Behavioral Analyses of Information Diffusion Models by Observed Data of Social Network View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2010

AUTHORS

Kazumi Saito , Masahiro Kimura , Kouzou Ohara , Hiroshi Motoda

ABSTRACT

We investigate how well different information diffusion models explain observation data by learning their parameters and performing behavioral analyses. We use two models (CTIC, CTLT) that incorporate continuous time delay and are extension of well known Independent Cascade (IC) and Linear Threshold (LT) models. We first focus on parameter learning of CTLT model that is not known so far, and apply it to two kinds of tasks: ranking influential nodes and behavioral analysis of topic propagation, and compare the results with CTIC model together with conventional heuristics that do not consider diffusion phenomena. We show that it is important to use models and the ranking accuracy is highly sensitive to the model used but the propagation speed of topics that are derived from the learned parameter values is rather insensitive to the model used. More... »

PAGES

149-158

Book

TITLE

Advances in Social Computing

ISBN

978-3-642-12078-7
978-3-642-12079-4

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-642-12079-4_20

DOI

http://dx.doi.org/10.1007/978-3-642-12079-4_20

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1039831213


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", 
    "about": [
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0104", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Statistics", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/01", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Mathematical Sciences", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "name": [
            "School of Administration and Informatics, University of Shizuoka, 52-1 Yada, Suruga-ku, 422-8526, Shizuoka, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Saito", 
        "givenName": "Kazumi", 
        "id": "sg:person.012577673231.47", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012577673231.47"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Ryukoku University", 
          "id": "https://www.grid.ac/institutes/grid.440926.d", 
          "name": [
            "Department of Electronics and Informatics, Ryukoku University, 520-2194, Otsu, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Kimura", 
        "givenName": "Masahiro", 
        "id": "sg:person.012170741307.01", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012170741307.01"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Aoyama Gakuin University", 
          "id": "https://www.grid.ac/institutes/grid.252311.6", 
          "name": [
            "Department of Integrated Information Technology, Aoyama Gakuin University, 229-8558, Kanagawa, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Ohara", 
        "givenName": "Kouzou", 
        "id": "sg:person.012040713771.24", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012040713771.24"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Osaka University", 
          "id": "https://www.grid.ac/institutes/grid.136593.b", 
          "name": [
            "Institute of Scientific and Industrial Research, Osaka University, 8-1 Mihogaoka, Ibaraki, 567-0047, Osaka, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Motoda", 
        "givenName": "Hiroshi", 
        "id": "sg:person.016251026775.26", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016251026775.26"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1073/pnas.082090499", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1007102528"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1086/518527", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1008151665"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1023/a:1011122126881", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1026494708", 
          "https://doi.org/10.1023/a:1011122126881"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1145/1046456.1046462", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1029449434"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-1-4419-0056-2_18", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1029584764", 
          "https://doi.org/10.1007/978-1-4419-0056-2_18"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-1-4419-0056-2_18", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1029584764", 
          "https://doi.org/10.1007/978-1-4419-0056-2_18"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nature03607", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1032155732", 
          "https://doi.org/10.1038/nature03607"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nature03607", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1032155732", 
          "https://doi.org/10.1038/nature03607"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nature03607", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1032155732", 
          "https://doi.org/10.1038/nature03607"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1145/956750.956769", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1034921751"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0169-7552(98)00110-x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1035913093"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1145/1134707.1134732", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1038160839"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1145/1514888.1514892", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1038900392"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-3-540-30115-8_22", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1044538060", 
          "https://doi.org/10.1007/978-3-540-30115-8_22"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-3-540-30115-8_22", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1044538060", 
          "https://doi.org/10.1007/978-3-540-30115-8_22"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-3-642-05224-8_25", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1052443337", 
          "https://doi.org/10.1007/978-3-642-05224-8_25"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physreve.66.035101", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1060728988"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physreve.66.035101", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1060728988"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/mis.2005.16", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061405800"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1137/s003614450342480", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1062877811"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1137/s003614450342480", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1062877811"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/wi.2005.151", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1093320920"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1017/cbo9780511815478", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1098700813"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2010", 
    "datePublishedReg": "2010-01-01", 
    "description": "We investigate how well different information diffusion models explain observation data by learning their parameters and performing behavioral analyses. We use two models (CTIC, CTLT) that incorporate continuous time delay and are extension of well known Independent Cascade (IC) and Linear Threshold (LT) models. We first focus on parameter learning of CTLT model that is not known so far, and apply it to two kinds of tasks: ranking influential nodes and behavioral analysis of topic propagation, and compare the results with CTIC model together with conventional heuristics that do not consider diffusion phenomena. We show that it is important to use models and the ranking accuracy is highly sensitive to the model used but the propagation speed of topics that are derived from the learned parameter values is rather insensitive to the model used.", 
    "editor": [
      {
        "familyName": "Chai", 
        "givenName": "Sun-Ki", 
        "type": "Person"
      }, 
      {
        "familyName": "Salerno", 
        "givenName": "John J.", 
        "type": "Person"
      }, 
      {
        "familyName": "Mabry", 
        "givenName": "Patricia L.", 
        "type": "Person"
      }
    ], 
    "genre": "chapter", 
    "id": "sg:pub.10.1007/978-3-642-12079-4_20", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isPartOf": {
      "isbn": [
        "978-3-642-12078-7", 
        "978-3-642-12079-4"
      ], 
      "name": "Advances in Social Computing", 
      "type": "Book"
    }, 
    "name": "Behavioral Analyses of Information Diffusion Models by Observed Data of Social Network", 
    "pagination": "149-158", 
    "productId": [
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1039831213"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/978-3-642-12079-4_20"
        ]
      }, 
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "bdbcda99bb7cac711d9c1d23881977e5dab78433f9f05debcc8d7e0cac346a34"
        ]
      }
    ], 
    "publisher": {
      "location": "Berlin, Heidelberg", 
      "name": "Springer Berlin Heidelberg", 
      "type": "Organisation"
    }, 
    "sameAs": [
      "https://doi.org/10.1007/978-3-642-12079-4_20", 
      "https://app.dimensions.ai/details/publication/pub.1039831213"
    ], 
    "sdDataset": "chapters", 
    "sdDatePublished": "2019-04-16T07:35", 
    "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/v90/0000000357_0000000357/records_99299_00000001.jsonl", 
    "type": "Chapter", 
    "url": "https://link.springer.com/10.1007%2F978-3-642-12079-4_20"
  }
]
 

