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20 Oct 2012: Here, we focus our prediction efforts oncheck-ins that happen within 24 hours from the previous one. ... where tod(t) [0, 1. 24] returns a value corresponding tothe hour of the day of time t.

3 Apr 2012: evic. es. Reach. ed (. %). Patched Node ID=2Patch [9.22]. Malware [0.24]. ... uploads {1 hr, 24 hrs};• Initial number of compromised devices and number of.

9 May 2012: We believe that direct application of existing tech-niques, such as community detection [8], tracking mobilitypatterns [24], etc. ... Theactive badge location system. ACM Trans. Inf. Syst.,10(1):91–102, Jan. 1992. [24] M.

1 Mar 2012: 0:00. 1:12. 2:24. 3:36. 4:48. 6:00. 7:12. 8:24. 0 1 2 3 4 5 6 7.

18 Jun 2012: based on human commu-nication and interaction, as demonstrated by some initialrecent attempts [2, 18, 24]. ... In Proceedings of EuroSys ’09.ACM, 2009. [24] M. P. Wittie, V.

21 Jul 2012: Thedata were collected between 10 and 24 May 2011, and wewere able to capture more than 3 million tweets sent by about500,000 Twitter users. ... User Type Weighted user typePolitics 13.53% Politics 15.07%Media 34.12% Media 24.80%.

11 Jan 2012: decreases the correlation (-0.00832 at 12 hour difference); and third, at 24 hour difference the correlation. ... Second, we can see the pattern of repeated peaks with 24-hour time difference although this trend.

21 Jul 2012: This approach is based on the assumption thatusers will exclusively visit the places visited by their friendsand builds on research exploring the interplay between humanmobility and social factors[5], [22], [24];

7 Sep 2012: problems faced by online service providers [24].However, researchers have often neglected factors that arenot inherently connected to the structure of the social net-work itself. ... random shared degree distance gravityrandom 12.34 9.48 -3.47 -28.17

21 Jul 2012: change over time [1], [23], or by generating timestamps in asimilar fashion to words [24]. ... 24] X. Wang and A. McCallum. Topics over Time: A Non-MarkovContinuous-Time Model of Topical Trends.