Estimating feature ratings through an effective review selection approach View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2014-02

AUTHORS

Chong Long, Jie Zhang, Minlie Huang, Xiaoyan Zhu, Ming Li, Bin Ma

ABSTRACT

Most participatory web sites collect overall ratings (e.g., five stars) of products from their customers, reflecting the overall assessment of the products. However, it is more useful to present ratings of product features (such as price, battery, screen, and lens of digital cameras) to help customers make effective purchase decisions. Unfortunately, only a very few web sites have collected feature ratings. In this paper, we propose a novel approach to accurately estimate feature ratings of products. This approach selects user reviews that extensively discuss specific features of the products (called specialized reviews), using information distance of reviews on the features. Experiments on both annotated and real data show that overall ratings of the specialized reviews can be used to represent their feature ratings. The average of these overall ratings can be used by recommender systems to provide feature-specific recommendations that can better help users make purchasing decisions. More... »

PAGES

419-446

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s10115-012-0495-8

DOI

http://dx.doi.org/10.1007/s10115-012-0495-8

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1010872905


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/2008/0806", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Information Systems", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/08", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Information and Computing Sciences", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "name": [
            "Yahoo! Labs, Beijing, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Long", 
        "givenName": "Chong", 
        "id": "sg:person.016323300540.57", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016323300540.57"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Nanyang Technological University", 
          "id": "https://www.grid.ac/institutes/grid.59025.3b", 
          "name": [
            "School of Computer Engineering, Nanyang Technological University, Singapore, Singapore"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Zhang", 
        "givenName": "Jie", 
        "id": "sg:person.013333040065.17", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013333040065.17"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Tsinghua University", 
          "id": "https://www.grid.ac/institutes/grid.12527.33", 
          "name": [
            "State Key Laboratory of Intelligent Technology and Systems, Department of Computer Science and Technology, Tsinghua National Laboratory for Information Science and Technology, Tsinghua University, 100084, Beijing, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Huang", 
        "givenName": "Minlie", 
        "id": "sg:person.012400674023.95", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012400674023.95"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Tsinghua University", 
          "id": "https://www.grid.ac/institutes/grid.12527.33", 
          "name": [
            "State Key Laboratory of Intelligent Technology and Systems, Department of Computer Science and Technology, Tsinghua National Laboratory for Information Science and Technology, Tsinghua University, 100084, Beijing, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Zhu", 
        "givenName": "Xiaoyan", 
        "id": "sg:person.013176254423.92", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013176254423.92"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of Waterloo", 
          "id": "https://www.grid.ac/institutes/grid.46078.3d", 
          "name": [
            "School of Computer Science, University of Waterloo, Waterloo, Canada"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Li", 
        "givenName": "Ming", 
        "id": "sg:person.0621576316.79", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0621576316.79"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of Waterloo", 
          "id": "https://www.grid.ac/institutes/grid.46078.3d", 
          "name": [
            "School of Computer Science, University of Waterloo, Waterloo, Canada"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Ma", 
        "givenName": "Bin", 
        "id": "sg:person.01221430663.16", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01221430663.16"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "sg:pub.10.1007/s10115-010-0376-y", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1000880292", 
          "https://doi.org/10.1007/s10115-010-0376-y"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10115-010-0338-4", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1000886995", 
          "https://doi.org/10.1007/s10115-010-0338-4"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1145/1014052.1014073", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1001058137"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/bioinformatics/17.2.149", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1009738168"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1145/1281192.1281285", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1010331285"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1145/1835804.1835903", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1019648855"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/bioinformatics/btl388", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1023443175"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://app.dimensions.ai/details/publication/pub.1025044546", 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-1-4757-2606-0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1025044546", 
