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Froehlich J, Neumann J, Oliver N.  2009.  Sensing and predicting the pulse of the city through shared bicycling. International Joint Conference on Artificial Intelligence. :1420-1426.
Daumé H.  2009.  Semi-supervised or semi-unsupervised? Proceedings of the NAACL HLT Workshop on Semisupervised Learning for Natural Language Processing. :84-85.
Han B, Davis LS.  2006.  Semi-Parametric Model-Based Clustering for DNA Microarray Data. Pattern Recognition, 2006. ICPR 2006. 18th International Conference on. 3:324-327.
Kolda TG, O'Leary DP.  1998.  A semidiscrete matrix decomposition for latent semantic indexing information retrieval. ACM Trans. Inf. Syst.. 16(4):322-346.
Chazelle B, Kingsford C, Singh M.  2004.  A semidefinite programming approach to side chain positioning with new rounding strategies. INFORMS Journal on Computing. 16(4):380-392.
Stewart G.W.  2009.  On the Semidefinite B-Arnoldi Method. SIAM Journal on Matrix Analysis and Applications. 31(3):1458-1468.
Suh B, Bederson BB.  2007.  Semi-automatic photo annotation strategies using event based clustering and clothing based person recognition. Interacting with Computers. 19(4):524-544.
Resnik P, Melamed ID.  1997.  Semi-automatic acquisition of domain-specific translation lexicons. Proceedings of the fifth conference on Applied natural language processing. :340-347.
Chuang W-H, M. Wu.  2010.  Semi non-intrusive training for cell-phone camera model linkage. Information Forensics and Security (WIFS), 2010 IEEE International Workshop on. :1-6.
Mangeruca L, Baleani M, Ferrari A, Sangiovanni-Vincentelli A.  2007.  Semantics-Preserving Design of Embedded Control Software from Synchronous Models. Software Engineering, IEEE Transactions on. 33(8):497-509.
Ruiz C, Minker J.  1996.  Semantics of knowledge-based systems with multiple forms of negation.
Weinberg A.  2002.  Semantics in the spin cycle Competence and performance criteria for the creation of lexical entries. The lexical basis of sentence processing: formal, computational, and experimental issues. 4:85-85.
Raschid L, Lobo J.  1991.  Semantics for update rule programs and implementation in a relational database management system. ACM Transactions on Database Systems.
Raschid L.  1992.  Semantics for Rule-based Programs that Express Non-determinism, Causality and Exception Handling Behavior. Workshop on Deductive Databases, JICSLP. :163-174.
Lobo J, Minker J, Rajasekar A.  1998.  Semantics for Disjunctive and Normal Disjunctive Logic Programs. Handbook of logic in artificial intelligence and logic programming. 5:325-325.
Raschid L, Lobo J.  1994.  A Semantics for a class of non-deterministic and causal production system programs. Journal of Automated Reasoning. 12(3):305-349.
Cleaveland R, Parrow J, Steffen B.  1989.  A semantics based verification tool for finite state systems. Proceedings of the IFIP WG6. 1:287-302.
Papaleo L, De Floriani L.  2009.  Semantic-based segmentation and annotation of 3d models. Image Analysis and Processing–ICIAP 2009. :103-112.
Baker K, Bethard S, Bloodgood M, Brown R, Callison-Burch C, Coppersmith G, Dorr BJ, Filardo W, Giles K, Irvine A et al..  2009.  Semantically informed machine translation (SIMT). SCALE summer workshop final report, Human Language Technology Center Of Excellence.
De Floriani L, Hui A, Papaleo L, Huang M, Hendler J.  2007.  A semantic web environment for digital shapes understanding. Proceedings of the semantic and digital media technologies 2nd international conference on Semantic Multimedia. :226-239.
Albanese M, Turaga P, Chellappa R, Pugliese A, Subrahmanian V.  2010.  Semantic Video Content Analysis. Video Search and MiningVideo Search and Mining. 287:147-176.
Cleaveland R, L\üttgen G.  2000.  A semantic theory for heterogeneous system design. FST TCS 2000: Foundations of Software Technology and Theoretical Computer Science. :312-324.
Cleaveland R.  1996.  Semantic theories and system design. ACM Computing Surveys (CSUR). 28(4es):41-41.
Tobin-Hochstadt S, Van Horn D.  2011.  Semantic Solutions to Program Analysis Problems. arXiv:1105.0106 [cs].
Resnik P.  2011.  Semantic similarity in a taxonomy: An information-based measure and its application to problems of ambiguity in natural language. Arxiv preprint arXiv:1105.5444.

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