Integrating Collaborate and Content-Based Filtering for Personalized Information Recommendation View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2005

AUTHORS

Zhiyun Xin , Jizhong Zhao , Ming Gu , Jiaguang Sun

ABSTRACT

To achieve high quality of push-based information service, in this paper, collaborative filtering and content-based adaptability approaches are surveyed for user-centered personalized information, then based on the above method, we proposed a mixed two-phased recommendation algorithm for high-quality information recommendation, upon which performance evaluations showed that the mixed algorithm is more efficient than pure content-based or collaborative filtering methods, for pure of either approaches is not so efficient for the lack of enough information need information. And moreover we found with large amount registered users, it is necessary and important for the system to serve users in a group mode, which involved merged retrieval issues. More... »

PAGES

476-482

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/11596448_70

DOI

http://dx.doi.org/10.1007/11596448_70

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1017532413


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/2008/08", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Information and Computing Sciences", 
        "type": "DefinedTerm"
      }, 
      {
        "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"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "School of Software, Tsinghua University, 100084, Beijing, China", 
          "id": "http://www.grid.ac/institutes/grid.12527.33", 
          "name": [
            "Department of Computer Science and Technology, Tsinghua University, 100084, Beijing, China", 
            "School of Software, Tsinghua University, 100084, Beijing, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Xin", 
        "givenName": "Zhiyun", 
        "id": "sg:person.011747356017.46", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011747356017.46"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Computer Science and Technology, Xi\u2019an Jiaotong University, 710049, Xi\u2019an, China", 
          "id": "http://www.grid.ac/institutes/grid.43169.39", 
          "name": [
            "Department of Computer Science and Technology, Xi\u2019an Jiaotong University, 710049, Xi\u2019an, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Zhao", 
        "givenName": "Jizhong", 
        "id": "sg:person.010342130521.42", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010342130521.42"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "School of Software, Tsinghua University, 100084, Beijing, China", 
          "id": "http://www.grid.ac/institutes/grid.12527.33", 
          "name": [
            "School of Software, Tsinghua University, 100084, Beijing, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Gu", 
        "givenName": "Ming", 
        "id": "sg:person.015646302766.82", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015646302766.82"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "School of Software, Tsinghua University, 100084, Beijing, China", 
          "id": "http://www.grid.ac/institutes/grid.12527.33", 
          "name": [
            "School of Software, Tsinghua University, 100084, Beijing, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Sun", 
        "givenName": "Jiaguang", 
        "id": "sg:person.011411464635.59", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011411464635.59"
        ], 
        "type": "Person"
      }
    ], 
    "datePublished": "2005", 
    "datePublishedReg": "2005-01-01", 
    "description": "To achieve high quality of push-based information service, in this paper, collaborative filtering and content-based adaptability approaches are surveyed for user-centered personalized information, then based on the above method, we proposed a mixed two-phased recommendation algorithm for high-quality information recommendation, upon which performance evaluations showed that the mixed algorithm is more efficient than pure content-based or collaborative filtering methods, for pure of either approaches is not so efficient for the lack of enough information need information. And moreover we found with large amount registered users, it is necessary and important for the system to serve users in a group mode, which involved merged retrieval issues.", 
    "editor": [
      {
        "familyName": "Hao", 
        "givenName": "Yue", 
        "type": "Person"
      }, 
      {
        "familyName": "Liu", 
        "givenName": "Jiming", 
        "type": "Person"
      }, 
      {
        "familyName": "Wang", 
        "givenName": "Yuping", 
        "type": "Person"
      }, 
      {
        "familyName": "Cheung", 
        "givenName": "Yiu-ming", 
        "type": "Person"
      }, 
      {
        "familyName": "Yin", 
        "givenName": "Hujun", 
        "type": "Person"
      }, 
      {
        "familyName": "Jiao", 
        "givenName": "Licheng", 
        "type": "Person"
      }, 
      {
        "familyName": "Ma", 
        "givenName": "Jianfeng", 
        "type": "Person"
      }, 
      {
        "familyName": "Jiao", 
        "givenName": "Yong-Chang", 
        "type": "Person"
      }
    ], 
    "genre": "chapter", 
    "id": "sg:pub.10.1007/11596448_70", 
    "inLanguage": "en", 
    "isAccessibleForFree": false, 
    "isPartOf": {
      "isbn": [
        "978-3-540-30818-8", 
        "978-3-540-31599-5"
      ], 
      "name": "Computational Intelligence and Security", 
      "type": "Book"
    }, 
    "keywords": [
      "information recommendation", 
      "personalized information recommendation", 
      "collaborative filtering methods", 
      "recommendation algorithm", 
      "collaborative filtering", 
      "retrieval issues", 
      "personalized information", 
      "information services", 
      "adaptability approach", 
      "mixed algorithm", 
      "performance evaluation", 
      "filtering method", 
      "users", 
      "algorithm", 
      "enough information", 
      "filtering", 
      "information", 
      "large amount", 
      "high quality", 
      "above method", 
      "group modes", 
      "collaborate", 
      "services", 
      "method", 
      "system", 
      "issues", 
      "quality", 
      "recommendations", 
      "evaluation", 
      "amount", 
      "lack", 
      "content", 
      "mode", 
      "approach", 
      "paper", 
      "push-based information service", 
      "content-based adaptability approaches", 
      "user-centered personalized information", 
      "high-quality information recommendation", 
      "merged retrieval issues", 
      "Integrating Collaborate"
    ], 
    "name": "Integrating Collaborate and Content-Based Filtering for Personalized Information Recommendation", 
    "pagination": "476-482", 
    "productId": [
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1017532413"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/11596448_70"
        ]
      }
    ], 
    "publisher": {
      "name": "Springer Nature", 
      "type": "Organisation"
    }, 
    "sameAs": [
      "https://doi.org/10.1007/11596448_70", 
      "https://app.dimensions.ai/details/publication/pub.1017532413"
    ], 
    "sdDataset": "chapters", 
    "sdDatePublished": "2022-01-01T19:28", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-springernature-scigraph/baseset/20220101/entities/gbq_results/chapter/chapter_85.jsonl", 
    "type": "Chapter", 
    "url": "https://doi.org/10.1007/11596448_70"
  }
]
 

