20 papers:
- VLDB-2015-SchuhknechtKD #clustering #on the
- On the Surprising Difficulty of Simple Things: the Case of Radix Partitioning (FMS, PK, JD), pp. 934–937.
- CHI-2015-DehaisPSFG #automation #realtime
- “Automation Surprise” in Aviation: Real-Time Solutions (FD, VP, SS, JF, TG), pp. 2525–2534.
- BX-2015-CheneyGMS #bidirectional #towards
- Towards a Principle of Least Surprise for Bidirectional Transformations (JC, JG, JM, PS), pp. 66–80.
- OOPSLA-2015-FelgentreffMBH #constraints #programming language #theorem proving
- Checks and balances: constraint solving without surprises in object-constraint programming languages (TF, TDM, AB, RH), pp. 767–782.
- CHI-2014-FioreCTM #online #research
- Incentives to participate in online research: an experimental examination of “surprise” incentives (ATF, CC, LST, GAM), pp. 3433–3442.
- SEKE-2013-Picard
- Surprising discoveries from emotion sensors (RWP).
- CSCW-2011-FanLZTSW #game studies #gesture #social #using
- Surprise Grabber: a co-located tangible social game using phone hand gesture (MF, XL, YZ, LT, YS, HW), pp. 625–628.
- HIMI-v1-2011-ZenkoyohT #generative
- Surprise Generator for Virtual KANSEI Based on Human Surprise Characteristics (MZ, KT), pp. 190–198.
- ESEC-FSE-2011-ShihabMKAH #case study #fault
- High-impact defects: a study of breakage and surprise defects (ES, AM, YK, BA, AEH), pp. 300–310.
- SAC-2010-Rooney #scheduling
- Scheduling intense applications most “surprising” first (SR), pp. 2077–2084.
- KDD-2009-OnumaTF #algorithm #named #novel #recommendation
- TANGENT: a novel, “Surprise me”, recommendation algorithm (KO, HT, CF), pp. 657–666.
- ITiCSE-2006-Motil
- Surprise snippets (JM), p. 351.
- ECOOP-2006-SkotiniotisPL #adaptation #interface #programming
- Demeter Interfaces: Adaptive Programming Without Surprises (TS, JP, KJL), pp. 477–500.
- CSL-2003-KristiansenV #power of #source code #strict
- The Surprising Power of Restricted Programs and Gödel’s Functionals (LK, PJV), pp. 345–358.
- KDD-2002-KeoghLC #database #linear
- Finding surprising patterns in a time series database in linear time and space (EJK, SL, BYcC), pp. 550–556.
- KDD-2001-YangWY #mining #named
- Infominer: mining surprising periodic patterns (JY, WW, PSY), pp. 395–400.
- VLDB-1998-ChakrabartiSD #mining #using
- Mining Surprising Patterns Using Temporal Description Length (SC, SS, BD), pp. 606–617.
- CSL-1998-Egly
- Quantifers and the System KE: Some Surprising Results (UE), pp. 90–104.
- KDD-1994-Siebes #database #scalability
- Homogeneous Discoveries Contain No Surprises: Inferring Risk Profiles from Large Databases (AS), pp. 97–108.
- CSCW-1986-MaloneGLRR #coordination
- Semi-structured messages are surprisingly useful for computer-supported coordination (TWM, KRG, KYL, RR, DR), pp. 102–114.