Knowledge-based temporal interpolation

Temporal interpolation is the task of bridging gaps between time-oriented concepts in a context-sensitive manner. It is a subtask important for solving the temporal-abstraction task-abstraction of interval-based, higher-level concepts from time-stamped data. We present a knowledge-based approach to the temporal-interpolation task and discuss in detail the precise knowledge required by that approach, its theoretical foundations, and the implications of the approach. The temporal-interpolation computational mechanism we discuss relies, among other knowledge types, on a temporal-persistence model. The temporal-persistence model employs local temporal-persistence functions that are temporally bidirectional (i.e. extend a belief measure in a predicate both into the future and into the past) and global, maximal-gap temporal-persistence functions that bridge gaps between interval-based predicates. We investigate the quantitative and qualitative properties implied by both types of persistence functions. We have implemented our approach in the RÉSUMÉ program and evaluated it in several different medical and engineering domains. We discuss the implications of our conceptual and computational methodology for acquisition, maintenance, reuse, and sharing of temporal-abstraction knowledge.     

A framework for knowledge-based temporal abstraction

A new domain-independent knowledge-based inference structure is presented, specific to the task of abstracting higher-level concepts from time-stamped data. The framework includes a model of time, parameters, events and contexts. A formal specification of a domain's temporal abstraction knowledge supports acquisition, maintenance, reuse and sharing of that knowledge.

The knowledge-based temporal abstraction method decomposes the temporal abstraction task into five subtasks. These subtasks are solved by five domain-independent temporal abstraction mechanisms. The temporal abstraction mechanisms depend on four domain-specific knowledge types: structural, classification (functional), temporal semantic (logical) and temporal dynamic (probabilistic) knowledge. Domain values for all knowledge types are specified when a temporal abstraction system is developed.

The knowledge-based temporal abstraction method has been implemented in the RÉSUMÉ system and has been evaluated in several clinical domains (protocol-based care, monitoring of children's growth and therapy of diabetes) and in an engineering domain (monitoring of traffic control), with encouraging results.     

Intrusion detection for mobile devices using the knowledge-based, temporal abstraction method

In this paper, a new approach for detecting previously unencountered malware targeting mobile device is proposed. In the proposed approach, time-stamped security data is continuously monitored within the target mobile device (i.e., smartphones, PDAs) and then processed by the knowledge-based temporal abstraction (KBTA) methodology. Using KBTA, continuously measured data (e.g., the number of sent SMSs) and events (e.g., software installation) are integrated with a mobile device security domain knowledge-base (i.e., an ontology for abstracting meaningful patterns from raw, time-oriented security data), to create higher level, time-oriented concepts and patterns, also known as temporal abstractions. Automatically-generated temporal abstractions are then monitored to detect suspicious temporal patterns and to issue an alert. These patterns are compatible with a set of predefined classes of malware as defined by a security expert (or the owner) employing a set of time and value constraints. The goal is to identify malicious behavior that other defensive technologies (e.g., antivirus or firewall) failed to detect. Since the abstraction derivation process is complex, the KBTA method was adapted for mobile devices that are limited in resources (i.e., CPU, memory, battery). To evaluate the proposed modified KBTA method a lightweight host-based intrusion detection system (HIDS), combined with central management capabilities for Android-based mobile phones, was developed. Evaluation results demonstrated the effectiveness of the new approach in detecting malicious applications on mobile devices (detection rate above 94% in most scenarios) and the feasibility of running such a system on mobile devices (CPU consumption was 3% on average).     

KB-SCHED: Knowledge-based scheduler for complex and dynamic systems

Scheduling problems are becoming more and more complex everyday. This makes the current rules and algorithms difficult to comply with the requirements. New machines with the capabilities of processing more than one jobs is being developed. Sometimes one job is divided into parts and processed by more than one machine at the same time. These make the current algorithms insufficient. Artificial intelligence technologies, especially expert systems are proven to deal with such dynamic complex problems in several domains. In this study, an example of such a complex problem is introduced and knowledge-based scheduling for these kind of problems is elaborated with a real life industrial example.     

