A social model for Literature Access: Towards a weighted social network of authors

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This paper presents a novel retrieval approach for literature access based on social network analysis. In fact, we investigate a social model where authors represent the main entities and relationships are extracted from co-author and citation links. Moreover, we define a weighting model for social relationships which takes into account the authors positions in the social network and their mutual collaborations. Assigned weights express influence, knowledge transfer and shared interest between authors. Furthermore, we estimate document relevance by combing the document-query similarity and the document social importance derived from corresponding authors. To evaluate the effectiveness of our model, we conduct a series of experiments on a scientific document dataset that includes textual content and social data extracted from the academic social network "CiteULike". Final results show that the proposed model improves the retrieval effectiveness and outperforms traditional and social information retrieval baselines.

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A social model for Literature Access: Towards a weighted social network of authors

  1. 1. A Social Model for literature Access:<br />Towards a weighted social network of authors<br />Lamjed Ben Jabeur, Lynda Tamine and MohandBoughanem<br />IRIT, University of Paul Sabatier, Toulouse<br />{jabeur,tamine,bougha}@irit.fr<br />1<br />
  2. 2. A social model for Literature access: Towards a weighted social network <br />Overview<br />Towards Social Information Retrieval<br />A Generic Social Information Retrieval Model<br />A Social Model for Literature access<br />Experimental evaluation<br />Conclusion and future work<br />2<br />
  3. 3. 1. Towards Social Information Retrieval Model<br />1. Social Information Retrieval<br />IRS<br />Query<br />Tag<br />Comment<br />3<br />Towards SIR Model A Generic SIR Model A Social Model for LA Experimental evaluation Conclusion<br />
  4. 4. 1. Towards Social Information Retrieval Model<br />1. Social Information Retrieval<br />Information<br />Producer<br />Documents<br />Social Information Retrieval<br />Information <br />Consumer<br />Social <br />Annotations<br />R(q,d,G)<br />R(q,d)<br />4<br />Towards SIR Model A Generic SIR Model A Social Model for LA Experimental evaluation Conclusion<br />
  5. 5. 1. Towards Social Information Retrieval Model<br />1. Social Information Retrieval<br /><ul><li>Integrate social network in the retrieval process
  6. 6. Access to relevant information by exploring the social network
  7. 7. Estimate document relevance from the social context
  8. 8. Crossing two domains
  9. 9. Information Retrieval
  10. 10. Represent and compare document /query
  11. 11. Social Network Analysis
  12. 12. Represent social entities and relationships
  13. 13. Estimate individual’s centrality</li></ul>Relevant information is related to importantpersons<br />5<br />Towards SIR Model A Generic SIR Model A Social Model for LA Experimental evaluation Conclusion<br />
  14. 14. 1. Towards Social Information Retrieval Model<br />2. Domain applications of Social Information Retrieval<br />Online communities<br /><ul><li>Ranking and clustering [Handcock, 2007] [Wai, 2008] [Li, 2009]
  15. 15. Member and group similarity [Spertus, 2005]
  16. 16. Collaborative Production
  17. 17. Quality, authority (people/content) [korfatis, 2006] [Hu, 2007] [Wilkonson, 2007]
  18. 18. Knowledge sharing, transfer [Kang, 2009] [Agostini, 2003] [Hassen, 2002]
  19. 19. Finding innovation and creativity networks [Goyal, 2008]
  20. 20. Social recommender systems
  21. 21. User/ document similarity [Jamali, 2009] [Ma, 2009] [McDonald, 2009]
  22. 22. Collaborative filtering [Konstas, 2009] [Siersdorfer, 2009] [Nakamoto, 2008] [Sen, 2009]</li></ul>6<br />Towards SIR Model A Generic SIR Model A Social Model for LA Experimental evaluation Conclusion<br />
  23. 23. 1. Towards Social Information Retrieval Model<br />2. Domain applications of Social Information Retrieval<br /><ul><li>Social Networking /bookmarking
  24. 24. Tags suggestion [Budura, 2008] [Heymann, 2008] [Qu, 2008]
  25. 25. Folksonomy[Ding,2009] [Soledad,2009]
  26. 26. Expert search
  27. 27. Modeling expert network [Balog, 2006] [Karimzadehgan, 2009]
  28. 28. Expert finding [Fu,2007] [Zhang,2008]
  29. 29. People Search [Artiles, 2008] [Popescu, 2007]
  30. 30. Web Search
  31. 31. Modeling social information network [Amer-Yahia, 2007]