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.10.1007/978-3-642-12079-4_20'

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

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/978-3-642-12079-4_20'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/978-3-642-12079-4_20'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/978-3-642-12079-4_20'


 

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

160 TRIPLES      23 PREDICATES      44 URIs      20 LITERALS      8 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/978-3-642-12079-4_20 schema:about anzsrc-for:01
2 anzsrc-for:0104
3 schema:author N754f1ce2e2cb416ebbddb47857a045d0
4 schema:citation sg:pub.10.1007/978-1-4419-0056-2_18
5 sg:pub.10.1007/978-3-540-30115-8_22
6 sg:pub.10.1007/978-3-642-05224-8_25
7 sg:pub.10.1023/a:1011122126881
8 sg:pub.10.1038/nature03607
9 https://doi.org/10.1016/s0169-7552(98)00110-x
10 https://doi.org/10.1017/cbo9780511815478
11 https://doi.org/10.1073/pnas.082090499
12 https://doi.org/10.1086/518527
13 https://doi.org/10.1103/physreve.66.035101
14 https://doi.org/10.1109/mis.2005.16
15 https://doi.org/10.1109/wi.2005.151
16 https://doi.org/10.1137/s003614450342480
17 https://doi.org/10.1145/1046456.1046462
18 https://doi.org/10.1145/1134707.1134732
19 https://doi.org/10.1145/1514888.1514892
20 https://doi.org/10.1145/956750.956769
21 schema:datePublished 2010
22 schema:datePublishedReg 2010-01-01
23 schema:description We investigate how well different information diffusion models explain observation data by learning their parameters and performing behavioral analyses. We use two models (CTIC, CTLT) that incorporate continuous time delay and are extension of well known Independent Cascade (IC) and Linear Threshold (LT) models. We first focus on parameter learning of CTLT model that is not known so far, and apply it to two kinds of tasks: ranking influential nodes and behavioral analysis of topic propagation, and compare the results with CTIC model together with conventional heuristics that do not consider diffusion phenomena. We show that it is important to use models and the ranking accuracy is highly sensitive to the model used but the propagation speed of topics that are derived from the learned parameter values is rather insensitive to the model used.
24 schema:editor Ne4763571eeb042f48c62ccfcde4dbd60
25 schema:genre chapter
26 schema:inLanguage en
27 schema:isAccessibleForFree false
28 schema:isPartOf N90a8c2f2b0c7454698db25e7ff24ea1f
29 schema:name Behavioral Analyses of Information Diffusion Models by Observed Data of Social Network
30 schema:pagination 149-158
31 schema:productId Nba9adc0bea27440180ffc361753708ea
32 Nc2f85b6387514ecc88251f453dbae65b
33 Nf6932bdc37fb44058ecb34ecfd068cad
34 schema:publisher Ncd1e15feabce45c492c616fea5eb8a16
35 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039831213
36 https://doi.org/10.1007/978-3-642-12079-4_20
37 schema:sdDatePublished 2019-04-16T07:35
38 schema:sdLicense https://scigraph.springernature.com/explorer/license/
39 schema:sdPublisher N2ea9fc48886148d99d4104435a86bc2c
40 schema:url https://link.springer.com/10.1007%2F978-3-642-12079-4_20
41 sgo:license sg:explorer/license/
42 sgo:sdDataset chapters
43 rdf:type schema:Chapter
44 N2828fd82b4cf4988a9df017a0e0d6e35 schema:familyName Mabry
45 schema:givenName Patricia L.
46 rdf:type schema:Person