基于知识库的语言翻译系统研究

语言翻译是工作和学习中经常要做的事,传统的语言翻译是基于词法结构分析,然而自然语言并不是那么的规范,这导致了这种翻译方式存在本质上的缺陷,不管算法如何改进,翻译结果和人工翻译都会相差很远。本文以英汉翻译为例介绍了基于知识库的语言翻译,详细讲解了基于知识库翻译的原理,以及这种翻译方式与传统的基于词法结构分析的翻译方式相比具有的优越性,并实现了一个简单的基于知识库的翻译软件。     

An active database architecture for knowledge-based incremental abstraction of complex concepts from continuously arriving time-oriented raw data

An effective solution to the tasks of continuous monitoring and aggregation querying of complex domain-meaningful concepts and patterns in environments featuring large continuously changing data sets is very important for many domains. Typical domains include: making financial decisions, integrating intelligence information from multiple sources, evaluating the effects of traffic controllers’ actions, detection of security threats in communication networks, planning and monitoring in robotics, and management of chronic patients in medical domains. In this paper, we present a general domain-independent method for an effective solution of these two tasks. Our method involves incremental creation of meaningful, interval-based abstractions, from raw, time-stamped data continuously arriving from multiple sources, which is supported by the accumulation and continuous validation of the created abstractions. We implemented our method in the Momentum system, which is an active knowledge-based time-oriented database—a temporal extension of the active-database concept that we propose for incremental application of knowledge to continuously arriving time-oriented data. We evaluated the Momentum system in a medical domain within a database of 1,000 patients monitored after bone-marrow transplantation, and a knowledge base of complex abstractions regarding more than 100 raw-data types and about 400 concept types derivable from them. Initial evaluations are highly encouraging with regards to the feasibility of the whole approach.     

Counterexample-guided predicate abstraction of hybrid systems

Predicate abstraction has emerged to be a powerful technique for extracting finite-state models from infinite-state systems, and has been recently shown to enhance the effectiveness of the reachability computation techniques for hybrid systems. Given a hybrid system with linear dynamics and a set of linear predicates, the verifier performs an on-the-fly search of the finite discrete quotient whose states correspond to the truth assignments to the input predicates. The success of this approach depends on the choice of the predicates used for abstraction. In this paper, we focus on identifying these predicates automatically by analyzing spurious counterexamples generated by the search in the abstract state-space. We present the basic techniques for discovering new predicates that will rule out closely related spurious counterexamples, optimizations of these techniques, implementation of these in the verification tool, and case studies demonstrating the promise of the approach.     

Knowledge-based organization evaluation

Knowledge has become the main value driver for modern organizations. In particular, knowledge-based organizations (KBOs) allocate resources to intangible assets (e.g., R&D) in the rapidly changing and highly competitive business environment in order to gain competitive advantages. Therefore, how to evaluate knowledge-based organizations has become one of the most important issues in knowledge management. The purpose of this paper is to provide a framework for the evaluation of KBOs under uncertainty, using the state-of-the-art methodology of Real Options. We define the unique features of KBOs and explain their value drivers. The present study's contribution is threefold: (1) it bridges the gaps in knowledge management literature related to evaluating knowledge capital; (2) it provides a systematic application of Real Options models in the context of knowledge-based organization evaluation; and, (3) it uses a real-world case to demonstrate the implications of the main findings for management.     

