Knowledge Sources (knowledge + source)

Distribution by Scientific Domains

Selected Abstracts

Users want more sophisticated search assistants: Results of a task-based evaluation

Udo Kruschwitz
The Web provides a massive knowledge source, as do intranets and other electronic document collections. However, much of that knowledge is encoded implicitly and cannot be applied directly without processing into some more appropriate structures. Searching, browsing, question answering, for example, could all benefit from domain-specific knowledge contained in the documents, and in applications such as simple search we do not actually need very "deep" knowledge structures such as ontologies, but we can get a long way with a model of the domain that consists of term hierarchies. We combine domain knowledge automatically acquired by exploiting the documents' markup structure with knowledge extracted on the fly to assist a user with ad hoc search requests. Such a search system can suggest query modification options derived from the actual data and thus guide a user through the space of documents. This article gives a detailed account of a task-based evaluation that compares a search system that uses the outlined domain knowledge with a standard search system. We found that users do use the query modification suggestions proposed by the system. The main conclusion we can draw from this evaluation, however, is that users prefer a system that can suggest query modifications over a standard search engine, which simply presents a ranked list of documents. Most interestingly, we observe this user preference despite the fact that the baseline system even performs slightly better under certain criteria. [source]

Children's Suggestibility in Relation to their Understanding about Sources of Knowledge

E. J. Robinson
In the experiments reported here, children chose either to maintain their initial belief about an object's identity or to accept the experimenter's contradicting suggestion. Both 3, to 4,year,olds and 4, to 5,year,olds were good at accepting the suggestion only when the experimenter was better informed than they were (implicit source monitoring). They were less accurate at recalling both their own and the experimenter's information access (explicit recall of experience), though they performed well above chance. Children were least accurate at reporting whether their final belief was based on what they were told or on what they experienced directly (explicit source monitoring). Contrasting results emerged when children decided between contradictory suggestions from two differentially informed adults: Three, to 4,year,olds were more accurate at reporting the knowledge source of the adult they believed than at deciding which suggestion was reliable. Decision making in this observation task may require reflective understanding akin to that required for explicit source judgments when the child participates in the task. [source]

Competence Models and the Maintenance Problem

Barry Smyth
Case-based reasoning (CBR) systems solve problems by retrieving and adapting the solutions to similar problems that have been stored previously as a case base of individual problem solving episodes or cases. The maintenance problem refers to the problem of how to optimize the performance of a CBR system during its operational lifetime. It can have a significant impact on all the knowledge sources associated with a system (the case base, the similarity knowledge, the adaptation knowledge, etc.), and over time, any one, or more, of these knowledge sources may need to be adapted to better fit the current problem-solving environment. For example, many maintenance solutions focus on the maintenance of case knowledge by adding, deleting, or editing cases. This has lead to a renewed interest in the issue of case competence, since many maintenance solutions must ensure that system competence is not adversely affected by the maintenance process. In fact, we argue that ultimately any generic maintenance solution must explicitly incorporate competence factors into its maintenance policies. For this reason, in our work we have focused on developing explanatory and predictive models of case competence that can provide a sound foundation for future maintenance solutions. In this article we provide a comprehensive survey of this research, and we show how these models have been used to develop a number of innovative and successful maintenance solutions to a variety of different maintenance problems. [source]

Sharing in teams of heterogeneous, collaborative learning agents

Christopher M. Gifford
This paper is focused on the effects of sharing knowledge and collaboration of multiple heterogeneous, intelligent agents (hardware or software) which work together to learn a task. As each agent employs a different machine learning technique, the system consists of multiple knowledge sources and their respective heterogeneous knowledge representations. Collaboration between agents involves sharing knowledge to both speed up team learning, as well as refine the team's overall performance and group behavior. Experiments have been performed that vary the team composition in terms of machine learning algorithms, learning strategies employed by the agents, and sharing frequency for a predator-prey cooperative pursuit task. For lifelong learning, heterogeneous learning teams were more successful than homogeneous learning counterparts. Interestingly, sharing increased the learning rate, but sharing with higher frequency showed diminishing results. Lastly, knowledge conflicts are reduced over time the more sharing takes place. These results support further investigation of the merits of heterogeneous learning. 2008 Wiley Periodicals, Inc. [source]

Sources of knowledge in clinical practice in postgraduate medical students and faculty members: a conceptual map

Reza Yousefi-Nooraie MD
Abstract Objectives, To determine the most important knowledge sources that can influence clinical practice and to cluster them in conceptual groups based on their relative importance. Methods, Faculty members, fellows and residents of a large teaching tertiary care hospital were asked to rate the importance of different resources in their daily clinical practice and their understanding of some common terms from evidence-based medicine. The knowledge sources were distributed in a two-dimensional map using multidimensional scaling and hierarchical cluster analysis. Results, A total of 250 of 320 recruited hospital staff returned the questionnaires. The most important resources in daily practice were English journals, text books and literature searching for faculty members, experience, text books and English journals for fellows and text books, experience and peers for residents. Regional journals were the least important resources for all study groups. About 62.7% of residents did not know the meaning of ,number needed to treat', 36.8%,confidence interval', 54.9%,confounding factor' and 44.6%,meta-analysis'. The percentages for faculty members were 41.3%, 37%, 42.2% and 39.1%. The knowledge sources were placed in four clusters in a point map derived from the multidimensional scaling process. Conclusion, The dominance of the traditional information resources and experience-based medicine debate which is the consequence of traditional approaches to medical education may be one of the considerable barriers to the dissemination of evidence-based medicine in developing countries. The evidence-based clinical practice guidelines could be used as a useful passive-predigested source for busy clinicians to make informed decisions. A considerable Western bias may undermine the local research in developing world. [source]

Locating knowledge sources through keyphrase extraction

Sara Tedmori
There are a large number of tasks for which keyphrases can be useful. Manually identifying keyphrases can be a tedious and time consuming process that requires expertise, but if automated could save time and aid in creating metadata that could be used to locate knowledge sources. In this paper, the authors present an automated process for keyphrase extraction from e-mail messages. The process enables users to find other people who might hold the knowledge they require from information communicated via the e-mail system. The effectiveness of the extraction system is tested and compared against other extraction systems and the overall value of extracting information from e-mail explored. Copyright 2006 John Wiley & Sons, Ltd. [source]

Relationship-based practice and reflective practice: holistic approaches to contemporary child care social work

Gillian Ruch
ABSTRACT The renewed interest in relationship-based practice can be understood in the child care social work context as a response to the call to re-focus practice in this field. Relationship-based practice challenges the prevailing trends which emphasize reductionist understandings of human behaviour and narrowly conceived bureaucratic responses to complex problems. In so doing practitioners engaged in relationship-based practice need to be able to cope with the uniqueness of each individual's circumstances and the diverse knowledge sources required to make sense of complex, unpredictable problems. This paper argues that if relationship-based practice is to become an established and effective approach to practice, practitioners need to develop their reflective capabilities. An outline of contemporary understandings of relationship-based and reflective practice is offered and findings from doctoral research drawn on to identify how reflective practice complements relationship-based practice. The product of this complementary relationship is enhanced understandings across four aspects of practice: the client, the professional self, the organizational context and the knowledges informing practice. The paper concludes by acknowledging the inextricably interconnected nature of relationship-based and reflective practice and emphasizes the importance of practitioners being afforded opportunities to practise in relational and reflective ways. [source]