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Journal articles on the topic 'Record matching'

Author: Grafiati

Published: 4 June 2021

Last updated: 13 February 2022

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1

Somasekhar, G., SeshaSravani K, Keerthi P, and Sai Sandeep G. "Record linkage and deduplication using traditional blocking." International Journal of Engineering & Technology 7, no. 1.1 (December 21, 2017): 294. http://dx.doi.org/10.14419/ijet.v7i1.1.9705.

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Record Linkage and Deduplication are the two process that are used in matching records. Matching of records is done to remove the duplicate records. These duplicate records highly influence the outputs of data mining and data processing. If the matching of records is done on the single database, it is called Deduplication. In Deduplication we check for the duplicate records in the single database. Unlike deduplication if the matching of the records is done on the several databases it is called as record linkage. In this paper we also discuss about the indexing technique called as traditional blocking which is used to remove non matching pairs that leads to the less number of record pair to be compared.

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2

Copas, J. B., and F. J. Hilton. "Record Linkage: Statistical Models for Matching Computer Records." Journal of the Royal Statistical Society. Series A (Statistics in Society) 153, no. 3 (1990): 287. http://dx.doi.org/10.2307/2982975.

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3

Winkler, William E. "Matching and record linkage." Wiley Interdisciplinary Reviews: Computational Statistics 6, no. 5 (July 2, 2014): 313–25. http://dx.doi.org/10.1002/wics.1317.

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Fan, Wenfei, Hong Gao, Xibei Jia, Jianzhong Li, and Shuai Ma. "Dynamic constraints for record matching." VLDB Journal 20, no. 4 (November 16, 2010): 495–520. http://dx.doi.org/10.1007/s00778-010-0206-6.

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Fan, Wenfei, Xibei Jia, Jianzhong Li, and Shuai Ma. "Reasoning about record matching rules." Proceedings of the VLDB Endowment 2, no. 1 (August 2009): 407–18. http://dx.doi.org/10.14778/1687627.1687674.

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6

Seleznjev, Oleg, and Bernhard Thalheim. "Random Databases with Approximate Record Matching." Methodology and Computing in Applied Probability 12, no. 1 (July 31, 2008): 63–89. http://dx.doi.org/10.1007/s11009-008-9092-4.

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7

Verykios, Vassilios S., Ahmed K. Elmagarmid, and Elias N. Houstis. "Automating the approximate record-matching process." Information Sciences 126, no. 1-4 (July 2000): 83–98. http://dx.doi.org/10.1016/s0020-0255(00)00013-x.

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8

Wiseley, W. Charles. "Collaborative Administrative Record Matching in California." New Directions for Community Colleges 1998, no. 104 (1998): 41–51. http://dx.doi.org/10.1002/cc.10404.

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9

Kan, Min-Yen, and Yee Fan Tan. "Record matching in digital library metadata." Communications of the ACM 51, no. 2 (February 2008): 91–94. http://dx.doi.org/10.1145/1314215.1314231.

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10

Bianchi Santiago, Josie D., Héctor Colón Jordán, and Didier Valdés. "Record Linkage of Crashes with Injuries and Medical Cost in Puerto Rico." Transportation Research Record: Journal of the Transportation Research Board 2674, no. 10 (July 31, 2020): 739–48. http://dx.doi.org/10.1177/0361198120935439.

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Cost considerations are critical in the analysis and prevention of traffic crashes. Integration of cost data into crash datasets facilitates the crash-cost analyses with all their related attributes. It is, however, a challenging task because of the lack of availability of unique identifiers across the databases and because of privacy and confidentiality regulations. This study performed a record linkage comparison between the deterministic and probabilistic approaches using attributes matching techniques with numerical distance and weight patterns under the Fellegi–Sunter approach. As a result, the deterministic algorithm developed using the exact match of the 14-digit police accident record number had an overall matching performance of 52.38% of real matched records, while the probabilistic algorithm had an overall matching performance of 70.41% with a quality measurement of the sensitivity of 99.99%. The deterministic approach was thus outperformed by the probabilistic approach by approximately 20% of records matched. The probabilistic matching with numerical variables seems to be a good matching strategy supported by quality variables. On record matching, a multivariable regression model was developed to model medical costs and identify factors that increase the costs of treating injured claimants in Puerto Rico.

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Gu, Binbin, Zhixu Li, Xiangliang Zhang, An Liu, Guanfeng Liu, Kai Zheng, Lei Zhao, and Xiaofang Zhou. "The Interaction Between Schema Matching and Record Matching in Data Integration." IEEE Transactions on Knowledge and Data Engineering 29, no. 1 (January 1, 2017): 186–99. http://dx.doi.org/10.1109/tkde.2016.2611577.

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12

Nowak, Robert, Wiktor Franus, Jiarui Zhang, Yue Zhu, Xin Tian, Zhouxian Zhang, Xu Chen, and Xiaoyu Liu. "Record Linkage of Chinese Patent Inventors and Authors of Scientific Articles." Applied Sciences 11, no. 18 (September 10, 2021): 8417. http://dx.doi.org/10.3390/app11188417.