          "https://doi.org/10.1007/978-1-4757-2606-0"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-1-4757-2606-0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1025044546", 
          "https://doi.org/10.1007/978-1-4757-2606-0"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.3115/979617.979640", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1028372173"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1145/1250910.1250931", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1029512545"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1145/1458082.1458242", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1035549514"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10115-010-0361-5", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1037594702", 
          "https://doi.org/10.1007/s10115-010-0361-5"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.3115/1220575.1220618", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1037746441"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1145/336992.337035", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1038908704"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1145/775047.775053", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1040379396"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1145/775152.775226", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1043544321"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1145/643477.643478", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1048466628"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1145/1183614.1183625", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1048570732"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/scientificamerican0603-76", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1056544393", 
          "https://doi.org/10.1038/scientificamerican0603-76"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/18.681318", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061100692"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/tit.2004.838101", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061650298"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/tkde.2007.48", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061661815"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/icdm.2008.94", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1094000153"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/wi-iat.2009.38", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1095669560"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.3115/1218955.1218990", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1099221218"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.3115/1218955.1218990", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1099221218"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.3115/1690219.1690249", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1099238581"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.3115/1610075.1610135", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1099244314"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2014-02", 
    "datePublishedReg": "2014-02-01", 
    "description": "Most participatory web sites collect overall ratings (e.g., five stars) of products from their customers, reflecting the overall assessment of the products. However, it is more useful to present ratings of product features (such as price, battery, screen, and lens of digital cameras) to help customers make effective purchase decisions. Unfortunately, only a very few web sites have collected feature ratings. In this paper, we propose a novel approach to accurately estimate feature ratings of products. This approach selects user reviews that extensively discuss specific features of the products (called specialized reviews), using information distance of reviews on the features. Experiments on both annotated and real data show that overall ratings of the specialized reviews can be used to represent their feature ratings. The average of these overall ratings can be used by recommender systems to provide feature-specific recommendations that can better help users make purchasing decisions.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1007/s10115-012-0495-8", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isPartOf": [
      {
        "id": "sg:journal.1041769", 
        "issn": [
          "0219-1377", 
          "0219-3116"
        ], 
        "name": "Knowledge and Information Systems", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "2", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "38"
      }
    ], 
    "name": "Estimating feature ratings through an effective review selection approach", 
    "pagination": "419-446", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "33cd4ddaf96ffa9b57720cc3f895a3b6e89d39e7115371db742ef9eb9fa225bf"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/s10115-012-0495-8"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1010872905"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/s10115-012-0495-8", 
      "https://app.dimensions.ai/details/publication/pub.1010872905"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-10T22:31", 
    "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_8690_00000511.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "http://link.springer.com/10.1007%2Fs10115-012-0495-8"
  }
]
 

