The use of graphs in analytic environments is getting more and more widespread, with applications in many different environments like social network analysis, fraud detection, industrial management, knowledge analysis, etc. Graph databases are one important solution to consider in the management of large datasets. The course will be oriented to tackle four important aspects of graph management. First, to give a characterization of graphs and the most common operations applied on them. Second, to review the technologies for graph management and focus on the particular case of Sparksee. Third, to analyze in depth some important applications and how graphs are used to solve them. Fourth, to understand the use of benchmarking to make the requir...
Several graph databases provide support to analyze a large amount of highly connected data, and it i...
<p>With the proliferation of large irregular sparse relational datasets, new storage and analysis pl...
Walke D, Micheel D, Schallert K, et al. The importance ofgraph databases andgraph learning forclinic...
Data analysis, data management, and big data play a major role in both social and business perspecti...
Part 1: Full Keynote and Invited PapersInternational audienceReal world data offers a lot of possibi...
In the recent years many real-world applications have been modeled by graph structures (e.g., social...
Abstract: For a long time, data has been typically stored in tabular form so as to increase the inde...
The take up of graph databases is slowed because practitioners find it hard to think about data stor...
Graph data is used in an increasing number of analytical data processing applications, ranging from ...
Abstract. Graph Database Management systems (GDBs) are gaining popularity. They are used to analyze ...
International audienceGraph data modeling and querying arises in many practical application domains ...
Graph data modeling and querying arises in many practical application domains such as social and bio...
Graph Database Management systems (GDBs) are gaining popularity. They are used to analyze huge graph...
This special issue of IT Professional focuses on the graph database. The graph database, a relativel...
Graph processing has become an important part of multiple areas of computer science, such as machine...
Several graph databases provide support to analyze a large amount of highly connected data, and it i...
<p>With the proliferation of large irregular sparse relational datasets, new storage and analysis pl...
Walke D, Micheel D, Schallert K, et al. The importance ofgraph databases andgraph learning forclinic...
Data analysis, data management, and big data play a major role in both social and business perspecti...
Part 1: Full Keynote and Invited PapersInternational audienceReal world data offers a lot of possibi...
In the recent years many real-world applications have been modeled by graph structures (e.g., social...
Abstract: For a long time, data has been typically stored in tabular form so as to increase the inde...
The take up of graph databases is slowed because practitioners find it hard to think about data stor...
Graph data is used in an increasing number of analytical data processing applications, ranging from ...
Abstract. Graph Database Management systems (GDBs) are gaining popularity. They are used to analyze ...
International audienceGraph data modeling and querying arises in many practical application domains ...
Graph data modeling and querying arises in many practical application domains such as social and bio...
Graph Database Management systems (GDBs) are gaining popularity. They are used to analyze huge graph...
This special issue of IT Professional focuses on the graph database. The graph database, a relativel...
Graph processing has become an important part of multiple areas of computer science, such as machine...
Several graph databases provide support to analyze a large amount of highly connected data, and it i...
<p>With the proliferation of large irregular sparse relational datasets, new storage and analysis pl...
Walke D, Micheel D, Schallert K, et al. The importance ofgraph databases andgraph learning forclinic...