Graph querying, graph motif mining and the discovery of clusters


Ontology type: sgo:Patent     


Patent Info

DATE

2013-03-12T00:00

AUTHORS

SINGH AMBUJ KUMAR , HE HUAHAI , RANU SAYAN

ABSTRACT

A method for analyzing, querying, and mining graph databases using subgraph and similarity querying. An index structure, known as a closure tree, is defined for topological summarization of a set of graphs. In addition, a significance model is created in which the graphs are transformed into histograms of primitive components. Finally, connected substructures or clusters, comprising paths or trees, are detected in networks found in the graph databases using a random walk technique and a repeated random walk technique. More... »

JSON-LD is the canonical representation for SciGraph data.

TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

[
  {
    "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
    "about": [
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/08", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0806", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "name": "SINGH AMBUJ KUMAR", 
        "type": "Person"
      }, 
      {
        "name": "HE HUAHAI", 
        "type": "Person"
      }, 
      {
        "name": "RANU SAYAN", 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "sg:pub.10.1038/415141a", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1001484556", 
          "https://doi.org/10.1038/415141a"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/35001009", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1035773549", 
          "https://doi.org/10.1038/35001009"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nature750", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1017837373", 
          "https://doi.org/10.1038/nature750"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/gb-2004-5-5-r35", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1052229286", 
          "https://doi.org/10.1186/gb-2004-5-5-r35"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/415180a", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1005267371", 
          "https://doi.org/10.1038/415180a"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2013-03-12T00:00", 
    "description": "

A method for analyzing, querying, and mining graph databases using subgraph and similarity querying. An index structure, known as a closure tree, is defined for topological summarization of a set of graphs. In addition, a significance model is created in which the graphs are transformed into histograms of primitive components. Finally, connected substructures or clusters, comprising paths or trees, are detected in networks found in the graph databases using a random walk technique and a repeated random walk technique.

", "endDate": "2027-02-27", "id": "sg:patent.US-8396884-B2", "name": "Graph querying, graph motif mining and the discovery of clusters", "recipient": [ { "id": "http://www.grid.ac/institutes/grid.30389.31", "type": "Organization" } ], "sameAs": [ "https://app.dimensions.ai/details/patent/US-8396884-B2" ], "sdDataset": "patents", "sdDatePublished": "2022-10-01T07:03", "sdLicense": "https://scigraph.springernature.com/explorer/license/", "sdPublisher": { "name": "Springer Nature - SN SciGraph project", "type": "Organization" }, "sdSource": "s3://com-springernature-scigraph/baseset/20221001/entities/gbq_results/patent/patent_2.jsonl", "type": "Patent" } ]
 

Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/patent.US-8396884-B2'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/patent.US-8396884-B2'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/patent.US-8396884-B2'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/patent.US-8396884-B2'


 

This table displays all metadata directly associated to this object as RDF triples.

54 TRIPLES      15 PREDICATES      21 URIs      9 LITERALS      2 BLANK NODES

Subject Predicate Object
1 sg:patent.US-8396884-B2 schema:about anzsrc-for:08
2 anzsrc-for:0806
3 schema:author N9c9997b7b7f0439eb4df23b21e0c6c31
4 schema:citation sg:pub.10.1038/35001009
5 sg:pub.10.1038/415141a
6 sg:pub.10.1038/415180a
7 sg:pub.10.1038/nature750
8 sg:pub.10.1186/gb-2004-5-5-r35
9 schema:datePublished 2013-03-12T00:00
10 schema:description <p num="p-0001">A method for analyzing, querying, and mining graph databases using subgraph and similarity querying. An index structure, known as a closure tree, is defined for topological summarization of a set of graphs. In addition, a significance model is created in which the graphs are transformed into histograms of primitive components. Finally, connected substructures or clusters, comprising paths or trees, are detected in networks found in the graph databases using a random walk technique and a repeated random walk technique.</p>
11 schema:endDate 2027-02-27
12 schema:name Graph querying, graph motif mining and the discovery of clusters
13 schema:recipient grid-institutes:grid.30389.31
14 schema:sameAs https://app.dimensions.ai/details/patent/US-8396884-B2
15 schema:sdDatePublished 2022-10-01T07:03
16 schema:sdLicense https://scigraph.springernature.com/explorer/license/
17 schema:sdPublisher N3e07e816818e42f68aab55bebeb0f839
18 sgo:license sg:explorer/license/
19 sgo:sdDataset patents
20 rdf:type sgo:Patent
21 N3e07e816818e42f68aab55bebeb0f839 schema:name Springer Nature - SN SciGraph project
22 rdf:type schema:Organization
23 N444a4bf7874346f787edd69a1f2b2e39 rdf:first Nf1420aa1431042228f0854996678cfa6
24 rdf:rest rdf:nil
25 N491d9aabf5e34681af31986fd305a9dc schema:name HE HUAHAI
26 rdf:type schema:Person
27 N6495940909734e06bca0cd0e0ad6813d rdf:first N491d9aabf5e34681af31986fd305a9dc
28 rdf:rest N444a4bf7874346f787edd69a1f2b2e39
29 N9c9997b7b7f0439eb4df23b21e0c6c31 rdf:first Ndcf1880c2c8b4417a6c27735ba1eef33
30 rdf:rest N6495940909734e06bca0cd0e0ad6813d
31 Ndcf1880c2c8b4417a6c27735ba1eef33 schema:name SINGH AMBUJ KUMAR
32 rdf:type schema:Person
33 Nf1420aa1431042228f0854996678cfa6 schema:name RANU SAYAN
34 rdf:type schema:Person
35 anzsrc-for:08 schema:inDefinedTermSet anzsrc-for:
36 rdf:type schema:DefinedTerm
37 anzsrc-for:0806 schema:inDefinedTermSet anzsrc-for:
38 rdf:type schema:DefinedTerm
39 sg:pub.10.1038/35001009 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035773549
40 https://doi.org/10.1038/35001009
41 rdf:type schema:CreativeWork
42 sg:pub.10.1038/415141a schema:sameAs https://app.dimensions.ai/details/publication/pub.1001484556
43 https://doi.org/10.1038/415141a
44 rdf:type schema:CreativeWork
45 sg:pub.10.1038/415180a schema:sameAs https://app.dimensions.ai/details/publication/pub.1005267371
46 https://doi.org/10.1038/415180a
47 rdf:type schema:CreativeWork
48 sg:pub.10.1038/nature750 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017837373
49 https://doi.org/10.1038/nature750
50 rdf:type schema:CreativeWork
51 sg:pub.10.1186/gb-2004-5-5-r35 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052229286
52 https://doi.org/10.1186/gb-2004-5-5-r35
53 rdf:type schema:CreativeWork
54 grid-institutes:grid.30389.31 schema:Organization
 




Preview window. Press ESC to close (or click here)


...