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/s10115-012-0495-8'

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/s10115-012-0495-8'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s10115-012-0495-8'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s10115-012-0495-8'


 

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

192 TRIPLES      21 PREDICATES      55 URIs      19 LITERALS      7 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/s10115-012-0495-8 schema:about anzsrc-for:08
2 anzsrc-for:0806
3 schema:author N0d561a32990045d39eaf16e802dc6afb
4 schema:citation sg:pub.10.1007/978-1-4757-2606-0
5 sg:pub.10.1007/s10115-010-0338-4
6 sg:pub.10.1007/s10115-010-0361-5
7 sg:pub.10.1007/s10115-010-0376-y
8 sg:pub.10.1038/scientificamerican0603-76
9 https://app.dimensions.ai/details/publication/pub.1025044546
10 https://doi.org/10.1093/bioinformatics/17.2.149
11 https://doi.org/10.1093/bioinformatics/btl388
12 https://doi.org/10.1109/18.681318
13 https://doi.org/10.1109/icdm.2008.94
14 https://doi.org/10.1109/tit.2004.838101
15 https://doi.org/10.1109/tkde.2007.48
16 https://doi.org/10.1109/wi-iat.2009.38
17 https://doi.org/10.1145/1014052.1014073
18 https://doi.org/10.1145/1183614.1183625
19 https://doi.org/10.1145/1250910.1250931
20 https://doi.org/10.1145/1281192.1281285
21 https://doi.org/10.1145/1458082.1458242
22 https://doi.org/10.1145/1835804.1835903
23 https://doi.org/10.1145/336992.337035
24 https://doi.org/10.1145/643477.643478
25 https://doi.org/10.1145/775047.775053
26 https://doi.org/10.1145/775152.775226
27 https://doi.org/10.3115/1218955.1218990
28 https://doi.org/10.3115/1220575.1220618
29 https://doi.org/10.3115/1610075.1610135
30 https://doi.org/10.3115/1690219.1690249
31 https://doi.org/10.3115/979617.979640
32 schema:datePublished 2014-02
33 schema:datePublishedReg 2014-02-01
34 schema:description Most participatory web sites collect overall ratings (e.g., five stars) of products from their customers, reflecting the overall assessment of the products. However, it is more useful to present ratings of product features (such as price, battery, screen, and lens of digital cameras) to help customers make effective purchase decisions. Unfortunately, only a very few web sites have collected feature ratings. In this paper, we propose a novel approach to accurately estimate feature ratings of products. This approach selects user reviews that extensively discuss specific features of the products (called specialized reviews), using information distance of reviews on the features. Experiments on both annotated and real data show that overall ratings of the specialized reviews can be used to represent their feature ratings. The average of these overall ratings can be used by recommender systems to provide feature-specific recommendations that can better help users make purchasing decisions.
35 schema:genre research_article
36 schema:inLanguage en
37 schema:isAccessibleForFree false
38 schema:isPartOf N210c779db62346e081371889f072c616
39 Nd5494622d5f345edb1475594481df9d9
40 sg:journal.1041769
41 schema:name Estimating feature ratings through an effective review selection approach
42 schema:pagination 419-446
43 schema:productId N00ec6b2861774b9e9518d9b69f24c882
44 N2a79b7a6512240d5905c6a41e0100890
45 N56adad7ee5bd45bcb2c4c0b8dfeb4cd6
46 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010872905
47 https://doi.org/10.1007/s10115-012-0495-8
48 schema:sdDatePublished 2019-04-10T22:31
49 schema:sdLicense https://scigraph.springernature.com/explorer/license/
50 schema:sdPublisher N5de76fd60a4243bb9e8a4743b4b66094
51 schema:url http://link.springer.com/10.1007%2Fs10115-012-0495-8
52 sgo:license sg:explorer/license/
53 sgo:sdDataset articles
54 rdf:type schema:ScholarlyArticle
55 N00ec6b2861774b9e9518d9b69f24c882 schema:name readcube_id
56 schema:value 33cd4ddaf96ffa9b57720cc3f895a3b6e89d39e7115371db742ef9eb9fa225bf
57 rdf:type schema:PropertyValue
58 N0d561a32990045d39eaf16e802dc6afb rdf:first sg:person.016323300540.57
59 rdf:rest Nc7fefd4687004701984eb5b74ed24059