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.10.1007/11596448_70'

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

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/11596448_70'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/11596448_70'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/11596448_70'


 

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

161 TRIPLES      23 PREDICATES      67 URIs      60 LITERALS      7 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/11596448_70 schema:about anzsrc-for:08
2 anzsrc-for:0806
3 schema:author Na61b15e079634961a27ab2e7fcfb5c25
4 schema:datePublished 2005
5 schema:datePublishedReg 2005-01-01
6 schema:description To achieve high quality of push-based information service, in this paper, collaborative filtering and content-based adaptability approaches are surveyed for user-centered personalized information, then based on the above method, we proposed a mixed two-phased recommendation algorithm for high-quality information recommendation, upon which performance evaluations showed that the mixed algorithm is more efficient than pure content-based or collaborative filtering methods, for pure of either approaches is not so efficient for the lack of enough information need information. And moreover we found with large amount registered users, it is necessary and important for the system to serve users in a group mode, which involved merged retrieval issues.
7 schema:editor N6793c383c6fa480d9f7a9c10e77378b7
8 schema:genre chapter
9 schema:inLanguage en
10 schema:isAccessibleForFree false
11 schema:isPartOf Naa6c710d0d1845108d4fa86ad28d4f10
12 schema:keywords Integrating Collaborate
13 above method
14 adaptability approach
15 algorithm
16 amount
17 approach
18 collaborate
19 collaborative filtering
20 collaborative filtering methods
21 content
22 content-based adaptability approaches
23 enough information
24 evaluation
25 filtering
26 filtering method
27 group modes
28 high quality
29 high-quality information recommendation
30 information
31 information recommendation
32 information services
33 issues
34 lack
35 large amount
36 merged retrieval issues
37 method
38 mixed algorithm
39 mode
40 paper
41 performance evaluation
42 personalized information
43 personalized information recommendation
44 push-based information service
45 quality
46 recommendation algorithm
47 recommendations
48 retrieval issues
49 services
50 system
51 user-centered personalized information
52 users
53 schema:name Integrating Collaborate and Content-Based Filtering for Personalized Information Recommendation
54 schema:pagination 476-482
55 schema:productId N3e53141bf72345f899d939fa375046e9
56 Na7be5562628f46529e4e59eccc96674f
57 schema:publisher Ne56b77bf04e54be5a376f873dec42780
58 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017532413
59 https://doi.org/10.1007/11596448_70
60 schema:sdDatePublished 2022-01-01T19:28
61 schema:sdLicense https://scigraph.springernature.com/explorer/license/
62 schema:sdPublisher N4c40fd2d9fab4e1cad160e43dd56e885
63 schema:url https://doi.org/10.1007/11596448_70
64 sgo:license sg:explorer/license/
65 sgo:sdDataset chapters
66 rdf:type schema:Chapter
67 N2ef084ac2a76411c9301e754001dea68 rdf:first sg:person.011411464635.59
68 rdf:rest rdf:nil
69 N3e53141bf72345f899d939fa375046e9 schema:name dimensions_id
70 schema:value pub.1017532413
71 rdf:type schema:PropertyValue
72 N4068c42d24c74d34b344b9d9a75789d9 rdf:first Nf8e6923e111d4a00adfa28242f504319
73 rdf:rest N7d5ed492369d47eda9bd0433a737312c
74 N4538332da6de46aa9da5158fda3cd4a7 rdf:first Nbbb9fd1173f84a56b8eb5b7e08c1ff80
75 rdf:rest N4068c42d24c74d34b344b9d9a75789d9
76 N4c40fd2d9fab4e1cad160e43dd56e885 schema:name Springer Nature - SN SciGraph project
77 rdf:type schema:Organization
78 N5cc99c3570214058b6fab07243d8c88f rdf:first Ne4cd79f39d394d338a4ff82cee11d02e
79 rdf:rest rdf:nil
80 N6793c383c6fa480d9f7a9c10e77378b7 rdf:first Nca3b70c53c2847a984aa541cc623c8e8
81 rdf:rest Neeb46958367040b59d5a9f102bc2544b