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We present an algorithm to find corresponding authors of patents and scientific articles. The authors are given as records in Scopus and the Chinese Patents Database. This issue is known as the record linkage problem, defined as finding and linking individual records from separate databases that refer to the same real-world entity. The presented solution is based on a record linkage framework combined with text feature extraction and machine learning techniques. The main challenges were low data quality, lack of common record identifiers, and a limited number of other attributes shared by both data sources. Matching based solely on an exact comparison of authors’ names does not solve the records linking problem because many Chinese authors share the same full name. Moreover, the English spelling of Chinese names is not standardized in the analyzed data. Three ideas on how to extend attribute sets and improve record linkage quality were proposed: (1) fuzzy matching of names, (2) comparison of abstracts of patents and articles, (3) comparison of scientists’ main research areas calculated using all metadata available. The presented solution was evaluated in terms of matching quality and complexity on ≈250,000 record pairs linked by human experts. The results of numerical experiments show that the proposed strategies increase the quality of record linkage compared to typical solutions.

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13

Keller, Jane E., Holly L. Howe, and John R. Noak. "An algorithm for matching anonymous hospital discharge records used in occupational disease surveillance: Anonymous record matching algorithm." American Journal of Industrial Medicine 20, no. 5 (1991): 657–61. http://dx.doi.org/10.1002/ajim.4700200508.

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Karakasidis, Alexandros, and Vassilios S. Verykios. "Secure Blocking + Secure Matching = Secure Record Linkage." Journal of Computing Science and Engineering 5, no. 3 (September 30, 2011): 223–35. http://dx.doi.org/10.5626/jcse.2011.5.3.223.

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15

Inan, Ali, Murat Kantarcioglu, Gabriel Ghinita, and Elisa Bertino. "A Hybrid Approach to Private Record Matching." IEEE Transactions on Dependable and Secure Computing 9, no. 5 (September 2012): 684–98. http://dx.doi.org/10.1109/tdsc.2012.46.

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16

Ross, J. M., R. N. Fermin Cota, and G. S. Zaric. "PROBABILISTIC RECORD MATCHING USING MACHINE LEARNING TECHNIQUES." Value in Health 19, no. 3 (May 2016): A82—A83. http://dx.doi.org/10.1016/j.jval.2016.03.1777.

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17

Lopez-Cuadrado, Jose Luis, Israel Gonzalez-Carrasco, Jesus Leonardo Lopez-Hernandez, Paloma Martinez-Fernandez, and Jose Luis Martinez-Fernandez. "Automatic Learning Framework for Pharmaceutical Record Matching." IEEE Access 8 (2020): 171754–70. http://dx.doi.org/10.1109/access.2020.3024558.

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Fan, Wenfei, Shuai Ma, Nan Tang, and Wenyuan Yu. "Interaction between Record Matching and Data Repairing." Journal of Data and Information Quality 4, no. 4 (May 2014): 1–38. http://dx.doi.org/10.1145/2567657.

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19

Douglas, M. M., D. Gardner, D. Hucker, and S. W. Kendrick. "Best-Link Matching of Scottish Health Data Sets." Methods of Information in Medicine 37, no. 01 (1998): 64–68. http://dx.doi.org/10.1055/s-0038-1634494.

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Abstract:Methods are described used to link the Community Health Index and the National Health Service Central Register (NHSCR) in Scotland to provide a basis for a national patient index. The linkage used a combination of deterministic and probability matching techniques. A best-link principle was used by which each Community Health Index record was allowed to link only to the NHSCR record with which it achieved the highest match weight. This strategy, applied in the context of two files which each covered virtually the entire population of Scotland, increased the accuracy of linkage approximately a thousand-fold compared with the likely results of a less structured probability matching approach. By this means, 98.8% of linkable records were linked automatically with a sufficient degree of confidence for administrative purposes.

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20

Roos, L. L., and A. Wajda. "Record Linkage Strategies." Methods of Information in Medicine 30, no. 02 (1991): 117–23. http://dx.doi.org/10.1055/s-0038-1634828.

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AbstractRecord linkage techniques can help identify the same patient for matching diverse files (hospital discharge abstracts, insurance claims, registries, Vital Statistics data) which contain similar identifiers. Prior knowledge of whether a linkage is feasible is important to prevent wasted effort (additional data collection or data manipulation), which decreases the cost-effectiveness of the linkage. Using examples generated by linking the Manitoba Health Services Commission data with Vital Statistics files, a method of estimating the information in each data set is presented first. Further, the feasibility of several different record linkage strategies is described and tested, given varying amounts of information. At the margin, relatively small amounts of information (having just one more variable to match with) can make a great difference. Probabilistic linkage’s great advantage was found in those situations where only a moderate amount of extra information was available.By using the above techniques when working with one or both files in a proposed record linkage project, a much more informed judgement can now be made as to whether a linkage will or will not work. In facilitating record linkage, flexibility of both software and the strategy for matching is very important.

