This textbook explores the different aspects of data mining from the fundamentals to the
complex data types and their applications, capturing the wide diversity of problem domains …

Graph-based text representation is one of the important preprocessing steps in data and text
mining, Natural Language Processing (NLP), and information retrieval approaches. The …

Given a query graph q and a data graph g, the subgraph isomorphism search finds all
occurrences of q in g and is considered one of the most fundamental query types for many …

Balanced graph partitioning in the streaming setting is a key problem to enable scalable and
efficient computations on massive graph data such as web graphs, knowledge graphs, and …

Finding subgraph isomorphisms is an important problem in many applications which deal
with data modeled as graphs. While this problem is NP-hard, in recent years, many …

A growing set of on-line applications are generating data that can be viewed as very large
collections of small, dense social graphs---these range from sets of social groups, events, or …

We witness an unprecedented proliferation of knowledge graphs that record millions of
entities and their relationships. While knowledge graphs are structure-flexible and content …

It is increasingly common to find real-life data represented as networks of labeled,
heterogeneous entities. To query these networks, one often needs to identify the matches of …

Knowledge graphs (KGs) such as DBpedia, Freebase, YAGO, Wikidata, and NELL were
constructed to store large-scale, real-world facts as (subject, predicate, object) triples-that …

Graphs are fundamental data structures and have been employed for centuries to model
real-world systems and phenomena. Random walk with restart (RWR) provides a good …