82 N6e262fab0a7348718856fefd8717dfcc schema:familyName Liu
83 schema:givenName Jiming
84 rdf:type schema:Person
85 N7d5ed492369d47eda9bd0433a737312c rdf:first N82efefdd4f89482a99c811af3e3ec3c0
86 rdf:rest Naa9bde6bfe424fc8881f3a682ca3a870
87 N82efefdd4f89482a99c811af3e3ec3c0 schema:familyName Yin
88 schema:givenName Hujun
89 rdf:type schema:Person
90 N88f82d16fd3c455798d9449aa5f7f1fe schema:familyName Ma
91 schema:givenName Jianfeng
92 rdf:type schema:Person
93 N8ef994e907f0463fa40609d2d9fb00d5 rdf:first sg:person.015646302766.82
94 rdf:rest N2ef084ac2a76411c9301e754001dea68
95 Na61b15e079634961a27ab2e7fcfb5c25 rdf:first sg:person.011747356017.46
96 rdf:rest Nbf64c523146b46a0ac00032c636310c6
97 Na7be5562628f46529e4e59eccc96674f schema:name doi
98 schema:value 10.1007/11596448_70
99 rdf:type schema:PropertyValue
100 Naa6c710d0d1845108d4fa86ad28d4f10 schema:isbn 978-3-540-30818-8
101 978-3-540-31599-5
102 schema:name Computational Intelligence and Security
103 rdf:type schema:Book
104 Naa9bde6bfe424fc8881f3a682ca3a870 rdf:first Nff4980cecdeb49079517e461bd74c0dc
105 rdf:rest Nac3fda44682c403ab45c782e72ed59c4
106 Nac3fda44682c403ab45c782e72ed59c4 rdf:first N88f82d16fd3c455798d9449aa5f7f1fe
107 rdf:rest N5cc99c3570214058b6fab07243d8c88f
108 Nbbb9fd1173f84a56b8eb5b7e08c1ff80 schema:familyName Wang
109 schema:givenName Yuping
110 rdf:type schema:Person
111 Nbf64c523146b46a0ac00032c636310c6 rdf:first sg:person.010342130521.42
112 rdf:rest N8ef994e907f0463fa40609d2d9fb00d5
113 Nca3b70c53c2847a984aa541cc623c8e8 schema:familyName Hao
114 schema:givenName Yue
115 rdf:type schema:Person
116 Ne4cd79f39d394d338a4ff82cee11d02e schema:familyName Jiao
117 schema:givenName Yong-Chang
118 rdf:type schema:Person
119 Ne56b77bf04e54be5a376f873dec42780 schema:name Springer Nature
120 rdf:type schema:Organisation
121 Neeb46958367040b59d5a9f102bc2544b rdf:first N6e262fab0a7348718856fefd8717dfcc
122 rdf:rest N4538332da6de46aa9da5158fda3cd4a7
123 Nf8e6923e111d4a00adfa28242f504319 schema:familyName Cheung
124 schema:givenName Yiu-ming
125 rdf:type schema:Person
126 Nff4980cecdeb49079517e461bd74c0dc schema:familyName Jiao
127 schema:givenName Licheng
128 rdf:type schema:Person
129 anzsrc-for:08 schema:inDefinedTermSet anzsrc-for:
130 schema:name Information and Computing Sciences
131 rdf:type schema:DefinedTerm
132 anzsrc-for:0806 schema:inDefinedTermSet anzsrc-for:
133 schema:name Information Systems
134 rdf:type schema:DefinedTerm
135 sg:person.010342130521.42 schema:affiliation grid-institutes:grid.43169.39
136 schema:familyName Zhao
137 schema:givenName Jizhong
138 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010342130521.42
139 rdf:type schema:Person
140 sg:person.011411464635.59 schema:affiliation grid-institutes:grid.12527.33
141 schema:familyName Sun
142 schema:givenName Jiaguang
143 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011411464635.59
144 rdf:type schema:Person
145 sg:person.011747356017.46 schema:affiliation grid-institutes:grid.12527.33
146 schema:familyName Xin
147 schema:givenName Zhiyun
148 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011747356017.46
149 rdf:type schema:Person
150 sg:person.015646302766.82 schema:affiliation grid-institutes:grid.12527.33
151 schema:familyName Gu
152 schema:givenName Ming
153 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015646302766.82
154 rdf:type schema:Person
155 grid-institutes:grid.12527.33 schema:alternateName School of Software, Tsinghua University, 100084, Beijing, China
156 schema:name Department of Computer Science and Technology, Tsinghua University, 100084, Beijing, China
157 School of Software, Tsinghua University, 100084, Beijing, China
158 rdf:type schema:Organization
159 grid-institutes:grid.43169.39 schema:alternateName Department of Computer Science and Technology, Xi’an Jiaotong University, 710049, Xi’an, China
160 schema:name Department of Computer Science and Technology, Xi’an Jiaotong University, 710049, Xi’an, China
161 rdf:type schema:Organization
 




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


...