This paper proposes a checking method based on mutual instances and discusses three key problems in the method： how to deal with mistakes in the mutual instances and how to deal with too many or too few mutual instan...This paper proposes a checking method based on mutual instances and discusses three key problems in the method： how to deal with mistakes in the mutual instances and how to deal with too many or too few mutual instances. It provides the checking based on the weighted mutual instances considering fault tolerance, gives a way to partition the large-scale mutual instances, and proposes a process greatly reducing the manual annotation work to get more mutual instances. Intension annotation that improves the checking method is also discussed. The method is practical and effective to check subsumption relations between concept queries in different ontologies based on mutual instances.展开更多
订单驱动进销存管理系统是基于订单实现计划生产、合理调度、顺畅销售而建立的电子商务应用系统。除了能够根据订单产生相应的库存信息和生产计划之外,它还有按要求查询、分类盘点、打印单据等功能。本系统用Microsoft SQL Server 2000...订单驱动进销存管理系统是基于订单实现计划生产、合理调度、顺畅销售而建立的电子商务应用系统。除了能够根据订单产生相应的库存信息和生产计划之外,它还有按要求查询、分类盘点、打印单据等功能。本系统用Microsoft SQL Server 2000做后台数据库,以VB.NET2005作为前台程序的开发工具,在数据库和VB.NET之间采用ADO控件实现数据库和操作程序的无缝连接,并利用Visual Studio 2005自带的Crystalreports生成打印报表。多条件查询、平行筛选、筛选条件互驱动与数据库结合产生了更灵活的数据组合方式。本系统更好地促进了生产销售的进行,有效地解决当前企业存在的信息化不足、机密性准确性差、工作效率低落、仓库管理很不合理、不能及时根据需要调整库存等一系列的问题。展开更多
This paper proposes a novel Chinese-English Cross-Lingual Information Retrieval (CECLIR) model PME, in which bilingual dictionary and comparable corpora are used to translate the query terms. The Proximity and mutua...This paper proposes a novel Chinese-English Cross-Lingual Information Retrieval (CECLIR) model PME, in which bilingual dictionary and comparable corpora are used to translate the query terms. The Proximity and mutual information of the term-pairs in the Chinese and English comparable corpora are employed not only to resolve the translation ambiguities but also to perform the query expansion so as to deal with the out-of-vocabulary issues in the CECLIR. The evaluation results show that the query precision of PME algorithm is about 84.4% of the monolingual information retrieval.展开更多
基金Supported by the National Natural Sciences Foundation of China(60373066 ,60425206 ,90412003) , National Grand Fundamental Research 973 Pro-gramof China(2002CB312000) , National Research Foundation for the Doctoral Pro-gramof Higher Education of China (20020286004)
文摘This paper proposes a checking method based on mutual instances and discusses three key problems in the method： how to deal with mistakes in the mutual instances and how to deal with too many or too few mutual instances. It provides the checking based on the weighted mutual instances considering fault tolerance, gives a way to partition the large-scale mutual instances, and proposes a process greatly reducing the manual annotation work to get more mutual instances. Intension annotation that improves the checking method is also discussed. The method is practical and effective to check subsumption relations between concept queries in different ontologies based on mutual instances.
文摘订单驱动进销存管理系统是基于订单实现计划生产、合理调度、顺畅销售而建立的电子商务应用系统。除了能够根据订单产生相应的库存信息和生产计划之外,它还有按要求查询、分类盘点、打印单据等功能。本系统用Microsoft SQL Server 2000做后台数据库,以VB.NET2005作为前台程序的开发工具,在数据库和VB.NET之间采用ADO控件实现数据库和操作程序的无缝连接,并利用Visual Studio 2005自带的Crystalreports生成打印报表。多条件查询、平行筛选、筛选条件互驱动与数据库结合产生了更灵活的数据组合方式。本系统更好地促进了生产销售的进行,有效地解决当前企业存在的信息化不足、机密性准确性差、工作效率低落、仓库管理很不合理、不能及时根据需要调整库存等一系列的问题。
基金the National Natural Science Foundation of China (No.69983009).Received November 26, 1999 revised November 1, 2000.
文摘This paper proposes a novel Chinese-English Cross-Lingual Information Retrieval (CECLIR) model PME, in which bilingual dictionary and comparable corpora are used to translate the query terms. The Proximity and mutual information of the term-pairs in the Chinese and English comparable corpora are employed not only to resolve the translation ambiguities but also to perform the query expansion so as to deal with the out-of-vocabulary issues in the CECLIR. The evaluation results show that the query precision of PME algorithm is about 84.4% of the monolingual information retrieval.
