EarlyData knowledge base for material decisions in building design

To make use of the great opportunities for emission reduction in early building design, future emissions need to be calculated when only geometric, but no detailed material information about a building is available. Currently, early design phase life cycle assessments (LCAs) are heavily reliant on assumptions of specific material choices, leading to single point emission values which suggest a precision not representative for an early design stage. By adding knowledge about possible locations and functions of materials within a building to life cycle inventory (LCI) data, the EarlyData knowledge base makes LCA data sets accessible and more transparent. Additionally, “generic building parts” are defined, which describe building parts independently of precise material choices as a combination of layers with specific functions. During evaluation, enriched LCI data and generic building parts enable assessment of a vast number of possible material combinations at once. Thus, instead of single value results for a particular material combination, ranges of results are displayed revealing the building parts with the greatest emission reduction potential. The application of the EarlyData tool is illustrated on a use case comparing a wood building and a concrete building. The database is developed with extensibility in mind, to include other criteria, such as (life cycle) costs.     

从经典逻辑知识构建ASP知识库的新方法

回答集程序设计(ASP)是一种主流的非单调知识表示工具。为了能够在利用ASP求解问题过程中使用现有的以经典逻辑表示的知识,给出了一种把以谓词逻辑公式表示的约束型知识和定义型知识转化为ASP程序或知识库的新方法,并以实例说明了其有效性。该方法满足转化后ASP程序的回答集与原公式集的模型具有一一对应关系。在实际应用中,该方法提供了一项从现存的以谓词逻辑为表示语言的知识库,构建以ASP为知识表示语言的非单调知识库的技术。     

Addition and removal of information for a knowledge base with incomplete information

A knowledge base containing incomplete information in the form of disjunctions and negative information shows difficulties regarding the update operators. In this paper simple and straightforward definitions are given for an ‘adding’ operator (‘+’) and a ‘removing’ operator (‘−’) using Hebrand models.     

Intelligent systems using Web-pages as knowledge base for statistical decision making

In this paper, we propose an approach to the construction of an intelligent system that handles various domain information provided on the Internet. The intelligent system adopts statistical decision-making as its reasoning framework and automatically constructs probabilistic knowledge, required for its decision-making, from Web-pages. This construction of probabilistic knowledge is carried out using aprobability interpretation idea that transforms statements in Web-pages into constraints on the subjective probabilities of a person who describes the statements. In this paper, we particularly focus on describing the basic idea of our approach and on discussing difficulties in our approach, including our perspective. Kazunori Fujimoto: He received bachelor’s degree from Department of Electrical Engineering, Doshisha University, Japan, in 1989, and master’s degree from Division of Applied Systems Science, Kyoto University, Japan, in 1992. From there, he joined NTT Electrical Communications Laboratories, Tokyo, Japan, and has been engaged in research on Artificial Intelligence. He is currently interested in probabilistic reasoning, knowledge acquisition, and especially in quantitative approaches to research in human cognition and behavior. Mr. Fujimoto is a member of Decision Analysis Society, The Behaviormetric Society of Japan, Japanese Society for Artificial Intelligence, Information Processing Society of Japan, and Japanese Society for Fuzzy Theory and Systems. Kazumitsu Matsuzawa: He received B.S. and M.S. degrees in electronic engineering from Tokyo Institute of Technology, Tokyo, Japan, in 1975 and 1977. From there, he joined NTT Electrical Communications Laboratories, Tokyo, Japan, and has been engaged in research on computer architecture and the design of LSI. He is currently concerned with AI technology. Mr. Matsuzawa is a member of The Institute of Electronics, Information and Communication Engineers, Information Processing Society of Japan, Japanese Society for Artificial Intelligence, and Japanese Society for Fuzzy Theory and Systems.     

工艺设计知识库的建造与维护

文中根据工艺设计知识的特点,构造了层次化的知识表达、组织与知识库模型,分析了工艺知识库不一致的表现形式,并给出了相应的一致性验证算法,提出了基于广义决策表的知识库完备性检查方法。     

Role taking and knowledge building in a blended university course

Role taking is an established approach for promoting social cognition. Playing a specific role within a group could lead students to exercise collective cognitive responsibility for collaborative knowledge building. Two studies explored the relationship of role taking to participation in a blended university course. Students participated in the same knowledge-building activity over three consecutive, five-week modules and enacted four roles designed in alignment with knowledge building pedagogy (Scardamalia and Bereiter 2010). In Study 1, 59 students were distributed into groups with two conditions: students who took a role in Module 2 and students who did not take a role, using Module 1 and 3 as pre and post tests. Results showed no differences in participation in Module 1, higher levels of writing and reading for role takers in Module 2, and this pattern was sustained in Module 3. Students with the Synthesizer role were the most active in terms of writing and the second most active for reading; students with the Social Tutor role were the most active for reading. In Study 2, 143 students were divided into groups with two conditions: students who took a role in Module 1 and students who did not take a role. Content analysis revealed that role takers tended to vary their contributions more than non-role takers by proposing more problems, synthesizing the discourse, reflecting on the process and organization of activity. They also assumed appropriate responsibilities for their role: the Skeptic prioritizes questioning of content, the Synthesizer emphasizes synthesizing of content, and the Social Tutor privileges maintaining of relationships. Implications of designing role taking to foster knowledge building in university blended courses are discussed.     