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21

Croft, D. "Improving record matching in imprecise and uncertain datasets." Literary and Linguistic Computing 27, no. 4 (July 14, 2012): 347–54. http://dx.doi.org/10.1093/llc/fqs028.

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22

Goel, Anjali, and Rajesh Prasad. "Efficient indexing techniques for record matching and deduplication." International Journal of Computational Vision and Robotics 4, no. 1/2 (2014): 75. http://dx.doi.org/10.1504/ijcvr.2014.059362.

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23

van Gennip, Yves, Blake Hunter, Anna Ma, Daniel Moyer, Ryan de Vera, and Andrea L. Bertozzi. "Unsupervised record matching with noisy and incomplete data." International Journal of Data Science and Analytics 6, no. 2 (May 23, 2018): 109–29. http://dx.doi.org/10.1007/s41060-018-0129-7.

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24

LI, YAKUN, HONGZHI WANG, HONG GAO, and JIANZHONG LI. "AN EFFICIENT ENTITY RESOLUTION METHOD FOR LARGE RELATIONS." International Journal of Cooperative Information Systems 22, no. 01 (March 2013): 1350006. http://dx.doi.org/10.1142/s0218843013500068.

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Entity resolution (ER) is to find the data objects referring to the same real-world entity. When ER is performed on relations, the crucial operator is record matching, which is to judge whether two tuples refer to the same real-world entity. Record matching is a longstanding issue. However, with massive and complex data in applications, current methods cannot satisfy the requirements. A Sequence-rule-based record matching (SeReMatching) is presented with the consideration of both which attributes should be used and their importance in record matching. We have changed the Bloom filter and therefore the checking speed is greatly increased. The best performance of the algorithm makes the complexity of entity resolution O (n). And extensive experiments were performed to evaluate our methods.

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S. RAMA, KRISHNAN. "PRIVATE RECORD MATCHING FOR UNSTRUCTURED DATA USING HYBRID APPROACH." i-manager’s Journal on Software Engineering 11, no. 4 (2017): 24. http://dx.doi.org/10.26634/jse.11.4.13818.

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26

Verykios, V. S., G. V. Moustakides, and M. G. Elfeky. "A Bayesian decision model for cost optimal record matching." VLDB Journal The International Journal on Very Large Data Bases 12, no. 1 (May 1, 2003): 28–40. http://dx.doi.org/10.1007/s00778-002-0072-y.

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27

Essex, Aleksander. "Secure Approximate String Matching for Privacy-Preserving Record Linkage." IEEE Transactions on Information Forensics and Security 14, no. 10 (October 2019): 2623–32. http://dx.doi.org/10.1109/tifs.2019.2903651.

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28

Su, Weifeng, Jiying Wang, and Frederick H. Lochovsky. "Record Matching over Query Results from Multiple Web Databases." IEEE Transactions on Knowledge and Data Engineering 22, no. 4 (April 2010): 578–89. http://dx.doi.org/10.1109/tkde.2009.90.

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29

B.Rakesh, B. Rakesh. "Implementation of Matching Tree Technique for Online Record Linkage." IOSR Journal of Computer Engineering 11, no. 4 (2013): 37–43. http://dx.doi.org/10.9790/0661-1143743.

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30

Murniwati, Murniwati. "PERAN REKAM MEDIK GIGI SEBAGAI SARANA IDENTIFIKASI." Majalah Kedokteran Andalas 36, no. 2 (August 30, 2012): 163. http://dx.doi.org/10.22338/mka.v36.i2.p163-172.2012.

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AbstrakIndonesia merupakan salah satu negara yang rawan terjadi bencana. Metode identifikasi korban akibat bencana salah satunya melalui pencocokan dental record. Dental record yang dapat digunakan dalam proses identifikasi adalah yang sesuai dengan Standar Nasional Rekam Medik Kedokteran Gigi yaitu harus memuat data identitas pasien, keadaan umum pasien, odontogram, data perawatan kedokteran gigi serta nama dan tanda tangan dokter gigi dan harus diisi secara lengkap.Kata Kunci : Dental Record, Standar Nasional Rekam Medik Kedokteran Gigi, Identifikasi Korban, OdontogramAbstract Indonesia is one of the disaster-prone countries. One method of identification of victims of the disaster is through matching dental records. Dental records that can be used in the identification process must comply with National Standard of Dentistry, Dental Record must contain data that identity of the patient, patient's general condition, odontogram, dental care data and the name and signature of the dentist and dental records are more important filled completely.Key word : Dental Record, National Standard Medical Record Dentistry, Victim Identification, Odontogram

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Avoundjian, Tigran, Julia C. Dombrowski, Matthew R. Golden, James P. Hughes, Brandon L. Guthrie, Janet Baseman, and Mauricio Sadinle. "Comparing Methods for Record Linkage for Public Health Action: Matching Algorithm Validation Study." JMIR Public Health and Surveillance 6, no. 2 (April 30, 2020): e15917. http://dx.doi.org/10.2196/15917.

