Effectiveness of expert semantic knowledge as a navigational aid within hypertext

Hypertext systems parse documents into content nodes connected by machine supported links or relationships. Many hypertext researchers claim that the node-link relationships of hypertext provide an information organization that models the structure of human knowledge and should therefore facilitate information access (Fiderio 1988). Yet, failures of information access occur when users lack an understanding of the overall scope and organization of a hypertext system (Gay and Mazur 1991). To support this understanding, the present research incorporated expert-based domain semantics in the design of prosthetic devices for hypertext navigation. The task domain was documentation for a word processing system. In the first experiment, the pathfinder algorithm (Schvaneveldt 1990) and cluster analysis were used to identify a set of expertbased semantic relationships between word-processing concepts. The results from these analyses contributed to the design of two prostheses to assist hypertext navigation: A hierarchical index and a local semantic browser. These aids were tested in a second experiment, crossing type of on-line documentation (semantically enhanced hypertext or an alphabetically indexed text) with level of subject expertise (novice or expert). Both performance and strategy measures suggest that the semantic prostheses improved the accessibility of information for novice users without hampering expert performance.     

Aesthetics of navigational performance in hypertext

A hypertext learner navigates with a instinctive feeling for a knowledge. The learner does not know her queries, although she has a feeling for them. A learners navigation appears as complete upon the emergence of an aesthetic pleasure, called rasa. The order of arrival or the associational logic and even the temporal order are not relevant to this emergence. The completeness of aesthetics is important. The learner does not look for the intention of the writer, neither does she look for significance. Lexia has a suggestive power and she is suggested in the arrival of aesthetics. Hypertext learning does not depend on communication. The learner in her pleasure transgresses the bounds of space-time to be in communion with several writers/learners. Hypertext learning does not appear to be fundamentally different from the analog learning; however, in performance, as in navigation, the learner assumes a mental state that helps her in her emergence into aesthetic bliss, of an arrival to the completed lexial navigation. This completeness is owing to aesthetics and is not owing to either the semantics or the query-fulfilling qualities.     

Using 3D sound as a navigational aid in virtual environments

As current virtual environments are less visually rich than real-world environments, careful consideration must be given to their design to ameliorate the lack of visual cues. One important design criterion in this respect is to make certain that adequate navigational cues are incorporated into complex virtual worlds. In this paper we show that adding 3D spatialized sound to a virtual environment can help people navigate through it. We conducted an experiment to determine if the incorporation of 3D sound (a) helps people find specific locations in the environment, and (b) influences the extent to which people acquire spatial knowledge about their environment. Our results show that the addition of 3D sound did reduce time taken to locate objects in a complex environment. However, the addition of sound did not increase the amount of spatial knowledge users were able to acquire. In fact, the addition of 3D auditory sound cues appears to suppress the development of overall spatial knowledge of the virtual environment.     

An evaluation of different navigational tools in using hypertext

Hypertext is a widely used form of information presentation which has gained wide popularity in the last few years due to the ease with which information can be portrayed and accessed. However, the very flexibility of hypertext creates problems of user disorientation and cognitive overhead. Designers in the past have tried to combat these problems by providing users with a myriad of navigational tools, with the most widely employed tools being a map and an index. The primary objective of this study was to evaluate the usefulness of the above mentioned navigational tools in alleviating the problems associated with using a hypertext system. For the purpose of this study, a hypertext package was developed using Hypercard on “Ancient Civilizations.” The experiment explored three variables: types of navigational tool available to the user (Map, Index and Combination of map and index); hypertext size (Small stack, Large stack) and trials (Before, After). The results of the study indicate significant differences in the use and effect of the navigational tools.     

Using 3D sound as a navigational aid in virtual environments

As current virtual environments are less visually rich than real-world environments, careful consideration must be given to their design to ameliorate the lack of visual cues. One important design criterion in this respect is to make certain that adequate navigational cues are incorporated into complex virtual worlds. In this paper we show that adding 3D spatialized sound to a virtual environment can help people navigate through it. We conducted an experiment to determine if the incorporation of 3D sound (a) helps people find specific locations in the environment, and (b) influences the extent to which people acquire spatial knowledge about their environment. Our results show that the addition of 3D sound did reduce time taken to locate objects in a complex environment. However, the addition of sound did not increase the amount of spatial knowledge users were able to acquire. In fact, the addition of 3D auditory sound cues appears to suppress the development of overall spatial knowledge of the virtual environment.     

