Current research in data modeling is motivated by the following dilemma: - At the application level - being confronted with slices of reality - details are perceived that, in general, cannot be rep...
当前数据建模的研究是由以下困境驱动的:-在应用程序层面-面对现实的片段-通常无法再现的细节被感知…
{"title":"Data abstraction tools","authors":"W. SchmidtJoachim","doi":"10.1145/960126.806917","DOIUrl":"https://doi.org/10.1145/960126.806917","url":null,"abstract":"Current research in data modeling is motivated by the following dilemma: - At the application level - being confronted with slices of reality - details are perceived that, in general, cannot be rep...","PeriodicalId":49524,"journal":{"name":"Sigmod Record","volume":"1 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"1980-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1145/960126.806917","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"64176458","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"The Papers of the Fourth Workshop on Computer Architecture for Non-Numeric Processing, Blue Mountain Lake, NY, USA, August 1-4, 1978","authors":"M. McGill","doi":"10.1145/982994","DOIUrl":"https://doi.org/10.1145/982994","url":null,"abstract":"","PeriodicalId":49524,"journal":{"name":"Sigmod Record","volume":"10 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"1978-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"64182498","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"SIGIR-SIGARCH-SIGMOD Third Workshop on Computer Architecture for Non-Numeric Processing, Blue Mountain Lake, Syracuse, NY, USA, May 17-18, 1977","authors":"M. McGill","doi":"10.1145/965641","DOIUrl":"https://doi.org/10.1145/965641","url":null,"abstract":"","PeriodicalId":49524,"journal":{"name":"Sigmod Record","volume":"9 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"1977-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"64178163","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.1201/9781420035414.ch4
Marie-Colette N. M. Van Lieshout, A. Baddeley
We discuss issues arising when a spatial pattern is observed within some bounded region of space, and one wishes to predict the process outside of this region (extrapolation) as well as to perform inference on features of the pattern that cannot be observed (interpolation). We focus on spatial cluster analysis. Here the interpolation arises from the fact that the centres of clustering are not observed. We take a Bayesian approach with a repulsive Markov prior, derive the posterior distribution of the complete data, i.e. cluster centres with associated offspring marks, and propose an adaptive coupling from the past algorithm to sample from this posterior. The approach is illustrated by means of the redwood data set (Ripley, 1977).
{"title":"Extrapolating and interpolating spatial patterns","authors":"Marie-Colette N. M. Van Lieshout, A. Baddeley","doi":"10.1201/9781420035414.ch4","DOIUrl":"https://doi.org/10.1201/9781420035414.ch4","url":null,"abstract":"We discuss issues arising when a spatial pattern is observed within some bounded region of space, and one wishes to predict the process outside of this region (extrapolation) as well as to perform inference on features of the pattern that cannot be observed (interpolation). We focus on spatial cluster analysis. Here the interpolation arises from the fact that the centres of clustering are not observed. We take a Bayesian approach with a repulsive Markov prior, derive the posterior distribution of the complete data, i.e. cluster centres with associated offspring marks, and propose an adaptive coupling from the past algorithm to sample from this posterior. The approach is illustrated by means of the redwood data set (Ripley, 1977).","PeriodicalId":49524,"journal":{"name":"Sigmod Record","volume":"11 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"65961627","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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