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Background Many public health departments use record linkage between surveillance data and external data sources to inform public health interventions. However, little guidance is available to inform these activities, and many health departments rely on deterministic algorithms that may miss many true matches. In the context of public health action, these missed matches lead to missed opportunities to deliver interventions and may exacerbate existing health inequities. Objective This study aimed to compare the performance of record linkage algorithms commonly used in public health practice. Methods We compared five deterministic (exact, Stenger, Ocampo 1, Ocampo 2, and Bosh) and two probabilistic record linkage algorithms (fastLink and beta record linkage [BRL]) using simulations and a real-world scenario. We simulated pairs of datasets with varying numbers of errors per record and the number of matching records between the two datasets (ie, overlap). We matched the datasets using each algorithm and calculated their recall (ie, sensitivity, the proportion of true matches identified by the algorithm) and precision (ie, positive predictive value, the proportion of matches identified by the algorithm that were true matches). We estimated the average computation time by performing a match with each algorithm 20 times while varying the size of the datasets being matched. In a real-world scenario, HIV and sexually transmitted disease surveillance data from King County, Washington, were matched to identify people living with HIV who had a syphilis diagnosis in 2017. We calculated the recall and precision of each algorithm compared with a composite standard based on the agreement in matching decisions across all the algorithms and manual review. Results In simulations, BRL and fastLink maintained a high recall at nearly all data quality levels, while being comparable with deterministic algorithms in terms of precision. Deterministic algorithms typically failed to identify matches in scenarios with low data quality. All the deterministic algorithms had a shorter average computation time than the probabilistic algorithms. BRL had the slowest overall computation time (14 min when both datasets contained 2000 records). In the real-world scenario, BRL had the lowest trade-off between recall (309/309, 100.0%) and precision (309/312, 99.0%). Conclusions Probabilistic record linkage algorithms maximize the number of true matches identified, reducing gaps in the coverage of interventions and maximizing the reach of public health action.

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Epifanio, Jenna A., Edward J. Brook, Christo Buizert, Jon S. Edwards, Todd A. Sowers, Emma C. Kahle, Jeffrey P. Severinghaus, et al. "The SP19 chronology for the South Pole Ice Core – Part 2: gas chronology, Δage, and smoothing of atmospheric records." Climate of the Past 16, no. 6 (December 3, 2020): 2431–44. http://dx.doi.org/10.5194/cp-16-2431-2020.

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Abstract. A new ice core drilled at the South Pole provides a 54 000-year paleoenvironmental record including the composition of the past atmosphere. This paper describes the SP19 chronology for the South Pole atmospheric gas record and complements a previous paper (Winski et al., 2019) describing the SP19 ice chronology. The gas chronology is based on a discrete methane (CH4) record with 20- to 190-year resolution. To construct the gas timescale, abrupt changes in atmospheric CH4 during the glacial period and centennial CH4 variability during the Holocene were used to synchronize the South Pole gas record with analogous data from the West Antarctic Ice Sheet Divide ice core. Stratigraphic matching based on visual optimization was verified using an automated matching algorithm. The South Pole ice core recovers all expected changes in CH4 based on previous records. Gas transport in the firn results in smoothing of the atmospheric gas record with a smoothing function spectral width that ranges from 30 to 78 years, equal to 3 % of the gas-age–ice-age difference, or Δage. The new gas chronology, in combination with the existing ice age scale from Winski et al. (2019), allows a model-independent reconstruction of the gas-age–ice-age difference through the whole record, which will be useful for testing firn densification models.

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Roos, L. L., M. Layefsky, J. A. Singleton, and A. Wajda. "Record Linkage Strategies: Part II. Portable Software and Deterministic Matching." Methods of Information in Medicine 30, no. 03 (1991): 210–14. http://dx.doi.org/10.1055/s-0038-1634840.

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AbstractSoftware to perform record linkage should have several characteristics: (1) portability in being able to function with researchers’ current arrangement of computer systems and languages, (2) flexibility in handling different linkage strategies, and (3) low cost in both computer time and researchers’ efforts. A linkage package (LINKS) is described which satisfies these criteria; LINKS provides tools for both deterministic and probabilistic linkage as well as test modules for assessing data quality and structure. Because each linkage project is different, the modular nature of the software allows for better control of the programming process and development of unique strategies. Since the user provides the weights and decision rules, he may modify data between steps and/or develop extra steps to supplement the basic modules. In two information-rich linkage projects involving California AIDS data, LINKS identified mortality using deterministic approaches and permitted comparisons with other software and strategies. Flexible software and a deterministic approach would have eliminated the expensive key entry used to add full names and social security numbers as additional identifiers to one of the California data files.