  32. 32. Social ranking and filtering [Jeh, 2002] [Xue, 2007]
  33. 33. Real-Time Search [Sankaranarayanany, 2009]
  34. 34. Literature Access [Mutschke, 2001] [Kirsch, 2006] [Yan, 2009]</li></ul>7<br />Towards SIR Model A Generic SIR Model A Social Model for LA Experimental evaluation Conclusion<br />
  35. 35. 1. Towards Social Information Retrieval Model<br />3. Our contribution<br /><ul><li>Generic model of social information retrieval
  36. 36. Information producing and consuming
  37. 37. Actors, data, relationships
  38. 38. Combine social relevance features
  39. 39. Specific social information for literature access
  40. 40. Social network topology
  41. 41. New entities: users and social annotations
  42. 42. New social relationships: Citations links between authors, tagging
  43. 43. A weighting model for social relationships
  44. 44. Evaluate scientific papers importance
  45. 45. Apply social importance measures on the social network of authors
  46. 46. Compare social importance measures </li></ul>8<br />Towards SIR Model A Generic SIR Model A Social Model for LA Experimental evaluation Conclusion<br />
  47. 47. 2. A Generic Social Information Retrieval Model<br />1. The Social Information Network<br /><ul><li>Actors
  48. 48. Authors, integrators
  49. 49. Users, annotators
  50. 50. Data
  51. 51. Documents
  52. 52. Social annotations
  53. 53. Social relationships
  54. 54. Implicit/Explicit
  55. 55. Directed/Undirected</li></ul>9<br />Towards SIR Model A Generic SIR Model A Social Model for LA Experimental evaluation Conclusion<br />
  56. 56. 2. A Generic Social Information Retrieval Model<br />2. Social relevance features<br /><ul><li>Topical relevance
  57. 57. Social distance
  58. 58. Incoming links and bookmarks
  59. 59. Timeliness and freshness
  60. 60. Social importance of individuals</li></ul>10<br />Towards SIR Model A Generic SIR Model A Social Model for LA Experimental evaluation Conclusion<br />
  61. 61. 2. A Generic Social Information Retrieval Model<br />1. Social Information Retrieval Model<br /><ul><li>D: documents
  62. 62. Q: Queries
  63. 63. G: Social information network
  64. 64. F: Modeling process of documents and queries
  65. 65. R(qi,dj,G): Ranking function that combines a subset of social relevance features</li></ul>11<br />Towards SIR Model A Generic SIR Model A Social Model for LA Experimental evaluation Conclusion<br />
  66. 66. 3. A Social model for literature access<br />1. The Social Information Network of bibliographic resources<br />12<br />Towards SIR Model A Generic SIR Model A Social Model for LA Experimental evaluation Conclusion<br />
  67. 67. 3. A Social model for literature access<br />2. Extracting the social network of authors<br />a1<br />a3<br />a2<br />a4<br />a6<br />a1<br />a3<br />a4<br />a2<br />a5<br />Co-authorship<br />d1<br />d2<br />d3<br />d4<br />Citation<br /><ul><li>Social network of authors
  68. 68. A: Authors
  69. 69. Ea: Author-to-author relationships
  70. 70. Edges express:
  71. 71. Co-authorships
  72. 72. Citation</li></ul>13<br />Towards SIR Model A Generic SIR Model A Social Model for LA Experimental evaluation Conclusion<br />
  73. 73. 3. A Social model for literature access<br />3. Weighting social network<br /><ul><li>Co-authorship
  74. 74. Similarity and shared interest between authors
  75. 75. Citation link
  76. 76. Influence and knowledge transfer</li></ul>a1<br />a4<br />a2<br />a5<br />a4<br />a2<br />a5<br />a3<br />a3<br />a1<br />Co(1,2)<br />With A(i,j) documents authored by aiand aj, A(i) documents published by ai<br />Ci(1,4)<br />C(i): citation announced by ai , C(I,j) number of time aicite aj <br />14<br />Towards SIR Model A Generic SIR Model A Social Model for LA Experimental evaluation Conclusion<br />
  77. 77. 3. A Social model for literature access<br />3. Weighting social network<br /><ul><li>Authorship
  78. 78. Author affiliation to the topic of the document</li></ul>Td tags assigned to document d, Ak documents authored by ak, A documents authored by all d co-authors, Hkd tags information entropy and 1-θ default weight value.<br />A<br />Ak<br />a1<br />W(a3,d)<br />a3<br />d<br />a2<br />15<br />Towards SIR Model A Generic SIR Model A Social Model for LA Experimental evaluation Conclusion<br />
  79. 79. 3. A Social model for literature access<br />4. Compute the social importance of authors<br /><ul><li>Rank authors according to their position in the network
  80. 80. Degree
  81. 81. Social activity
  82. 82. Popularity
  83. 83. Gregariousness
  84. 84. Closeness
  85. 85. Reachability|independence