Are expert users always better searchers? Interaction of expertise and semantic grouping in hypertext search tasks

The facilitative effect of expertise in hypertext information retrieval (IR) tasks has been widely reported in related literature. However, recent theories of human expertise question the robustness of this result, since previous works have not fully considered the interaction between user and system characteristics. In this study, the constraint attunement hypothesis (CAH) is considered in order to predict that the effect of expertise in IR would appear only when the user and system characteristics can be combined successfully. Results from an experiment revealed that expert users outperformed novice users in IR when the elements of a system interface are organized semantically, but not when organized randomly. Results are discussed in the framework of the CAH supporting the interactive nature of human behaviour in HCI.     

Incremental maintenance of semantic links in dynamically changing hypertext systems

One purported advantage of hypertext systems is the ability to move between semantically related parts of a document (or family of documents). If the document is undergoing frequent modification (for example while an author is writing a book or while a software design stored in the hypertext system is evolving) the question arises as to how to incrementally maintain semantic interconnections in the face of the modifications.

The paper presents an optimal technique for the incremental maintenance of such interconnections as a document evolves. The technique, based on theories of information retrieval based on lexical affinities and theories of incremental computation, updates semantic interconnections as nodes are checked into the hypertext system (either new or as a result of an edit). Because we use the semantic weight of lexical affinities to determine which affinities are meaningful in the global context of the document, introducing a new affinity or changing the weight of an existing affinity can potentially have an effect on any node in the system. The challenge met by our algorithm is to guarantee that despite this potentially arbitrary impact, we still update link information optimally.

Once established the semantic interconnections are used to allow the user to move from node to node based not on rigid connections but instead on dynamically determined semantic interrelationships among the nodes.     

The effect of questioning on concept learning within a hypertext system

Abstract Two studies report upon the effect of asking learners to answer questions when learning in a hypertext environment, even when no immediate feedback is given to learners about the appropriateness of their responses. Such questions may be useful as a means to induce responses that can be used to monitor learning, but here the hypothesis was investigated that their inclusion would also improve learning directly. In the first study, 80 student teachers answered embedded multiple-choice questions that encouraged analysis of examples. Concept learning achieved using this environment was significantly reduced when compared with an environment requiring no such responses. In the second study, a cohort of 68 students were asked to summarise the information illustrated by the examples. Here, learning was significantly improved as compared with the no-response condition.     

超文本教学系统中学生知识的自适应测评研究

知识空间理论提供了一种描述给定知识域结构的方法,它被看作是有效评估学生知识程度的一个基础,但它是一种基于问题的知识空间理论.利用超文本结构和知识空间结构相似的特性,将知识点超文本结构转换为超文本知识空间,使知识空间理论建立在知识点上,并在此超文本知识空间上利用自动机原理实现对学生知识结构的自适应测评过程.给出了基于自动机的自适应测评算法,并进一步分析了算法的有效性和复杂性.     

The effects of graphical overviews on knowledge acquisition in hypertext

Abstract A central aspect of designing hypertext for learning concerns the structure of the information in the hypertext and the view the learner is offered of this structure. In this study, a hypertext environment was enhanced with a graphical overview that represented the basic, inherent, structure of the domain and the layout was designed in such a way that learners were unobtrusively encouraged to follow a sequence of exploration that followed the domain structure. This so-called 'visual' lay-out was compared with two lay-outs that presented randomly positioned nodes. One of these two lay-outs contained hints (using 'highlighting') to stimulate learners to follow a domain related exploration similar to the one incorporated in the visual lay-out. The other ('control') lay-out did not provide such hints. Results showed that participants from both the 'visual' and the 'hints' conditions demonstrated a more domain-related exploration pattern than participants from the 'control' condition. Participants in the 'visual' lay-out did not show a better recall of the content of the nodes as such, but showed a significantly better acquisition of knowledge of structure than participants from the other two conditions. These data indicate that a visual display conveys knowledge in its own right and that knowledge gained does not depend on the exploration route followed in the hypertext material.     

A semantic fuzzy expert system for a fuzzy balanced scorecard

Balanced scorecard is a widely recognized tool to support decision making in business management. Unfortunately, current balanced scorecard-based systems present two drawbacks: they do not allow to define explicitly the semantics of the underlying knowledge and they are not able to deal with imprecision and vagueness. To overcome these limitations, in this paper we propose a semantic fuzzy expert system which implements a generic framework for the balanced scorecard. In our approach, knowledge about balanced scorecard variables is represented using an OWL ontology, therefore allowing reuse and sharing of the model among different companies. The ontology acts as the basis for the fuzzy expert system, which uses highly interpretable fuzzy IF–THEN rules to infer new knowledge. Results are valuable pieces of information to help managers to improve the achievement of the strategic objectives of the company. A main contribution of this work it that the system is general and can be customized to adapt to different scenarios.     