视频摘要技术综述

目的 类似于文本摘要,视频摘要是对视频内容的总结。为了合理地评估视频摘要领域的研究进展,正确导向视频摘要的继续研究,本文归纳总结视频摘要技术的主要研究方法和显著性成果,对视频摘要技术进行综述。方法 依据视频摘要的两个主要生成步骤:视频内容分析和摘要生成分别介绍视频摘要的主要研究方法。同时,分析了近5年视频摘要领域的研究状况,对视频摘要发展的新趋势:实时视频摘要和多视角视频摘要进行了阐述。最后,还对视频摘要的评价系统进行了分类总结。结果 对视频摘要进行综述,对摘要中的语义获取难题提出了2种指导性建议。并依据分析结果,展望了视频摘要技术未来的发展方向。结论 视频摘要技术作为视频内容理解的重要组成部分,有较大研究价值。而目前,视频摘要在视频语义表达和摘要评价系统方面并不精确完善,还需进一步的深入研究。     

Knowledge-based management support: an application to the IS change agent role problem

This paper explores how the change agent role problem can be detected and alleviated with the help of a knowledge-based support tool. The mismatch between MIS specialist change agent role style and IS environment is a complex problem to solve. The problem results when the MIS specialist's role outlines responsibilities that cannot possibly manage the change and related uncertainty surrounding an IS initiative. MIS specialists are classified by change agent roles that reflect varying types of responsibility for social and technological change. Evaluation of IS environment constructs provide the MIS specialist with a formal way to compare the different IS change agent roles to moderate IS uncertainty, thereby increasing the likelihood of IS success. The relevant IS change agentry relationships are identified from a literature review. Results from a multiple case study were used to develop and validate a conceptual model of the IS change agentry application domain. Based on this model, a suitable knowledge representation scheme is developed that provides a high level structure to the IS change agent role application domain and also guides the reasoning process. The proposed approach supports the interpretation of domain relationships applicable when choosing among change agent roles. Therefore, it could be used by IS specialists proactively to facilitate the analysis of complex domain facts prior to committing resources to a change agent role. The approach is illustrated with case data. Managerial implications of the study are discussed.     

知识经济条件下的CALS

CALS是在计算机辅助后勤保障基础上发展起来的装备采办策略。该文深入研究了CALS产生的背景及其发展历程,并结合其在实际应用中的成果剖析了其深刻内涵。在此基础上,结合知识经济和知识经济条件下装备保障的特点,分析了CALS对装备保障的影响,认为CALS将使装备保障的流程发生改变,推动装备保障向着精确化、信息化的方向发展。     

Object-oriented motion abstraction

An important problem in the production of an animation sequence is the great amount of information necessary to control and specify the motion. Specification of complex animation sequences with a smaller amount of information is possible if they are built over some abstracted sequences. Abstraction supports dealing with complexity by structuring, so that the necessary features are made available while those that are not necessary are hidden. In our work, motion abstraction is used to build complex animation sequences with the help of object-oriented concepts. A parametric key-frame interpolation method is used for producing the in-between frames of an animation sequence. The parameters that define the motion of a model, in our work, are position, orientation, size, shape and colour. Orientation transformations are implemented by unit quaternions.     

Abstraction of levels of abstraction

The notion of level of abstraction (LoA) is one of the foundations of the Floridi's Philosophy of Information. It also serves for many practical purposes as in information ethics. But the notion of abstraction is not new; it has been given many different meanings in various fields, especially in scientific disciplines and, in particular, in computer science. Our purpose here is to examine the use of abstraction in Floridi's works in conjunction with some of the meanings of abstraction in computer science. The article is divided into five sections. After a general introduction to the Floridi's method of abstraction (MoA) in Section 1, Section 2 revisits Floridi's definition of abstraction and Section 3 gives the different senses of abstraction in computer science. The Section 4 compares them with the Floridi's LoAs and proposes to generalise the Floridi's approach to abstraction using an abstraction of the LoAs, while Section 5 concludes on what we think to be some new arguments in favour of MoA and LoA.     

