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Table 2: An illustration of 4 communities from a 50- community solution for the CiteSeer dataset after 1000 it- erations based on Real SIP approach. Each commu- nity is shown with the 10 researchers and the corresponding m;n(magnitude is 10 2) that have the highest probability conditioned on that topic

in Probabilistic community discovery using hierarchical latent gaussian mixture model
by Haizheng Zhang, C. Lee Giles, Henry C. Foley, John Yen 2007
"... In PAGE 5: ... Furthermore, we investigate the quality of the discovered communities from a clustering perspective. Examples of Communities Table2 shows 4 exemplary communities from a 50- community solution for the CiteSeer dataset with social in- teraction pro les being created using Real-SIP representa- tion. Each community is shown with the top 10 researchers that have the highest probability conditioned on the com- munity.... ..."
Cited by 1

Table 1. The service model parameters. CC, FC, and SP stand for collaborative commu- nity, flashcrowd, and super-peer, resp.

in Provisioning and scheduling resources for worldwide data-sharing services
by Ru Iosup, Paweł Garbacki, D. H. J. Epema
"... In PAGE 2: ... Similarly to the real- life situation, all service jobs have a fixed lifetime, which represents the span of the users interest. Table1 summa- rizes the parameters of our service model, and their typ- ical values, as observed in previous measurement studies of large-scale P2P networks [21, 10, 13] and large-scale multimedia streaming networks [20]. The service dispatch constants (fiCC and fiFC) show how well the obtained ca- pacity is used by the SuperPeer to dispatch requests, and are much lower for collaborative communities (shared re-... ..."
Cited by 1

Table 3. Number and

in STRUCTURE AND EVOLUTION OF
by Andrew Tomkins
"... In PAGE 5: ... We extracted the communities by identifying col- lections of blogs that frequently link back and forth to one another. Table3 outlines the number of commu- nities resulting from this extraction; for instance, the table reports that we found 79 communities in which a community consisted of five blogs. Given these communities, how might social net- work researchers identify bursty periods of high inter- linking activity? An algorithm presented in [5] identifies bursts of activity around certain words or expressions in a sequence of documents (such as an email repository).... ..."

Table 2: An informal description of the conversation policies as defined by Flores and Kremer. (The names of some of the policies have changed since the original work.)

in Using a performative subsumption lattice to support commitment-based conversations
by Rob Kremer, Roberto Flores 2005
"... In PAGE 3: ... Note that this is just as easy for an individual agent to track its own social commitments (as in our implementa- tion) or for a 3rd party observer to track all of the social commit- ments of a society of agents (as in [11]). Table2 informally describes some of the fundamental polices we have defined so far. The policies are meant to be used by a commu- nity of agents as a description of social norms .... In PAGE 3: ... Since these particular policies are about conversational acts, all of these arrows (except the last two) terminate on subtypes of communication-act. The curved arrows between the performatives and the social com- mitment operators in Figure 3 represent some of the policies de- scribed in [5] and informally described in Table2 . For example, the P-inform policy associated with the inform perforative would read if Bob receives a message with an inform performative from Alice,... In PAGE 6: ... The number of the mes- sages in the conversation would drop from 7 to 5. Our protocols, as defined in Table2 and Figure 3, call for ev- ery message to be acknowledged. This is an option in our system, and can easily be turned off by merely deleting the policies in Figure 3 associated with P-inform and P-ack.... ..."
Cited by 3

Table 1 Demographics of 22q11DS and comparison subjects

in Cerebral Cortex Advance Access published October 20, 2006 Mapping Cortical Thickness in Children with 22q11.2 Deletions
by unknown authors
"... In PAGE 2: ... The CHOP Institutional Review Board approved the study, and signed informed assents and consents were obtained from all subjects and their parents, respectively. A total of 21 22q11DS patients and 13 normal comparison subjects participated in the study (see Table1 ). Normal comparison subjects were recruited through advertisement in the hospital commu- nity and were matched with probands for race, handedness, parental social class, sex, and age (each subject was individually matched within 14 months).... In PAGE 4: ...001), indicating that age and diagnosis both exerted signifi- cant independent effects on cortical thickness. Effects of Psychiatric Diagnosis Psychiatric diagnoses within the 22q11DS patient group are presented in Table1 . No differences in cortical thickness were observed between 22q11DS patients with (N = 9, 43%) and without (N = 12, 57%) psychiatric diagnoses overall (P gt; 0.... ..."