Interactive induction of expert knowledge

The process of extracting, structuring and organizing elicited knowledge (called knowledge acquisition) is a bottleneck in developing knowledge-based systems. A manual approach that elicits domain knowledge by interviewing human experts typically has problems, because the experts are often unable to articulate their reasoning rules. An automatic approach that induces knowledge from a set of training cases also suffers from the unavailability of sufficient training cases. We present an integrated approach that combines the strengths of both methods to compensate for their weaknesses. In this approach, human experts are responsible for solving problems, whereas an inductive learning algorithm is responsible for reasoning and consistency checking.     

Expert knowledge acquisition and the unwilling expert: a knowledge engineering perspective

Expert systems are an evolving technology with the potential to make human expertise widely and cheaply available. The literature describing the development of expert systems generally assumes that experts willingly give up their knowledge. This is unrealistic and may be a reason why most expert system projects fail. This paper explores the problem of unwilling experts from the perspective of a knowledge engineer building an expert system. The link between knowledge and organizational power is established and human motivation theories are discussed. Finally, a new motivational approach is introduced to help the knowledge engineer deal with unwilling experts.     

纺织专家系统中知识与知识库的应用

专家系统是人工智能的一个分支，是一种模拟专家决策能力的计算机系统，知识库是系统的重要组成部分，是系统的核心。本文结合纺织工艺设计及管理专家系统介绍了基于知识的专家系统的概念和结构，对系统中知识的获取、存储方式予以说明．并对其知识的表示方法加以阐述。     

A knowledge sorting process for a product design expert system

Knowledge sorting is one way to organize the knowledge acquired from the domain expert(s) and various sources. Well-organized knowledge representation will make rule extraction much easier. This paper describes a knowledge sorting process that was developed to facilitate the rule extraction for a product design expert system. The process capitalizes on the relationships between design attributes and factors, dependent and independent variables, and consists of three stages: identification of knowledge sources, generation of taxonomic trees, and organization of acquired knowledge. An example applies the sorting process to the development of an expert system for the design of wood head golf clubs.     

Information retrieval and knowledge discovery utilizing a biomedical patent semantic Web

Before undertaking new biomedical research, identifying concepts that have already been patented is essential. A traditional keyword-based search on patent databases may not be sufficient to retrieve all the relevant information, especially for the biomedical domain. This paper presents BioPatentMiner, a system that facilitates information retrieval and knowledge discovery from biomedical patents. The system first identifies biological terms and relations from the patents and then integrates the information from the patents with knowledge from biomedical ontologies to create a semantic Web. Besides keyword search and queries linking the properties specified by one or more RDF triples, the system can discover semantic associations between the Web resources. The system also determines the importance of the resources to rank the results of a search and prevent information overload while determining the semantic associations.     

SABUMO: Towards a collaborative and semantic framework for knowledge sharing

Knowledge is one the most valuable assets in todays companies. Artificial Intelligence (AI) techniques aim to represent the knowledge in a way that can be applied to solving complex problems or supporting decision making processes. During the last years the semantic web techniques have supported the share of knowledge by means of ontologies. Ontologies have been used for both annotating resources and reasoning. Business Process Management is one of the specific fields in which the use of ontologies has been widely applied. This paper presents SABUMO, a framework based on ontologies that allows experts to represent and share their knowledge with other experts by means of shared and controlled vocabularies. The framework also allows the execution of business processes represented by experts. The execution of this knowledge does not require the installation of complex AI programs. Initial results of the evaluation setup show promising results both in usability and recommendation.     

Inferring robot goals from violations of semantic knowledge

A growing body of literature shows that endowing a mobile robot with semantic knowledge and with the ability to reason from this knowledge can greatly increase its capabilities. In this paper, we present a novel use of semantic knowledge, to encode information about how things should be, i.e. norms, and to enable the robot to infer deviations from these norms in order to generate goals to correct these deviations. For instance, if a robot has semantic knowledge that perishable items must be kept in a refrigerator, and it observes a bottle of milk on a table, this robot will generate the goal to bring that bottle into a refrigerator. The key move is to properly encode norms in an ontology so that each norm violation results in a detectable inconsistency. A goal is then generated to bring the world back in a consistent state, and a planner is used to transform this goal into actions. Our approach provides a mobile robot with a limited form of goal autonomy: the ability to derive its own goals to pursue generic aims. We illustrate our approach in a full mobile robot system that integrates a semantic map, a knowledge representation and reasoning system, a task planner, and standard perception and navigation routines.