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Gessendorfer, Jonathan, Jonas Beste, Jörg Drechsler, and Joseph W. Sakshaug. "Statistical Matching as a Supplement to Record Linkage: A Valuable Method to Tackle Nonconsent Bias?" Journal of Official Statistics 34, no. 4 (December 1, 2018): 909–33. http://dx.doi.org/10.2478/jos-2018-0045.

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Abstract Record linkage has become an important tool for increasing research opportunities in the social sciences. Surveys that perform record linkage to administrative records are often required to obtain informed consent from respondents prior to linkage. A major concern is that nonconsent could introduce biases in analyses based on the linked data. One straightforward strategy to overcome the missing data problem created by nonconsent is to match nonconsenters with statistically similar units in the target administrative database. To assess the effectiveness of statistical matching in this context, we use data from two German panel surveys that have been linked to an administrative database of the German Federal Employment Agency. We evaluate the statistical matching procedure under various artificial nonconsent scenarios and show that the method can be effective in reducing nonconsent biases in marginal distributions, but that biases in multivariate estimates can sometimes be worsened. We discuss the implications of these findings for survey practice and elaborate on some of the practical challenges of implementing the statistical matching procedure in the context of linkage nonconsent. The developed simulation design can act as a roadmap for other statistical agencies considering the proposed approach for their data.

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35

Michaud, Dominic, and Pierre Léger. "Ground motions selection and scaling for nonlinear dynamic analysis of structures located in Eastern North America." Canadian Journal of Civil Engineering 41, no. 3 (March 2014): 232–44. http://dx.doi.org/10.1139/cjce-2012-0339.

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This paper presents the effectiveness of seven ground motion scaling methods and two spectral matching methods to achieve compatibility with the Canadian National Building Code (CNBC) 2005 uniform hazard spectrum for Montreal to perform nonlinear seismic analysis. Databases of 30 historical records and 30 Eastern North America simulated records have been selected to compute the reference mean seismic demand and its dispersion. The characteristics and destructive capacity of ground motions have been studied using a large number of indices computed from (i) the records themselves, (ii) a series of single degree of freedom structures, as well as (iii) a four-story steel frame. Record scaling methods to the target spectrum using (i) spectral intensity, (ii) reducing the mean square error, (iii) and minimizing dispersion as well as time domain spectral matching generated coherent seismic demand and dispersion in agreement with the reference values. Spectral matching to a specified elastic design spectrum does not reduce the dispersion of the nonlinear response. Therefore close spectral matching cannot be used to reduce the number of records to minimize the resources allocated in seismic safety assessment. At least seven records, as recommended in current CNBC and FEMA (2012) guidelines to compute an average response, should be used to characterize the nonlinear behaviour of structural systems.

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Clark, Daniel, Drew Fudenberg, and Alexander Wolitzky. "Record-Keeping and Cooperation in Large Societies." Review of Economic Studies 88, no. 5 (March 12, 2021): 2179–209. http://dx.doi.org/10.1093/restud/rdab016.

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Abstract We introduce a new model of repeated games in large populations with random matching, overlapping generations, and limited records of past play. We prove that steady-state equilibria exist under general conditions on records. When the updating of a player’s record can depend on the actions of both players in a match, any strictly individually rational action can be supported in a steady-state equilibrium. When record updates can depend only on a player’s own actions, fewer actions can be supported. Here, we focus on the prisoner’s dilemma and restrict attention to strict equilibria that are coordination-proof, meaning that matched partners never play a Pareto-dominated Nash equilibrium in the one-shot game induced by their records and expected continuation payoffs. Such equilibria can support full cooperation if the stage game is either “strictly supermodular and mild” or “strongly supermodular,” and otherwise permit no cooperation at all. The presence of “supercooperator” records, where a player cooperates against any opponent, is crucial for supporting any cooperation when the stage game is “severe.”

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Elezaj, Ogerta, and Gloria Tuxhari. "Record Linkage using Probabilistic Methods and Data Mining Techniques." Mediterranean Journal of Social Sciences 8, no. 3 (May 24, 2017): 203–7. http://dx.doi.org/10.5901/mjss.2017.v8n3p203.

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Abstract Nowadays corporations and organizations acquire large amounts of information daily which is stored in many large databases (DB). These databases mostly are heterogeneous and the data are represented differently. Data in these DB may simply be inaccurate and there is a need to clean these DB. The record linkage process is considered to be part of the data cleaning phase when working with big scale surveys considered as a data mining step. Record linkage is an important process in data integration, which consists in finding duplication records and finding matched records too. This process can be divided in two main steps Exact Record Linkage, which founds all the exact matches between two records and Probabilistic Record Linkage, which matches records that are not exactly equal but have a high probability of being equal. In recent years, the record linkage becomes an important process in data mining task. As the databases are becoming more and more complex, finding matching records is a crucial task. Comparing each possible pair of records in large DB is impossible via manual/automatic procedures. Therefore, special algorithms (blocking methods) have to be used to reduce computational complexity of comparison space among records. The paper will discuss the deterministic and probabilistic methods used for record linkage. Also, different supervised and unsupervised techniques will be discussed. Results of a real world datasets linkage (Albanian Population and Housing Census 2011 and farmers list registered by Food Safety and Veterinary Institute) will be presented.