60 N0e70d8dd17ff4bf8a13124dc17cf1a4d rdf:first sg:person.013176254423.92
61 rdf:rest Nf3f25b9ccd944686acd42bc367454bde
62 N210c779db62346e081371889f072c616 schema:volumeNumber 38
63 rdf:type schema:PublicationVolume
64 N2a79b7a6512240d5905c6a41e0100890 schema:name dimensions_id
65 schema:value pub.1010872905
66 rdf:type schema:PropertyValue
67 N470bc040a56d434b9405e1fdc4182f90 rdf:first sg:person.012400674023.95
68 rdf:rest N0e70d8dd17ff4bf8a13124dc17cf1a4d
69 N56adad7ee5bd45bcb2c4c0b8dfeb4cd6 schema:name doi
70 schema:value 10.1007/s10115-012-0495-8
71 rdf:type schema:PropertyValue
72 N5de76fd60a4243bb9e8a4743b4b66094 schema:name Springer Nature - SN SciGraph project
73 rdf:type schema:Organization
74 N6efe208a8b7c459594cb5b4f8cbcc882 rdf:first sg:person.01221430663.16
75 rdf:rest rdf:nil
76 Nc7fefd4687004701984eb5b74ed24059 rdf:first sg:person.013333040065.17
77 rdf:rest N470bc040a56d434b9405e1fdc4182f90
78 Nd5494622d5f345edb1475594481df9d9 schema:issueNumber 2
79 rdf:type schema:PublicationIssue
80 Neae6caad45d7400b84953def873285d5 schema:name Yahoo! Labs, Beijing, China
81 rdf:type schema:Organization
82 Nf3f25b9ccd944686acd42bc367454bde rdf:first sg:person.0621576316.79
83 rdf:rest N6efe208a8b7c459594cb5b4f8cbcc882
84 anzsrc-for:08 schema:inDefinedTermSet anzsrc-for:
85 schema:name Information and Computing Sciences
86 rdf:type schema:DefinedTerm
87 anzsrc-for:0806 schema:inDefinedTermSet anzsrc-for:
88 schema:name Information Systems
89 rdf:type schema:DefinedTerm
90 sg:journal.1041769 schema:issn 0219-1377
91 0219-3116
92 schema:name Knowledge and Information Systems
93 rdf:type schema:Periodical
94 sg:person.01221430663.16 schema:affiliation https://www.grid.ac/institutes/grid.46078.3d
95 schema:familyName Ma
96 schema:givenName Bin
97 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01221430663.16
98 rdf:type schema:Person
99 sg:person.012400674023.95 schema:affiliation https://www.grid.ac/institutes/grid.12527.33
100 schema:familyName Huang
101 schema:givenName Minlie
102 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012400674023.95
103 rdf:type schema:Person
104 sg:person.013176254423.92 schema:affiliation https://www.grid.ac/institutes/grid.12527.33
105 schema:familyName Zhu
106 schema:givenName Xiaoyan
107 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013176254423.92
108 rdf:type schema:Person
109 sg:person.013333040065.17 schema:affiliation https://www.grid.ac/institutes/grid.59025.3b
110 schema:familyName Zhang
111 schema:givenName Jie
112 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013333040065.17
113 rdf:type schema:Person
114 sg:person.016323300540.57 schema:affiliation Neae6caad45d7400b84953def873285d5
115 schema:familyName Long
116 schema:givenName Chong
117 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016323300540.57
118 rdf:type schema:Person
119 sg:person.0621576316.79 schema:affiliation https://www.grid.ac/institutes/grid.46078.3d
120 schema:familyName Li
121 schema:givenName Ming
122 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0621576316.79
123 rdf:type schema:Person
124 sg:pub.10.1007/978-1-4757-2606-0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025044546
125 https://doi.org/10.1007/978-1-4757-2606-0
126 rdf:type schema:CreativeWork
127 sg:pub.10.1007/s10115-010-0338-4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1000886995
128 https://doi.org/10.1007/s10115-010-0338-4
129 rdf:type schema:CreativeWork
130 sg:pub.10.1007/s10115-010-0361-5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037594702
131 https://doi.org/10.1007/s10115-010-0361-5
132 rdf:type schema:CreativeWork
133 sg:pub.10.1007/s10115-010-0376-y schema:sameAs https://app.dimensions.ai/details/publication/pub.1000880292
134 https://doi.org/10.1007/s10115-010-0376-y
135 rdf:type schema:CreativeWork
136 sg:pub.10.1038/scientificamerican0603-76 schema:sameAs https://app.dimensions.ai/details/publication/pub.1056544393
137 https://doi.org/10.1038/scientificamerican0603-76
138 rdf:type schema:CreativeWork
139 https://app.dimensions.ai/details/publication/pub.1025044546 schema:CreativeWork
