文献类型：期刊文献

英文题名：Defining the notion of 'Information Content' and reasoning about it in a database

作者：Xu, Kaibo[1,2];Feng, Junkang[1,2];Crowe, Malcolm[2]

第一作者：Xu, Kaibo

通讯作者：Xu, KB[1]

机构：[1]Beijing Union Univ, Coll Business, E Business Res Inst, Beijing, Peoples R China;[2]Univ W Scotland, Sch Comp, Database Res Grp, Paisley, Renfrew, Scotland

第一机构：北京联合大学商务学院

通讯机构：[1]corresponding author), Beijing Union Univ, Coll Business, E Business Res Inst, Beijing, Peoples R China.|[1141721]北京联合大学商务学院;[11417]北京联合大学;

年份：2009

卷号：18

期号：1

起止页码：29-59

外文期刊名：KNOWLEDGE AND INFORMATION SYSTEMS

收录：;EI(收录号：20211810283476);Scopus(收录号：2-s2.0-58549094313);WOS:【SCI-EXPANDED(收录号:WOS:000262483000002)】；

基金：This work is partly sponsored by the Chinese BMEC (Beijing Municipal Education Commission) under the grant number KM200311417153 for the Project of 'The Research on Information Bearing Capability'. The second author is also supported by a Senior Visiting Fellowship from the Royal Academy of Engineering, UK, 2005 and a grant for Distributed Information Systems Research from the Carnegie Trust for Universities of Scotland, 2007.

语种：英文

外文关键词：Information content; Reasoning; Data semantics; Semantic information theory; Inference rules

摘要：The problem of 'information content' of an information system appears elusive. In the field of databases, the information content of a database has been taken as the instance of a database. We argue that this view misses two fundamental points. One is a convincing conception of the phenomenon concerning information in databases, especially a properly defined notion of 'information content'. The other is a framework for reasoning about information content. In this paper, we suggest a modification of the well known definition of 'information content' given by Dretske(Knowledge and the flow of information,1981). We then define what we call the 'information content inclusion' relation (IIR for short) between two random events. We present a set of inference rules for reasoning about information content, which we call the IIR Rules. Then we explore how these ideas and the rules may be used in a database setting to look at databases and to derive otherwise hidden information by deriving new relations from a given set of IIR. A prototype is presented, which shows how the idea of IIR-Reasoning might be exploited in a database setting including the relationship between real world events and database values.