social relationships,
biological interactions, and knowledge bases. In many scenarios, graphs not only represent …

This paper studies fundamental problems for distributed graph simulation. Given a pattern
query Q and a graph G that is fragmented and distributed, a graph simulation algorithm A is …

Pattern matching is a powerful graph analysis tool. Unfortunately, existing solutions have
limited scalability, support only a limited set of search patterns, and/or focus on only a subset …

This paper proposes a class of graph rules for deducing associations between entities,
referred to as Graph Rules with Oracles and denoted by GROs. As opposed to previous …

In the era of big data, interest in analysis andextraction of information from large data graphs
is increasingrapidly. This paper examines the field of graph analytics fromsomewhat of a …