47 N2ea9fc48886148d99d4104435a86bc2c schema:name Springer Nature - SN SciGraph project
48 rdf:type schema:Organization
49 N34f72e1789bd4937958b5323e3af855b rdf:first sg:person.016251026775.26
50 rdf:rest rdf:nil
51 N50e9a31b2c93433d8b92b7431566dd79 schema:name School of Administration and Informatics, University of Shizuoka, 52-1 Yada, Suruga-ku, 422-8526, Shizuoka, Japan
52 rdf:type schema:Organization
53 N5cf72dce86014e0887f9fad2519aeb07 rdf:first N2828fd82b4cf4988a9df017a0e0d6e35
54 rdf:rest rdf:nil
55 N750afd1e937843c08d41169966f3b934 schema:familyName Chai
56 schema:givenName Sun-Ki
57 rdf:type schema:Person
58 N754f1ce2e2cb416ebbddb47857a045d0 rdf:first sg:person.012577673231.47
59 rdf:rest Nb0ab16473e55418db820c9e7036ff801
60 N7925162669a84fe5bc5704c8bf1adcbd rdf:first Ne2c1c70eb8dd4c0a8966c29e2c98eaa9
61 rdf:rest N5cf72dce86014e0887f9fad2519aeb07
62 N90a8c2f2b0c7454698db25e7ff24ea1f schema:isbn 978-3-642-12078-7
63 978-3-642-12079-4
64 schema:name Advances in Social Computing
65 rdf:type schema:Book
66 N9d145f2363eb4f0bbe17db8db2a66aae rdf:first sg:person.012040713771.24
67 rdf:rest N34f72e1789bd4937958b5323e3af855b
68 Nb0ab16473e55418db820c9e7036ff801 rdf:first sg:person.012170741307.01
69 rdf:rest N9d145f2363eb4f0bbe17db8db2a66aae
70 Nba9adc0bea27440180ffc361753708ea schema:name doi
71 schema:value 10.1007/978-3-642-12079-4_20
72 rdf:type schema:PropertyValue
73 Nc2f85b6387514ecc88251f453dbae65b schema:name readcube_id
74 schema:value bdbcda99bb7cac711d9c1d23881977e5dab78433f9f05debcc8d7e0cac346a34
75 rdf:type schema:PropertyValue
76 Ncd1e15feabce45c492c616fea5eb8a16 schema:location Berlin, Heidelberg
77 schema:name Springer Berlin Heidelberg
78 rdf:type schema:Organisation
79 Ne2c1c70eb8dd4c0a8966c29e2c98eaa9 schema:familyName Salerno
80 schema:givenName John J.
81 rdf:type schema:Person
82 Ne4763571eeb042f48c62ccfcde4dbd60 rdf:first N750afd1e937843c08d41169966f3b934
83 rdf:rest N7925162669a84fe5bc5704c8bf1adcbd
84 Nf6932bdc37fb44058ecb34ecfd068cad schema:name dimensions_id
85 schema:value pub.1039831213
86 rdf:type schema:PropertyValue
87 anzsrc-for:01 schema:inDefinedTermSet anzsrc-for:
88 schema:name Mathematical Sciences
89 rdf:type schema:DefinedTerm
90 anzsrc-for:0104 schema:inDefinedTermSet anzsrc-for:
91 schema:name Statistics
92 rdf:type schema:DefinedTerm
93 sg:person.012040713771.24 schema:affiliation https://www.grid.ac/institutes/grid.252311.6
94 schema:familyName Ohara
95 schema:givenName Kouzou
96 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012040713771.24
97 rdf:type schema:Person
98 sg:person.012170741307.01 schema:affiliation https://www.grid.ac/institutes/grid.440926.d
99 schema:familyName Kimura
100 schema:givenName Masahiro
101 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012170741307.01
102 rdf:type schema:Person
103 sg:person.012577673231.47 schema:affiliation N50e9a31b2c93433d8b92b7431566dd79
104 schema:familyName Saito
105 schema:givenName Kazumi
106 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012577673231.47
107 rdf:type schema:Person
108 sg:person.016251026775.26 schema:affiliation https://www.grid.ac/institutes/grid.136593.b
109 schema:familyName Motoda
110 schema:givenName Hiroshi
111 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016251026775.26
112 rdf:type schema:Person
113 sg:pub.10.1007/978-1-4419-0056-2_18 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029584764
