Method for assisting in rendering a decision using improved belief networks


Ontology type: sgo:Patent     


Patent Info

DATE

N/A

AUTHORS

David E. Heckerman , Dan Geiger , David M. Chickering

ABSTRACT

An improved belief network generator is provided. A belief network is generated utilizing expert knowledge retrieved from an expert in a given field of expertise and empirical data reflecting observations made in the given field of the expert. In addition to utilizing expert knowledge and empirical data, the belief network generator of the preferred embodiment provides for the use of continuous variables in the generated belief network and missing data in the empirical data. More... »

Related SciGraph Publications

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/2008/2746", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "name": "David E. Heckerman", 
        "type": "Person"
      }, 
      {
        "name": "Dan Geiger", 
        "type": "Person"
      }, 
      {
        "name": "David M. Chickering", 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "sg:pub.10.1007/bf00994110", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1046316965", 
          "https://doi.org/10.1007/bf00994110"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1214/ss/1177010888", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064409646"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "description": "

An improved belief network generator is provided. A belief network is generated utilizing expert knowledge retrieved from an expert in a given field of expertise and empirical data reflecting observations made in the given field of the expert. In addition to utilizing expert knowledge and empirical data, the belief network generator of the preferred embodiment provides for the use of continuous variables in the generated belief network and missing data in the empirical data.

", "id": "sg:patent.US-5696884-A", "keywords": [ "method", "belief network", "expert knowledge", "expert", "given field", "expertise", "empirical data", "observation", "embodiment", "continuous variable" ], "name": "Method for assisting in rendering a decision using improved belief networks", "recipient": [ { "id": "https://www.grid.ac/institutes/grid.419815.0", "type": "Organization" } ], "sameAs": [ "https://app.dimensions.ai/details/patent/US-5696884-A" ], "sdDataset": "patents", "sdDatePublished": "2019-03-07T15:32", "sdLicense": "https://scigraph.springernature.com/explorer/license/", "sdPublisher": { "name": "Springer Nature - SN SciGraph project", "type": "Organization" }, "sdSource": "s3://com.uberresearch.data.dev.patents-pipeline/full_run_10/sn-export/5eb3e5a348d7f117b22cc85fb0b02730/0000100128-0000348334/json_export_2d2c25e7.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-5696884-A'

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-5696884-A'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/patent.US-5696884-A'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/patent.US-5696884-A'


 

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

46 TRIPLES      14 PREDICATES      25 URIs      17 LITERALS      2 BLANK NODES

Subject Predicate Object
1 sg:patent.US-5696884-A schema:about anzsrc-for:2746
2 schema:author N8a06bbb33ed04958a84f5788daef01e2
3 schema:citation sg:pub.10.1007/bf00994110
4 https://doi.org/10.1214/ss/1177010888
5 schema:description <p>An improved belief network generator is provided. A belief network is generated utilizing expert knowledge retrieved from an expert in a given field of expertise and empirical data reflecting observations made in the given field of the expert. In addition to utilizing expert knowledge and empirical data, the belief network generator of the preferred embodiment provides for the use of continuous variables in the generated belief network and missing data in the empirical data.</p>
6 schema:keywords belief network
7 continuous variable
8 embodiment
9 empirical data
10 expert
11 expert knowledge
12 expertise
13 given field
14 method
15 observation
16 schema:name Method for assisting in rendering a decision using improved belief networks
17 schema:recipient https://www.grid.ac/institutes/grid.419815.0
18 schema:sameAs https://app.dimensions.ai/details/patent/US-5696884-A
19 schema:sdDatePublished 2019-03-07T15:32
20 schema:sdLicense https://scigraph.springernature.com/explorer/license/
21 schema:sdPublisher Ncc70f79d0f23464aba0e3acffd4b8721
22 sgo:license sg:explorer/license/
23 sgo:sdDataset patents
24 rdf:type sgo:Patent
25 N5394168afccf4014bf1cd938b86d46d8 rdf:first Nf3a54a1e8b2840fdbff2bcfac03ac074
26 rdf:rest Nb5ee89d734504ea294ee7540e9cdf05f
27 N7cd613a3c57e479ebf01fdf0c9034cc8 schema:name David M. Chickering
28 rdf:type schema:Person
29 N8a06bbb33ed04958a84f5788daef01e2 rdf:first Nafc5a7133f0f466f8d660638618527b7
30 rdf:rest N5394168afccf4014bf1cd938b86d46d8
31 Nafc5a7133f0f466f8d660638618527b7 schema:name David E. Heckerman
32 rdf:type schema:Person
33 Nb5ee89d734504ea294ee7540e9cdf05f rdf:first N7cd613a3c57e479ebf01fdf0c9034cc8
34 rdf:rest rdf:nil
35 Ncc70f79d0f23464aba0e3acffd4b8721 schema:name Springer Nature - SN SciGraph project
36 rdf:type schema:Organization
37 Nf3a54a1e8b2840fdbff2bcfac03ac074 schema:name Dan Geiger
38 rdf:type schema:Person
39 anzsrc-for:2746 schema:inDefinedTermSet anzsrc-for:
40 rdf:type schema:DefinedTerm
41 sg:pub.10.1007/bf00994110 schema:sameAs https://app.dimensions.ai/details/publication/pub.1046316965
42 https://doi.org/10.1007/bf00994110
43 rdf:type schema:CreativeWork
44 https://doi.org/10.1214/ss/1177010888 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064409646
45 rdf:type schema:CreativeWork
46 https://www.grid.ac/institutes/grid.419815.0 schema:Organization
 




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


...