Reverse Hypothesis Machine Learning View Full Text


Ontology type: schema:Book     


Book Info

DATE

2017

GENRE

Monograph

AUTHORS

Parag Kulkarni

PUBLISHER

Springer International Publishing

ABSTRACT

N/A

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-319-55312-2

DOI

http://dx.doi.org/10.1007/978-3-319-55312-2

ISBN

978-3-319-55311-5 | 978-3-319-55312-2

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1084706168


Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
Incoming Citations Browse incoming citations for this publication using opencitations.net

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", 
    "author": [
      {
        "familyName": "Kulkarni", 
        "givenName": "Parag", 
        "type": "Person"
      }
    ], 
    "datePublished": "2017", 
    "datePublishedReg": "2017-01-01", 
    "genre": "monograph", 
    "id": "sg:pub.10.1007/978-3-319-55312-2", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isbn": [
      "978-3-319-55311-5", 
      "978-3-319-55312-2"
    ], 
    "name": "Reverse Hypothesis Machine Learning", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "8366c88835a18296ace70f97f813c4c24f0b6d6a2558eeeb8196d57ea850b9ba"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/978-3-319-55312-2"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1084706168"
        ]
      }
    ], 
    "publisher": {
      "location": "Cham", 
      "name": "Springer International Publishing", 
      "type": "Organisation"
    }, 
    "sameAs": [
      "https://doi.org/10.1007/978-3-319-55312-2", 
      "https://app.dimensions.ai/details/publication/pub.1084706168"
    ], 
    "sdDataset": "books", 
    "sdDatePublished": "2019-04-11T23:41", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000001_0000000264/records_8695_00000599.jsonl", 
    "type": "Book", 
    "url": "http://link.springer.com/10.1007/978-3-319-55312-2"
  }
]
 

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/pub.10.1007/978-3-319-55312-2'

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

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/978-3-319-55312-2'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/978-3-319-55312-2'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/978-3-319-55312-2'


 

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

41 TRIPLES      18 PREDICATES      23 URIs      18 LITERALS      6 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/978-3-319-55312-2 schema:author N759f65ba490a4fe288e8791c554e0532
2 schema:datePublished 2017
3 schema:datePublishedReg 2017-01-01
4 schema:genre monograph
5 schema:inLanguage en
6 schema:isAccessibleForFree false
7 schema:isbn 978-3-319-55311-5
8 978-3-319-55312-2
9 schema:name Reverse Hypothesis Machine Learning
10 schema:productId N8605c169eeaa4ceeae91e523d70729a9
11 Na5d3c136f7cb45ad9ad77eabde9697f7
12 Nf7b63b7f06144dd18bdd64ea105c2ebe
13 schema:publisher Nf735aa5f24fc4a488a4c502487215b58
14 schema:sameAs https://app.dimensions.ai/details/publication/pub.1084706168
15 https://doi.org/10.1007/978-3-319-55312-2
16 schema:sdDatePublished 2019-04-11T23:41
17 schema:sdLicense https://scigraph.springernature.com/explorer/license/
18 schema:sdPublisher Nccb5e5babecb4a95b4be8f2fb204b263
19 schema:url http://link.springer.com/10.1007/978-3-319-55312-2
20 sgo:license sg:explorer/license/
21 sgo:sdDataset books
22 rdf:type schema:Book
23 N759f65ba490a4fe288e8791c554e0532 rdf:first Nafd79c8819f549599c0b0205b6abf50b
24 rdf:rest rdf:nil
25 N8605c169eeaa4ceeae91e523d70729a9 schema:name doi
26 schema:value 10.1007/978-3-319-55312-2
27 rdf:type schema:PropertyValue
28 Na5d3c136f7cb45ad9ad77eabde9697f7 schema:name dimensions_id
29 schema:value pub.1084706168
30 rdf:type schema:PropertyValue
31 Nafd79c8819f549599c0b0205b6abf50b schema:familyName Kulkarni
32 schema:givenName Parag
33 rdf:type schema:Person
34 Nccb5e5babecb4a95b4be8f2fb204b263 schema:name Springer Nature - SN SciGraph project
35 rdf:type schema:Organization
36 Nf735aa5f24fc4a488a4c502487215b58 schema:location Cham
37 schema:name Springer International Publishing
38 rdf:type schema:Organisation
39 Nf7b63b7f06144dd18bdd64ea105c2ebe schema:name readcube_id
40 schema:value 8366c88835a18296ace70f97f813c4c24f0b6d6a2558eeeb8196d57ea850b9ba
41 rdf:type schema:PropertyValue
 




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


...