Wiki-supported learning and knowledge building: effects of incongruity between knowledge and information

This study describes the empirical test of a theoretical model of knowledge building with wikis that was recently introduced by Cress and Kimmerle. The underlying assumption of this model is that both learning (as an internal, individual process) and knowledge building (as the creation of public knowledge) are based on the interplay between an individual's knowledge and the information available in the wiki. Incongruity between individual knowledge and the information contained in the wiki will lead to learning (through the acquisition of factual and conceptual knowledge) and to knowledge building (through assimilation and accommodation). In three conditions, the experiment provided the participants with different levels of incongruity between their individual knowledge and information in the wiki by varying the amount of information that was contained in the wiki, while the amount of information that the participants possessed was kept constant. As predicted, the results confirmed that a medium level of incongruity between an individual's knowledge and the information that a wiki contains will best support learning. Moreover, a medium level of incongruity leads to more accommodative knowledge building despite the fact that high and medium levels of incongruity will result in similar amounts of assimilative knowledge building. The implications of these findings were discussed in the concluding remarks.     

Designing information systems for nursing practice: data base and knowledge base requirements of different organizational technologies

One of the major causes of failure of information system design is the failure of developers to take into account the organizational environment, thereby leading to an unusable system. The first step in designing an effective system is to describe the user's view of the system, a view that incorporates how the system will help users to manage information in their particular organizational environment. For nurses involved in designing a nursing information system, a useful way of considering the organizational environment is provided by Perrow. The organizational technologies described by Perrow can be viewed as different models of nursing practice, each with particular requirements for a knowledge base and a data base. Nurses can identify the model that most closely corresponds to actual or desired nursing practice in their agencies and use the model's associated knowledge base and data base requirements as a guide to specifying the information system to be developed.     

语义为核心的多文种信息处理平台的模型

提出了一个基于语义、面向自然语言处理的多文种信息处理平台的模型SMIPP.该模型主要由应用程序/用户接口层、文字输入层和文字输出层、信息处理服务层、语料库层、多文种代码体系SemaCode层和语言Ontology层组成,该平台把各种语言文字统一用具有自描述能力的SemaCode表示,并通过语言Ontology来表示词汇的语义以及在各个文种间的联系,再通过服务形式提供各种基于语料库的文字信息处理功能,是一个全新的多文种信息处理模型.     

Observations of a firm's information processing with a data base management system

The organization in this study used all versions of IMS, from IMS 1 through IMS VS 1.01, over the period 1970–1975. During this period, the number of messages processed steadily increased from 6000 in October 1970 to a maximum in excess of 150,000 in September 1974. This volume enhancement was achieved by solving a sequence of problems concerning IMS software, data base design, or program coding. Perhaps the most important factors supporting the increase were two improvements in IMS software: one was the data base buffer pool introduced with IMS 2; the other the feature introduced with IMS VS that, unlike the previous versions, enabled the simultaneous updating of different data base segments belonging to the same type.     

Expert systems for knowledge management: crossing the chasm between information processing and sense making

Based on insights from research in information systems, information science, business strategy and organization science, this paper develops the bases for advancing the paradigm of AI and expert systems technologies to account for two related issues: (a) dynamic radical discontinuous change impacting organizational performance; and (b) human sense-making processes that can complement the machine learning capabilities for designing and implementing more effective knowledge management systems.     

A Logical Framework for Knowledge Base Maintenance

The maintenance sequences of a knowledge base and their limits are introduced.Some concepts used in knowledge base maintenance,such as new laws,user‘s rejections,and reconstructions of a knowledge base are defined;the related theorems are proved.A procedure is defined using transition systems;it generates maintenance sequences for a given user‘s model and a knowledge base.It is proved that all sequences produced by the procedure are convergent,and their limit is the set of true sentences of the model.Some computational aspects of reconstructions are studied.An R-calculus is given to deduce a reconstruction when a knowledge base meets a user‘s rejection.The work is compared with AGM‘s theory of belief revision.     

A unification-based approach for knowledge base verification

Abstract: Knowledge base verification, a part of the validation process in expert system development, includes checking the knowledge base for completeness and consistency to guard against a variety of errors that can arise during the process of transferring expertise from a human expert to a computer system. Regardless of how an expert system is developed, its developers can profit from a systematic check of the knowledge base without gathering extensive data for test runs, even before the full reasoning mechanism is functioning. Until recently knowledge base verification has been largely ignored, which has led to expert systems with knowledge base errors and no safety factors for correctness. We propose a unification-based approach for verification of a knowledge base represented in the form of production rules and facts. This approach can determine conflicting, redundant, subsumed and circular rules; redundant if-conditions in rules; dead-end rules; and cycles and contradiction in rules.     

A Prolog knowledge base for drug interactions

This article describes a Prolog knowledge base for drug interactions. The knowledge base combines information from two databases: one of drug interactions and the second of drug chemical names and structures. Researchers can interrogate this knowledge base to answer questions about relationships between interacting drugs and their chemical components.     

Entity-related paths modeling for knowledge base completion

Knowledge bases (KBs) are far from complete, necessitating a demand for KB completion. Among various methods, embedding has received increasing attention in recent years. PTransE, an important approach using embedding method in KB completion, considers multiple-step relation paths based on TransE, but ignores the association between entity and their related entities with the same direct relationships. In this paper, we propose an approach called EPTransE, which considers this kind of association. As a matter of fact, the dissimilarity of these related entities should be taken into consideration and it should not exceed a certain threshold. EPTransE adjusts the embedding vector of an entity by comparing it with its related entities which are connected by the same direct relationship. EPTransE further makes the euclidean distance between them less than a certain threshold. Therefore, the embedding vectors of entities are able to contain rich semantic information, which is valuable for KB completion. In experiments, we evaluated our approach on two tasks, including entity prediction and relation prediction. Experimental results show that our idea of considering the dissimilarity of related entities with the same direct relationships is effective.