Table 2 shows the results obtained for different community sizes using the same calculations as presented above.

in Text-Based Content Search and Retrieval in ad hoc P2P Communities
by Francisco Matias Cuenca-acuna, Thu D. Nguyen{mcuenca 2002
"... In PAGE 14: ... Table2 . Amount of memory used per node to store Bloom filters summarizing the whole commu- nity on AP89.... ..."
Cited by 51

Table 2 shows the results obtained for different community sizes using the same calculations as presented above.

in Text-Based Content Search and Retrieval in ad hoc P2P Communities
by Francisco Matias Cuenca-acuna, Thu D. Nguyen 2002
"... In PAGE 14: ... Table2 . Amount of memory used per node to store Bloom filters summarizing the whole commu- nity on AP89.... ..."
Cited by 51

Table 3: Elements of total learning experiences in the four year SE program shown through generic attributes

in Accreditation of Monash University Software Engineering (MUSE) Program
by Sita Ramakrishnan
"... In PAGE 8: ... The generic attributes are as follows: a) ability to apply knowledge of basic science and engineering fundamentals b) ability to communicate effectively, not only with engineers but also with the commu- nity at large c) in-depth technical competence in at least one engineering discipline d) ability to undertake problem identification, formulation and solution e) ability to utilise a systems approach to design and operational performance f) ability to function effectively as an individual and in multi-disciplinary and multi- cultural teams g) understanding of the social, cultural, global and environmental responsibilities and the need for sustainable development h) understanding of the principles of sustainable design and development i) understanding of professional and ethical responsibilities and commitment to them j) expectation of the need to undertake lifelong learning, and capacity to do so. We show how it was covered in our units to show the elements of total learning experiences in the four year SE program during the accreditation visit in 2003 (see Table3 ). As outlined in the IE Aust.... ..."

Table 2: Prediction performance for single individuals joining communities in LiveJournal. For every individual in the fringe of one of our 875 communities, we estimate the probability that person will join in a one-month interval. We repeat this exper- iment using 3 sets of features: only the number of friends in the community, features based on post activity (plus basic fea- tures: number of friends and community size), and finally the combination of all the features, including the graph-theoretic ones from Table 1.

in Group formation in large social networks: membership, growth, and evolution
by Lars Backstrom, Dan Huttenlocher, Jon Kleinberg, Xiangyang Lan 2006
"... In PAGE 5: ... 2.3 Results and Discussion Table2 and Table 3 summarize the performance we achieve with these decision trees. For comparison, both tables contain the base- line performance one could achieve by predicting based solely on the number of friends a fringe member already has in the commu- nity.... ..."
Cited by 30

Table 2: Prediction performance for single individuals joining communities in LiveJournal. For every individual in the fringe of one of our 875 communities, we estimate the probability that person will join in a one-month interval. We repeat this exper- iment using 3 sets of features: only the number of friends in the community, features based on post activity (plus basic fea- tures: number of friends and community size), and finally the combination of all the features, including the graph-theoretic ones from Table 1.

in Group Formation in Large Social Networks: Membership, Growth, and Evolution
by Lars Backstrom, Dan Huttenlocher, Jon Kleinberg, Xiangyang Lan 2006
"... In PAGE 5: ... 2.3 Results and Discussion Table2 and Table 3 summarize the performance we achieve with these decision trees. For comparison, both tables contain the base- line performance one could achieve by predicting based solely on the number of friends a fringe member already has in the commu- nity.... ..."
Cited by 30
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