PPT-Active Sampling for Entity Matching

Aditya Parameswaran Stanford University Jointly with Kedar Bellare Suresh Iyengar Vibhor Rastogi Yahoo Research Entity Matching Goal Find duplicate entities in a given data set. Individual Matching Controls are matched to cases on one or more attributes (i.e. age, gender, smoking status, etc). Each case/control pair then has identical values on the matching factors. Requi James G. Shanahan. Independent . Consultant. EMAIL: . James_DOT_Shanahan_AT_gmail.com. July 27, 2011. http://research.microsoft.com/en-us/um/beijing/events/ia2011. /. . [. with . Nedim. . Lipka. , . Pieter . Abbeel. UC Berkeley EECS. TexPoint fonts used in EMF. . Read the TexPoint manual before you delete this box.: . A. A. A. A. A. A. A. A. A. A. A. A. A. Problem statement:. Given a scan and a map, or a scan and a scan, or a map and a map, find the rigid-body transformation (. Sampling is perhaps the most important step in assuring that good quality aggregates are being used on INDOT contracts. Since a sample is just a small portion of the total material, the importance th . . Agnel . Praveen . Joseph. STFC, Harwell. Sample . classigication. Taxonomy. Pfam. domains (fitted models). Uniprot. ID (text search/. Pfam. link). Alignment scores, transformation matrix . Kieskompas. datasets. Max . Boiten. Overview. Weighting. . methodologies. Sampling . from. data. Weighting. data. Sampling . from. . data. Sample matching. Take . probability. sample. Match cases . Re-labeling. Christopher H. Lin. University of Washington. Mausam. IIT Delhi. Daniel S. . Weld. University of Washington. 1. 2. *Speaker not paid by Oracle Corporation. 3. CROWDSOURCING. Human. (Labeling) Mistakes Were . A link between Continuous-time/Discrete-time Systems. x. (. t. ). y. (. t. ). h. (. t. ). x. [. n. ]. y. [. n. ]. h. [. n. ]. Sampling. x. [. n. ]=. x. (. nT. ), . T. : sampling period. x. [. n. ]. x. Statement of the problem. Two sides of the market to be . matched.. Participants . on . both sides care about to whom they are matched.. M. oney can’t . be used to . determine . the assignment. .. Examples . merayxu@gmail.com. Person . Re-identification by Matching Compositional Template with . Cluster Sampling. Problem. Identifying The Same Person Under Different Cameras. Person Re-identification. Basic Assumption. Jiannan. Wang (. Tsinghua. , China) . Guoliang. Li (. Tsinghua. , China). Jeffrey . Xu. Yu (CUHK, HK, China). Jianhua. . Feng. (. Tsinghua. , China). Entity Matching. 2011/8/30. Find records referring to the same entity. Muthu Venkitasubramaniam (U Rochester). Based on joint works with Carmit . Hazay. , Yuval . Ishai. , . abhi. . shelat. . Active Secure MPC under 1-bit leakage. Muthu Venkitasubramaniam (U Rochester). Paul A. Smith, S3RI, University of Southampton. Shelley Gammon, Sarah Cummins, Christos Chatzoglou, Office for National Statistics. Dick . Heasman. 1. Outline. Record linkage and strategies. Quality measures for record linkage. Peng Li, Jing Jiang, . Yinglin. Wang. Shanghai Jiao Tong University. Singapore Management University. An Example Entity Summary. July 13, 2010. ACL 2010. 2. An Example Entity Summary. July 13, 2010.