Semantics, Modelling, and the Problem of Representation of Meaning -- a Brief Survey of Recent Literature

Over the past 50 years many have debated what representation should be used to capture the meaning of natural language utterances. Recently new needs of such representations have been raised in research. Here I survey some of the interesting representations suggested to answer for these new needs.Comment: 15 pages, no figure

Reverse production effect: Children recognize novel words better when they are heard rather than produced

This is the peer reviewed version of the following article: Tania S. Zamuner, Stephanie Strahm, Elizabeth Morin-Lessard, and Michael P. A. Page, 'Reverse production effect: children recognize novel words better when they are heard rather than produced', Developmental Science, which has been published in final form at DOI 10.1111/desc.12636. Under embargo until 15 November 2018. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.This research investigates the effect of production on 4.5- to 6-year-old children’s recognition of newly learned words. In Experiment 1, children were taught four novel words in a produced or heard training condition during a brief training phase. In Experiment 2, children were taught eight novel words, and this time training condition was in a blocked design. Immediately after training, children were tested on their recognition of the trained novel words using a preferential looking paradigm. In both experiments, children recognized novel words that were produced and heard during training, but demonstrated better recognition for items that were heard. These findings are opposite to previous results reported in the literature with adults and children. Our results show that benefits of speech production for word learning are dependent on factors such as task complexity and the developmental stage of the learner.Peer reviewedFinal Accepted Versio

Coping with Poorly Understood Domains: the Example of Internet Trust

The notion of trust, as required for secure operations over the Internet, is important for ascertaining the source of received messages. How can we measure the degree of trust in authenticating the source? Knowledge in the domain is not established, so knowledge engineering becomes knowledge generation rather than mere acquisition. Special techniques are required, and special features of KBS software become more important than in conventional domains. This paper generalizes from experience with Internet trust to discuss some techniques and software features that are important for poorly understood domains

Conceptual graph-based knowledge representation for supporting reasoning in African traditional medicine

Although African patients use both conventional or modern and traditional healthcare simultaneously, it has been proven that 80% of people rely on African traditional medicine (ATM). ATM includes medical activities stemming from practices, customs and traditions which were integral to the distinctive African cultures. It is based mainly on the oral transfer of knowledge, with the risk of losing critical knowledge. Moreover, practices differ according to the regions and the availability of medicinal plants. Therefore, it is necessary to compile tacit, disseminated and complex knowledge from various Tradi-Practitioners (TP) in order to determine interesting patterns for treating a given disease. Knowledge engineering methods for traditional medicine are useful to model suitably complex information needs, formalize knowledge of domain experts and highlight the effective practices for their integration to conventional medicine. The work described in this paper presents an approach which addresses two issues. First it aims at proposing a formal representation model of ATM knowledge and practices to facilitate their sharing and reusing. Then, it aims at providing a visual reasoning mechanism for selecting best available procedures and medicinal plants to treat diseases. The approach is based on the use of the Delphi method for capturing knowledge from various experts which necessitate reaching a consensus. Conceptual graph formalism is used to model ATM knowledge with visual reasoning capabilities and processes. The nested conceptual graphs are used to visually express the semantic meaning of Computational Tree Logic (CTL) constructs that are useful for formal specification of temporal properties of ATM domain knowledge. Our approach presents the advantage of mitigating knowledge loss with conceptual development assistance to improve the quality of ATM care (medical diagnosis and therapeutics), but also patient safety (drug monitoring)