Software Agent间的知识级通信

提供了一种综合了概念表示语言（ＣＲＬＥ）,共享本体论、消息表示语言（ＭＲＬ）和通信促进器的共享信息和知识的高层模型,以实现Ｓｏｆｔｗａｒｅ Ａｇｅｎｔ间的知识级通信。     

Knowledge-based systems in civil engineering: Three case studies

Although substantial advances have been achieved in last twenty years, in practice we are still far from taking full advantage of the potential of knowledge-based systems (KBS). Very few KBS have survived their evaluation period and only one third of those that were initially reported as successful are still in use. The primary purpose of the paper is to report on three KBS applications that have been developed for research purposes in the field of civil engineering. The main challenge underlying all three projects has been to develop computer support systems that would induce changes and improvements to the way that engineers solve their everyday problems. A great deal of effort has been put into eliciting knowledge and reasoning strategies from engineering experts with the aim of building up a computer model of their expertise in order to assist engineers in their decision-making processes. The paper closes by highlighting the principal achievements and the main issues concerning the future development of KBS for solving real life problems.     

Knowledge-based system for railway scheduling

In this paper, we describe a Knowledge-Based railway scheduling system (called RSS) for Taiwan Railway Administration's (TRA) railway scheduling operations. In our approach, the scheduling process is divided into two levels: global scheduling and local scheduling. In global scheduling, an initial train diagram is established by the Global Scheduler according to the master scheduling plan without considering conflicts. In local scheduling, scheduling conflicts are repaired by Local Scheduler. An embedded knowledge base provides advice for conflict resolution. Since cycles may exist among a sequence of repairs during the repair process, we also propose a cycle detection and resolution scheme in this paper. Through a graphic user interface, the user can interact with the Automatic Scheduler to solve the large-scale complex train scheduling problem in a cooperative and flexible fashion.     

Knowledge-based information retrieval

A knowledge-based system is used as a front-end to a very large database to increase the relevance of the information being retrieved. The subject domain of the data base is modelled in a semantic network and the queries to the database are expanded according to the semantic model. An experiment has been performed on a bibliographic database, by developing the prototype KNOWIT, a knowledge-based front-end to the information retrieval system ESA-QUEST¹. An experimental evaluation shows that the number of relevant bibliographic references retrieved with the knowledge-based front-end is significantly improved, without compromising the precision of the retrieval.     

Knowledge-based part correspondence

This paper presents a direct method for finding corresponding pairs of parts between two shapes. Statistical knowledge about a large number of parts from many different objects is used to find a part correspondence between two previously unseen input shapes. No class membership information is required. The knowledge-based approach is shown to produce significantly better results than a classical metric distance approach. The potential role of part correspondence as a complement to geometric and structural comparisons is discussed.     

Strings and the sequence abstraction in Pascal

This paper examines the sequence abstraction known in Pascal as the ‘file’, and shows how sequences of characters (‘strings’ in the SNOBOL sense) may be cleanly fitted into Pascal-like languages. The specific problems of providing the suggested facilities as an experimental extension to Pascal are examined.     

Knowledge-based programs

Summary.  Reasoning about activities in a distributed computer system at the level of the knowledge of individuals and groups allows us to abstract away from many concrete details of the system we are considering. In this paper, we make use of two notions introduced in our recent book to facilitate designing and reasoning about systems in terms of knowledge. The first notion is that of a knowledge-based program. A knowledge-based program is a syntactic object: a program with tests for knowledge. The second notion is that of a context, which captures the setting in which a program is to be executed. In a given context, a standard program (one without tests for knowledge) is represented by (i.e., corresponds in a precise sense to) a unique system. A knowledge-based program, on the other hand, may be represented by no system, one system, or many systems. In this paper, we provide a sufficient condition for a knowledge-based program to be represented in a unique way in a given context. This condition applies to many cases of interest, and covers many of the knowledge-based programs considered in the literature. We also completely characterize the complexity of determining whether a given knowledge-based program has a unique representation, or any representation at all, in a given finite-state context. Received: October 1995 / Accepted: February 1997