140 https://doi.org/10.1093/bioinformatics/17.2.149 schema:sameAs https://app.dimensions.ai/details/publication/pub.1009738168
141 rdf:type schema:CreativeWork
142 https://doi.org/10.1093/bioinformatics/btl388 schema:sameAs https://app.dimensions.ai/details/publication/pub.1023443175
143 rdf:type schema:CreativeWork
144 https://doi.org/10.1109/18.681318 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061100692
145 rdf:type schema:CreativeWork
146 https://doi.org/10.1109/icdm.2008.94 schema:sameAs https://app.dimensions.ai/details/publication/pub.1094000153
147 rdf:type schema:CreativeWork
148 https://doi.org/10.1109/tit.2004.838101 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061650298
149 rdf:type schema:CreativeWork
150 https://doi.org/10.1109/tkde.2007.48 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061661815
151 rdf:type schema:CreativeWork
152 https://doi.org/10.1109/wi-iat.2009.38 schema:sameAs https://app.dimensions.ai/details/publication/pub.1095669560
153 rdf:type schema:CreativeWork
154 https://doi.org/10.1145/1014052.1014073 schema:sameAs https://app.dimensions.ai/details/publication/pub.1001058137
155 rdf:type schema:CreativeWork
156 https://doi.org/10.1145/1183614.1183625 schema:sameAs https://app.dimensions.ai/details/publication/pub.1048570732
157 rdf:type schema:CreativeWork
158 https://doi.org/10.1145/1250910.1250931 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029512545
159 rdf:type schema:CreativeWork
160 https://doi.org/10.1145/1281192.1281285 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010331285
161 rdf:type schema:CreativeWork
162 https://doi.org/10.1145/1458082.1458242 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035549514
163 rdf:type schema:CreativeWork
164 https://doi.org/10.1145/1835804.1835903 schema:sameAs https://app.dimensions.ai/details/publication/pub.1019648855
165 rdf:type schema:CreativeWork
166 https://doi.org/10.1145/336992.337035 schema:sameAs https://app.dimensions.ai/details/publication/pub.1038908704
167 rdf:type schema:CreativeWork
168 https://doi.org/10.1145/643477.643478 schema:sameAs https://app.dimensions.ai/details/publication/pub.1048466628
169 rdf:type schema:CreativeWork
170 https://doi.org/10.1145/775047.775053 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040379396
171 rdf:type schema:CreativeWork
172 https://doi.org/10.1145/775152.775226 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043544321
173 rdf:type schema:CreativeWork
174 https://doi.org/10.3115/1218955.1218990 schema:sameAs https://app.dimensions.ai/details/publication/pub.1099221218
175 rdf:type schema:CreativeWork
176 https://doi.org/10.3115/1220575.1220618 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037746441
177 rdf:type schema:CreativeWork
178 https://doi.org/10.3115/1610075.1610135 schema:sameAs https://app.dimensions.ai/details/publication/pub.1099244314
179 rdf:type schema:CreativeWork
180 https://doi.org/10.3115/1690219.1690249 schema:sameAs https://app.dimensions.ai/details/publication/pub.1099238581
181 rdf:type schema:CreativeWork
182 https://doi.org/10.3115/979617.979640 schema:sameAs https://app.dimensions.ai/details/publication/pub.1028372173
183 rdf:type schema:CreativeWork
184 https://www.grid.ac/institutes/grid.12527.33 schema:alternateName Tsinghua University
185 schema:name State Key Laboratory of Intelligent Technology and Systems, Department of Computer Science and Technology, Tsinghua National Laboratory for Information Science and Technology, Tsinghua University, 100084, Beijing, China
186 rdf:type schema:Organization
187 https://www.grid.ac/institutes/grid.46078.3d schema:alternateName University of Waterloo
188 schema:name School of Computer Science, University of Waterloo, Waterloo, Canada
189 rdf:type schema:Organization
190 https://www.grid.ac/institutes/grid.59025.3b schema:alternateName Nanyang Technological University
191 schema:name School of Computer Engineering, Nanyang Technological University, Singapore, Singapore
192 rdf:type schema:Organization
 




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


...