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Zhang, Rui, Dong-sheng Wang, Xiao-yu Chen, and Hong-nan Li. "Comparison of Scaling Ground Motions Using Arithmetic with Logarithm Values for Spectral Matching Procedure." Shock and Vibration 2020 (January 3, 2020): 1–14. http://dx.doi.org/10.1155/2020/8180612.

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In recent studies, spectral matching is the most commonly proposed method for selecting earthquake records for time-history analysis of structures. However, until now, there have been no serious investigations of the effects of coordinate values on the scaling of ground motions. This paper investigated the influence of using arithmetic and logarithmic values of response spectra in spectral matching procedures (i.e., ASM and LSM methods) on the results of nonlinear structural time-history analysis. Steel moment resisting frame structures of the 3-, 9-, and 20-stories, which represent low-, medium-, and high-rise buildings, respectively, were used as examples. Structural benchmark responses were determined by calculating the arithmetic mean and median of peak interstory drift ratio (PIDR) demands based on the three record sets developed by the American SAC Steel Project. The three record sets represent seismic hazard levels with 50%, 10%, and 2% probabilities exceeded in 50 years, and their average acceleration spectra were also taken as the target spectrum. Moreover, another 40 record components for selection were scaled both by ASM and LSM methods. The seven components whose spectra were best compatible with the target spectra were selected for the structural time-history analysis. The scale factors obtained by the LSM method are nearly larger than that of the ASM method, and their ranking and selection of records are different. The estimation accuracies of structural mean (median) responses by both methods can be controlled within an engineering acceptable range (±20%), but the LSM method may cause larger structural responses than the ASM method. The LSM method has a better capacity for reducing the variability of structural responses than the ASM method, and this advantage is more significant for longer-period structures (e.g., 20-story structure) with more severe nonlinear responses.

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Dey, Debabrata. "Record Matching in Data Warehouses: A Decision Model for Data Consolidation." Operations Research 51, no. 2 (April 2003): 240–54. http://dx.doi.org/10.1287/opre.51.2.240.12779.

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Aljawad, Dr Mohamed Saleh, Dr Mohamed Hlaeel, Abdul-Mohaimin Abbas Dawood, Alya‘a Mahmood Ali, and Hiba Ala‘a Nsaeef. "Matching Well Test Data with Computer Model." Journal of Petroleum Research and Studies 7, no. 2 (May 6, 2021): 144–61. http://dx.doi.org/10.52716/jprs.v7i2.194.

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This project concerning with matching the well test data for one of Buzurgan wells the objective of make matching is to see if the observed data of the well test as same as the calculated one by using the mathematical model we made by using computer program.The well test data was available for matching was consist of three build up test two of them have a record for the well head pressure and bottom hole pressure and one just contain a record for the well head pressure so after matching we can make correlation to find the bottom hole pressure for the test haven‘t BHP values .By using Eclipse program we build a mathematical model for the well BU-6The model consist of six layer (MA, MB11, MB12, MB21, MC1and MC2) and we take r=1, theta=10,we use the available data in Buzurgan field reports and then we enter the well test data and see the result of matching between the observed and the calculated one.From the matching we see that there was good matching between the two data, the matching was for the production and the bottomhole flowing pressure and the two was matched with the observed one.In order to make the matching very well we make change in permeability and increase its value by 20% and this change was very good to the matching of the production data and we also change the skin factor to -3.6 and that effect on the pressure matching and make it very well.

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Tuovenen, J., M. Oussalah, and P. Kostakos. "MAuto: Automatic Mobile Game Testing Tool Using Image-Matching Based Approach." Computer Games Journal 8, no. 3-4 (October 19, 2019): 215–39. http://dx.doi.org/10.1007/s40869-019-00087-z.

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Abstract The exponential increase in the speed of the mobile industry has led to a decreasing quality in many associated mobile apps. Besides, the number of distinct Android devices reached thousands. This challenged the development of universally accepted test applications that can run on all devices. This paper focuses on the development of a new mobile game testing framework, referred to, MAuto. MAuto records the user actions in the game and replays the tests on any Android device. MAuto uses image recognition, through AKAZE features, to record the test cases and the Appium framework to replay the user actions automatically. The feasibility of the developed tool has been demonstrated through testing on the Clash of Clans mobile game.

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Nash, J. Q., M. Chandrakumar, C. P. Farrington, S. Williamson, and E. Miller. "Feasibility study for identifying adverse events attributable to vaccination by record linkage." Epidemiology and Infection 114, no. 3 (June 1995): 475–80. http://dx.doi.org/10.1017/s0950268800052183.