  86. 86. Influence
  87. 87. Betweenss
  88. 88. Interdisciplinary
  89. 89. PageRank
  90. 90. Authority
  91. 91. Hits
  92. 92. Hub and authority</li></ul>16<br />16<br />Towards SIR Model A Generic SIR Model A Social Model for LA Experimental evaluation Conclusion<br />
  93. 93. 3. A Social model for literature access<br />5. Derive document social score<br />CG(a3))<br />CG(a1))<br />CG(a3))<br />ImpG(d)<br />CG(a2))<br />17<br />Towards SIR Model A Generic SIR Model A Social Model for LA Experimental evaluation Conclusion<br />
  94. 94. 3. A Social model for literature access<br />6. Combine topical and social scores<br />Result set<br />IRS<br />Query<br />{d, RSV (q,d)}<br />Topical relevance<br />Social importance<br /><ul><li>Retrieve documents
  95. 95. Combine scores</li></ul>18<br />Towards SIR Model A Generic SIR Model A Social Model for LA Experimental evaluation Conclusion<br />
  96. 96. 4. Experimental evaluation<br />1. Document Dataset and Social Network<br /><ul><li>ACM SIGIR publications from 1978 to 2008
  97. 97. 2 053 documents
  98. 98. Social annotations gathered from CiteUlike1
  99. 99. 6 352 tag applications and 1 382 distinct tags</li></ul>A: Co-authorships<br />C: Citation links<br />AC : Co-authorships<br />and/or Citation links<br />Social network proprieties<br />The giant component<br />[1] http://www.citeulike.org<br />19<br />Towards SIR Model A Generic SIR Model A Social Model for LA Experimental evaluation Conclusion<br />
  100. 100. 4. Experimental evaluation<br />2. Evaluation standard<br /><ul><li>Queries: Top 25 popular tags
  101. 101. Tags are user generated terms to annotate/index documents
  102. 102. Most frequently tags are more important in the social context
  103. 103. Relevance assumption: Strongly tagged documents
  104. 104. Tag is associated at least once to document
  105. 105. Tag is among the top-3 assigned tags to document
  106. 106. Measures
  107. 107. p@5
  108. 108. p@10</li></ul>20<br />Towards SIR Model A Generic SIR Model A Social Model for LA Experimental evaluation Conclusion<br />
  109. 109. 4. Experimental evaluation<br />3. Experimental baselines<br /><ul><li>BM25 Model:
  110. 110. Topical relevance
  111. 111. Select query relevant documents
  112. 112. PR-Docs model:
  113. 113. Combine topical relevance and document authority (in the citation graph).
  114. 114. Estimate the scientific importance of documents
  115. 115. Kirsch’s model:
  116. 116. Combine both topical and social relevance
  117. 117. Estimate social relevancefrom authors authority in the co-authorship network</li></ul>α<br />Tuning α for PR-Docs Model<br />21<br />21<br />Towards SIR Model A Generic SIR Model A Social Model for LA Experimental evaluation Conclusion<br />
  118. 118. 4. Experimental evaluation<br />4. Tuning the social model<br />Binary social network<br />α<br />Tuning αparameter<br />Weighted social network<br />22<br />Towards SIR Model A Generic SIR Model A Social Model for LA Experimental evaluation Conclusion<br />
  119. 119. 4. Experimental evaluation<br />5. Evaluation of model effectivness<br /><ul><li>Final configuration
  120. 120. W-Hub
  121. 121. α=0.9 (SM0.9)</li></ul>p@5<br />p@10<br />SM0.9 improvement<br />Evaluation of the retrieval effectiveness<br />23<br />Towards SIR Model A Generic SIR Model A Social Model for LA Experimental evaluation Conclusion<br />
  122. 122. 5. Conclusion and future work<br /><ul><li>A social information model for literature access
  123. 123. Include information consumer and social annotation
  124. 124. Include citation links between authors
  125. 125. Weight social relationships
  126. 126. Experimental evaluation
  127. 127. W-Hub better evaluate the scientific importance of bibliographic resources
  128. 128. Superiority of proposed model compared to traditional information retrieval and other closely related models</li></ul>24<br />Towards SIR Model A Generic SIR Model A Social Model for LA Experimental evaluation Conclusion<br />
  129. 129. 5. Conclusion and future work<br /><ul><li>Integrate more social features
  130. 130. Social distance
  131. 131. Popularity and freshness
  132. 132. Evaluate tag quality and information consumer centrality
  133. 133. Learn to rank with different social features
  134. 134. Experimental evaluation on larger scientific datasets with various research fields</li></ul>25<br />Towards SIR Model A Generic SIR Model A Social Model for LA Experimental evaluation Conclusion<br />
  135. 135. Thanks for your attention!<br />

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