114 https://doi.org/10.1007/978-1-4419-0056-2_18
115 rdf:type schema:CreativeWork
116 sg:pub.10.1007/978-3-540-30115-8_22 schema:sameAs https://app.dimensions.ai/details/publication/pub.1044538060
117 https://doi.org/10.1007/978-3-540-30115-8_22
118 rdf:type schema:CreativeWork
119 sg:pub.10.1007/978-3-642-05224-8_25 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052443337
120 https://doi.org/10.1007/978-3-642-05224-8_25
121 rdf:type schema:CreativeWork
122 sg:pub.10.1023/a:1011122126881 schema:sameAs https://app.dimensions.ai/details/publication/pub.1026494708
123 https://doi.org/10.1023/a:1011122126881
124 rdf:type schema:CreativeWork
125 sg:pub.10.1038/nature03607 schema:sameAs https://app.dimensions.ai/details/publication/pub.1032155732
126 https://doi.org/10.1038/nature03607
127 rdf:type schema:CreativeWork
128 https://doi.org/10.1016/s0169-7552(98)00110-x schema:sameAs https://app.dimensions.ai/details/publication/pub.1035913093
129 rdf:type schema:CreativeWork
130 https://doi.org/10.1017/cbo9780511815478 schema:sameAs https://app.dimensions.ai/details/publication/pub.1098700813
131 rdf:type schema:CreativeWork
132 https://doi.org/10.1073/pnas.082090499 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007102528
133 rdf:type schema:CreativeWork
134 https://doi.org/10.1086/518527 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008151665
135 rdf:type schema:CreativeWork
136 https://doi.org/10.1103/physreve.66.035101 schema:sameAs https://app.dimensions.ai/details/publication/pub.1060728988
137 rdf:type schema:CreativeWork
138 https://doi.org/10.1109/mis.2005.16 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061405800
139 rdf:type schema:CreativeWork
140 https://doi.org/10.1109/wi.2005.151 schema:sameAs https://app.dimensions.ai/details/publication/pub.1093320920
141 rdf:type schema:CreativeWork
142 https://doi.org/10.1137/s003614450342480 schema:sameAs https://app.dimensions.ai/details/publication/pub.1062877811
143 rdf:type schema:CreativeWork
144 https://doi.org/10.1145/1046456.1046462 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029449434
145 rdf:type schema:CreativeWork
146 https://doi.org/10.1145/1134707.1134732 schema:sameAs https://app.dimensions.ai/details/publication/pub.1038160839
147 rdf:type schema:CreativeWork
148 https://doi.org/10.1145/1514888.1514892 schema:sameAs https://app.dimensions.ai/details/publication/pub.1038900392
149 rdf:type schema:CreativeWork
150 https://doi.org/10.1145/956750.956769 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034921751
151 rdf:type schema:CreativeWork
152 https://www.grid.ac/institutes/grid.136593.b schema:alternateName Osaka University
153 schema:name Institute of Scientific and Industrial Research, Osaka University, 8-1 Mihogaoka, Ibaraki, 567-0047, Osaka, Japan
154 rdf:type schema:Organization
155 https://www.grid.ac/institutes/grid.252311.6 schema:alternateName Aoyama Gakuin University
156 schema:name Department of Integrated Information Technology, Aoyama Gakuin University, 229-8558, Kanagawa, Japan
157 rdf:type schema:Organization
158 https://www.grid.ac/institutes/grid.440926.d schema:alternateName Ryukoku University
159 schema:name Department of Electronics and Informatics, Ryukoku University, 520-2194, Otsu, Japan
160 rdf:type schema:Organization
 




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


...