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SUMMARYTo investigate the feasibility of using a record linkage method for identifying vaccine attributable adverse events, computerized hospital admissions and vaccination records from South East Kent district were linked and checked for accuracy. Records for 90% of children under 2 years of age admitted to hospital over a 2-year period were matched with vaccination records using a computer algorithm based on name, date of birth, sex, and post-code supplemented by visual inspection. Relative to this gold standard, matching on date of birth, sex and postcode alone had a sensitivity of 60% and an incorrect match rate of 0·2% after matches to more than one vaccine recipient were excluded. Manual checking of a sample of admissions showed that only 4% had been assigned incorrect International Classification of Disease (ICD) codes. Routine record linkage of ICD admission codes to vaccination records therefore yields data of good quality which may be used for surveillance purposes.

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Zech, John, Gregg Husk, Thomas Moore, and Jason Shapiro. "Measuring the Degree of Unmatched Patient Records in a Health Information Exchange Using Exact Matching." Applied Clinical Informatics 07, no. 02 (April 2016): 330–40. http://dx.doi.org/10.4338/aci-2015-11-ra-0158.

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SummaryHealth information exchange (HIE) facilitates the exchange of patient information across different healthcare organizations. To match patient records across sites, HIEs usually rely on a master patient index (MPI), a database responsible for determining which medical records at different healthcare facilities belong to the same patient. A single patient’s records may be improperly split across multiple profiles in the MPI.We investigated the how often two individuals shared the same first name, last name, and date of birth in the Social Security Death Master File (SSDMF), a US government database containing over 85 million individuals, to determine the feasibility of using exact matching as a split record detection tool. We demonstrated how a method based on exact record matching could be used to partially measure the degree of probable split patient records in the MPI of an HIE.We calculated the percentage of individuals who were uniquely identified in the SSDMF using first name, last name, and date of birth. We defined a measure consisting of the average number of unique identifiers associated with a given first name, last name, and date of birth. We calculated a reference value for this measure on a subsample of SSDMF data. We compared this measure value to data from a functioning HIE.We found that it was unlikely for two individuals to share the same first name, last name, and date of birth in a large US database including over 85 million individuals. 98.81% of individuals were uniquely identified in this dataset using only these three items. We compared the value of our measure on a subsample of Social Security data (1.00089) to that of HIE data (1.1238) and found a significant difference (t-test p-value < 0.001).This method may assist HIEs in detecting split patient records.

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Bassett, Ingrid Valerie, Mingshu Huang, Christie Cloete, Sue Candy, Janet Giddy, Simone Claire Frank, and Robert A. Parker. "Assessing the completeness and accuracy of South African National Laboratory CD4 and viral load data: a cross-sectional study." BMJ Open 8, no. 8 (August 2018): e021506. http://dx.doi.org/10.1136/bmjopen-2018-021506.

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ObjectiveTo assess the accuracy of the South African National Health Laboratory Services (NHLS) corporate data warehouse (CDW) using a novel data cross-matching method.MethodsAdults (≥18 years) on antiretroviral therapy (ART) who visited a hospital-based HIV clinic in Durban from March to June 2012 were included. We matched patient identifiers, CD4 and viral load (VL) records from the HIV clinic’s electronic record with the NHLS CDW according to a set of matching criteria for patient identifiers, test values and test dates. We calculated the matching rates for patient identifiers, CD4 and VL records, and an overall matching rate.ResultsNHLS returned records for 3498 (89.6%) of the 3906 individuals requested. Using our computer algorithm, we confidently matched 3278 patients (83.9% of the total request). Considering less than confident matches as well, and then manually reviewing questionable matches using only patient identifiers, only nine (0.3% of records returned by NHLS) of the suggested matches were judged incorrect.ConclusionsWe developed a data cross-matching method to evaluate national laboratory data and were able to match almost 9 of 10 patients with data we expected to find in the NHLS CDW. We found few questionable matches, suggesting that manual review of records returned was not essential. As the number of patients initiating ART in South Africa grows, maintaining a comprehensive and accurate national data repository is of critical importance, since it may serve as a valuable tool to evaluate the effectiveness of the country’s HIV care system. This study helps validate the use of NHLS CDW data in future research on South Africa’s HIV care system and may inform analyses in similar settings with national laboratory systems.

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Maratea, Antonio, Angelo Ciaramella, and Giuseppe Pio Cianci. "Record linkage of banks and municipalities through multiple criteria and neural networks." PeerJ Computer Science 6 (February 24, 2020): e258. http://dx.doi.org/10.7717/peerj-cs.258.

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Record linkage aims to identify records from multiple data sources that refer to the same entity of the real world. It is a well known data quality process studied since the second half of the last century, with an established pipeline and a rich literature of case studies mainly covering census, administrative or health domains. In this paper, a method to recognize matching records from real municipalities and banks through multiple similarity criteria and a Neural Network classifier is proposed: starting from a labeled subset of the available data, first several similarity measures are combined and weighted to build a feature vector, then a Multi-Layer Perceptron (MLP) network is trained and tested to find matching pairs. For validation, seven real datasets have been used (three from banks and four from municipalities), purposely chosen in the same geographical area to increase the probability of matches. The training only involved two municipalities, while testing involved all sources (municipalities vs. municipalities, banks vs banks and and municipalities vs. banks). The proposed method scored remarkable results in terms of both precision and recall, clearly outperforming threshold-based competitors.

