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your caption here POLYPHONET: An Advanced Social Network Extraction System from the Web Yutaka Matsuo Junichiro Mori Masahiro Hamasaki National Institute of Advanced University of Tokyo National Institute of Advanced Industrial Science and Hongo 7-3-1, Tokyo 113-8656 Industrial Science and Technology Japan Technology y.matsuo@aist.go.jp jmori@mi.ci.i.u-tokyo.ac.jp hamasaki@ni.aist.go.jp (WWW2006) Finding Social Network for Trust Calculation (ECAI 2004) Yutaka Matsuo, Hironori Tomobe, Koiti Hasida and Mitsuru Ishizuka
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your caption here 2 ABSTRACT Social networks in Semantic Web: Knowledge management, Information retrieval, Ubiquitous computing.. POLYPHONET: Extract relations of persons Detect groups of persons Obtain keywords for a person.
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your caption here 3 Introduction and Related work – 1/3 Social Network : “Please indicate which persons you would regard as your friend.” Social networking services (SNSs) Friendster : http://www.friendster.com/ Orkut : http://www.orkut.com/ Imeem : http://www.imeem.com/ 360 0 : http://360.yahoo.com/ Web of trust Ontology construction
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your caption here 4 Introduction and Related work – 2/3 Referral Web (1995): social network extraction system from the Web Two person X and Y by putting a query “X and Y” to a search engine. Flink : online social networks for a Semantic Web community Given a set of names as input, the component uses a search engine to obtain hit counts
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your caption here 5 Introduction and Related work – 3/3 Name disambiguation probability model Co-occurrence information provided by a search engine to detect the proof of relations Google-Hacks [book] PageRank, HITS Web graphs Link structure of Web pages is seen as a social network.
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your caption here 6 Social Network Extraction – 1/4 Nodes and Edges Nodes: a list of persons is given beforehand JSAI2003,JSAI2004,JSAI2005 and UbiComp2005 Edges between of nodes are added using a search engine. Co-occurrence matching coefficient, n X^Y mutual information, log(n X^Y /n X n Y ) Dice coefficient, (2n X^Y )/(n X + n Y ) Jaccard coefficient,(n X^Y /n XvY ) overlap coefficient, (n X^Y / min(n X, n Y )) [ECAI 2004] cosine, (n X^Y / )
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your caption here 7 Social Network Extraction – 2/4 K=30
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your caption here 8 Social Network Extraction – 3/4
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your caption here 9 Social Network Extraction – 4/4 _
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your caption here 10 Advanced Extraction Relationship: Relationships between people 30 kinds of relationships http://vocab.org/relationship POLYPHONET Co-author: co-authors of a technical paper Lab: members of the same laboratory or research institute Proj: members of the same project or committee Conf: participants in the same conference or workshop
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your caption here 11 Advanced Extraction - Class of Relation 1/2 GoogleTop(“X Y”,5) C4.5 Five-fold cross validation (JSAI Case) High tf-idf terms manually categorize data set.
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your caption here 12 Advanced Extraction - Class of Relation 2/2
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your caption here 13 Advanced Extraction – Scalability 1/3 For example - The network density of the JSAI2003 social network is 0.0196 with o.2 threshold.
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your caption here 14 Advanced Extraction – Scalability 2/3 _
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your caption here 15 Advanced Extraction – Scalability 3/3
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your caption here 16 Advanced Extraction – Intellectual link 1/6 Intellectual link : A relation between a pair of persons with similar interests or citations Evaluation : They plot the probability that the two persons will attend the same session at a JSAI conference. Idea : If two persons are researchers of very similar topics, the distribution of word co-occurrences will be similar.
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your caption here 17 Advanced Extraction – Intellectual link 2/6 Termex [37] Keyword extraction
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your caption here 18 Advanced Extraction – Intellectual link 3/6 Keyword extraction 567 researchers with 3981 pages They gave questionnaires to 10 researchers and defined the correct set of keywords.
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your caption here 19 Advanced Extraction – Intellectual link 4/6 X 2 idf hit
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your caption here 20 Advanced Extraction – Intellectual link 5/6
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your caption here 21 Advanced Extraction – Intellectual link 6/6
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your caption here 22 POLYPHONET – 1/4
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your caption here 23 POLYPHONET – 2/4
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your caption here 24 POLYPHONET – 3/4
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your caption here 25 POLYPHONET – 4/4
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your caption here 26 Conclusion This paper describes a social network mining approach using the Web and organize those methods into small pseudocodes. New aspects of social networks are investigated: classes of relations, scalability, and a person-word matrix. This paper implemented every algorithm on POLYPHONET.
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