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Deb, Joyee, Takuo Sugaya, and Alexander Wolitzky. "The Folk Theorem in Repeated Games With Anonymous Random Matching." Econometrica 88, no. 3 (2020): 917–64. http://dx.doi.org/10.3982/ecta16680.

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We prove the folk theorem for discounted repeated games with anonymous random matching. We allow non‐uniform matching, include asymmetric payoffs, and place no restrictions on the stage game other than full dimensionality. No record‐keeping or communication devices—including cheap talk communication and public randomization—are necessary.

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Cox, Shelley, Rohan Martin, Piyali Somaia, and Karen Smith. "The development of a data-matching algorithm to define the ‘case patient’." Australian Health Review 37, no. 1 (2013): 54. http://dx.doi.org/10.1071/ah11161.

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Objectives. To describe a model that matches electronic patient care records within a given case to one or more patients within that case. Method. This retrospective study included data from all metropolitan Ambulance Victoria electronic patient care records (n = 445 576) for the time period 1 January 2009–31 May 2010. Data were captured via VACIS (Ambulance Victoria, Melbourne, Vic., Australia), an in-field electronic data capture system linked to an integrated data warehouse database. The case patient algorithm included ‘Jaro–Winkler’, ‘Soundex’ and ‘weight matching’ conditions. Results. The case patient matching algorithm has a sensitivity of 99.98%, a specificity of 99.91% and an overall accuracy of 99.98%. Conclusions. The case patient algorithm provides Ambulance Victoria with a sophisticated, efficient and highly accurate method of matching patient records within a given case. This method has applicability to other emergency services where unique identifiers are case based rather than patient based. What is known about the topic? Accurate pre-hospital data that can be linked to patient outcomes is widely accepted as critical to support pre-hospital patient care and system performance. What does this paper add? There is a paucity of literature describing electronic matching of patient care records at the patient level rather than the case level. Ambulance Victoria has developed a complex yet efficient and highly accurate method for electronically matching patient records, in the absence of a patient-specific unique identifier. Linkage of patient information from multiple patient care records to determine if the records are for the same individual defines the ‘case patient’. What are the implications for practitioners? This paper describes a model of record linkage where patients are matched within a given case at the patient level as opposed to the case level. This methodology is applicable to other emergency services where unique identifiers are case based.

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HAUPTFLEISCH, ULF, ÁRNI EINARSSON, THORBJøRN J. ANDERSEN, ANTHONY NEWTON, and ARNTHOR GARDARSSON. "Matching thirty years of ecosystem monitoring with a high resolution microfossil record." Freshwater Biology 57, no. 10 (October 18, 2010): 1986–97. http://dx.doi.org/10.1111/j.1365-2427.2010.02518.x.

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Dou, Chenxiao, Yi Cui, Daniel Sun, Raymond Wong, Muhammad Atif, Guoqiang Li, and Rajiv Ranjan. "Unsupervised blocking and probabilistic parallelisation for record matching of distributed big data." Journal of Supercomputing 75, no. 2 (March 16, 2017): 623–45. http://dx.doi.org/10.1007/s11227-017-2008-8.

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Mekhaldi, Florian, Markus Czymzik, Florian Adolphi, Jesper Sjolte, Svante Björck, Ala Aldahan, Achim Brauer, Celia Martin-Puertas, Göran Possnert, and Raimund Muscheler. "Radionuclide wiggle matching reveals a nonsynchronous early Holocene climate oscillation in Greenland and western Europe around a grand solar minimum." Climate of the Past 16, no. 4 (July 3, 2020): 1145–57. http://dx.doi.org/10.5194/cp-16-1145-2020.

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Abstract. Several climate oscillations have been reported from the early Holocene superepoch, the best known of which is the Preboreal oscillation (PBO). It is still unclear how the PBO and the number of climate oscillations observed in Greenland ice cores and European terrestrial records are related to one another. This is mainly due to uncertainties in the chronologies of the records. Here, we present new, high-resolution 10Be concentration data from the varved Meerfelder Maar sediment record in Germany, spanning the period 11 310–11 000 years BP. These new data allow us to synchronize this well-studied record, as well as Greenland ice core records, with the IntCal13 timescale via radionuclide wiggle matching. In doing so, we show that the climate oscillations identified in Greenland and Europe between 11 450 and 11 000 years BP were not synchronous but terminated and began, respectively, with the onset of a grand solar minimum. A similar spatial anomaly pattern is found in a number of modeling studies on solar forcing of climate in the North Atlantic region. We further postulate that freshwater delivery to the North Atlantic would have had the potential to amplify solar forcing through a slowdown of the Atlantic meridional overturning circulation (AMOC) reinforcing surface air temperature anomalies in the region.

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