In search of a theory of list memory: an inquiry into the efects of long-term information on short-term recall

Over recent years, evidence has been accumulating in favour of the importance of long-term information as a variable which can affect the success of short-term recall. Lexicality, word frequency, imagery and meaning have all been shown to augment short term recall performance. Two competing theories as to the causes of this long-term memory influence are outlined and tested in this thesis. The first approach is the order-encoding account, which ascribes the effect to the usage of resources at encoding, hypothesising that word lists which require less effort to process will benefit from increased levels of order encoding, in turn enhancing recall success. The alternative view, trace redintegration theory, suggests that order is automatically encoded phonologically, and that long-term information can only influence the interpretation of the resultant memory trace. The free recall experiments reported here attempted to determine the importance of order encoding as a facilitatory framework and to determine the locus of the effects of long-term information in free recall. Experiments 1 and 2 examined the effects of word frequency and semantic categorisation over a filled delay, and experiments 3 and 4 did the same for immediate recall. Free recall was improved by both long-term factors tested. Order information was not used over a short filled delay, but was evident in immediate recall. Furthermore, it was found that both long-term factors increased the amount of order information retained. Experiment 5 induced an order encoding effect over a filled delay, leaving a picture of short-term processes which are closely associated with long-term processes, and which fit conceptions of short-term memory being part of language processes rather better than either the encoding or the retrieval-based models. Experiments 6 and 7 aimed to determine to what extent phonological processes were responsible for the pattern of results observed. Articulatory suppression affected the encoding of order information where speech rate had no direct influence, suggesting that it is ease of lexical access which is the most important factor in the influence of long-term memory on immediate recall tasks. The evidence presented in this thesis does not offer complete support for either the retrieval-based account or the order encoding account of long-term influence. Instead, the evidence sits best with models that are based upon language-processing. The path urged for future research is to find ways in which this diffuse model can be better specified, and which can take account of the versatility of the human brain.

The functional organisation of the fronto-temporal language system:evidence from syntactic and semantic ambiguity

Spoken language comprehension is known to involve a large left-dominant network of fronto-temporal brain regions, but there is still little consensus about how the syntactic and semantic aspects of language are processed within this network. In an fMRI study, volunteers heard spoken sentences that contained either syntactic or semantic ambiguities as well as carefully matched low-ambiguity sentences. Results showed ambiguity-related responses in the posterior left inferior frontal gyrus (pLIFG) and posterior left middle temporal regions. The pLIFG activations were present for both syntactic and semantic ambiguities suggesting that this region is not specialised for processing either semantic or syntactic information, but instead performs cognitive operations that are required to resolve different types of ambiguity irrespective of their linguistic nature, for example by selecting between possible interpretations or reinterpreting misparsed sentences. Syntactic ambiguities also produced activation in the posterior middle temporal gyrus. These data confirm the functional relationship between these two brain regions and their importance in constructing grammatical representations of spoken language.

Discriminative training of the hidden vector state model for semantic parsing

In this paper, we discuss how discriminative training can be applied to the hidden vector state (HVS) model in different task domains. The HVS model is a discrete hidden Markov model (HMM) in which each HMM state represents the state of a push-down automaton with a finite stack size. In previous applications, maximum-likelihood estimation (MLE) is used to derive the parameters of the HVS model. However, MLE makes a number of assumptions and unfortunately some of these assumptions do not hold. Discriminative training, without making such assumptions, can improve the performance of the HVS model by discriminating the correct hypothesis from the competing hypotheses. Experiments have been conducted in two domains: the travel domain for the semantic parsing task using the DARPA Communicator data and the Air Travel Information Services (ATIS) data and the bioinformatics domain for the information extraction task using the GENIA corpus. The results demonstrate modest improvements of the performance of the HVS model using discriminative training. In the travel domain, discriminative training of the HVS model gives a relative error reduction rate of 31 percent in F-measure when compared with MLE on the DARPA Communicator data and 9 percent on the ATIS data. In the bioinformatics domain, a relative error reduction rate of 4 percent in F-measure is achieved on the GENIA corpus.

A formal model of the Semantic Web Service Ontology (WSMO)

Semantic Web Service, one of the most significant research areas within the Semantic Web vision, has attracted increasing attention from both the research community and industry. The Web Service Modelling Ontology (WSMO) has been proposed as an enabling framework for the total/partial automation of the tasks (e.g., discovery, selection, composition, mediation, execution, monitoring, etc.) involved in both intra- and inter-enterprise integration of Web services. To support the standardisation and tool support of WSMO, a formal model of the language is highly desirable. As several variants of WSMO have been proposed by the WSMO community, which are still under development, the syntax and semantics of WSMO should be formally defined to facilitate easy reuse and future development. In this paper, we present a formal Object-Z formal model of WSMO, where different aspects of the language have been precisely defined within one unified framework. This model not only provides a formal unambiguous model which can be used to develop tools and facilitate future development, but as demonstrated in this paper, can be used to identify and eliminate errors present in existing documentation.

Describing and communicating uncertainty within the semantic web

The Semantic Web relies on carefully structured, well defined, data to allow machines to communicate and understand one another. In many domains (e.g. geospatial) the data being described contains some uncertainty, often due to incomplete knowledge; meaningful processing of this data requires these uncertainties to be carefully analysed and integrated into the process chain. Currently, within the SemanticWeb there is no standard mechanism for interoperable description and exchange of uncertain information, which renders the automated processing of such information implausible, particularly where error must be considered and captured as it propagates through a processing sequence. In particular we adopt a Bayesian perspective and focus on the case where the inputs / outputs are naturally treated as random variables. This paper discusses a solution to the problem in the form of the Uncertainty Markup Language (UncertML). UncertML is a conceptual model, realised as an XML schema, that allows uncertainty to be quantified in a variety of ways i.e. realisations, statistics and probability distributions. UncertML is based upon a soft-typed XML schema design that provides a generic framework from which any statistic or distribution may be created. Making extensive use of Geography Markup Language (GML) dictionaries, UncertML provides a collection of definitions for common uncertainty types. Containing both written descriptions and mathematical functions, encoded as MathML, the definitions within these dictionaries provide a robust mechanism for defining any statistic or distribution and can be easily extended. Universal Resource Identifiers (URIs) are used to introduce semantics to the soft-typed elements by linking to these dictionary definitions. The INTAMAP (INTeroperability and Automated MAPping) project provides a use case for UncertML. This paper demonstrates how observation errors can be quantified using UncertML and wrapped within an Observations & Measurements (O&M) Observation. The interpolation service uses the information within these observations to influence the prediction outcome. The output uncertainties may be encoded in a variety of UncertML types, e.g. a series of marginal Gaussian distributions, a set of statistics, such as the first three marginal moments, or a set of realisations from a Monte Carlo treatment. Quantifying and propagating uncertainty in this way allows such interpolation results to be consumed by other services. This could form part of a risk management chain or a decision support system, and ultimately paves the way for complex data processing chains in the Semantic Web.

Sensing presence (PreSense) ontology : user modelling in the semantic sensor web

Increasingly, people's digital identities are attached to, and expressed through, their mobile devices. At the same time digital sensors pervade smart environments in which people are immersed. This paper explores different perspectives in which users' modelling features can be expressed through the information obtained by their attached personal sensors. We introduce the PreSense Ontology, which is designed to assign meaning to sensors' observations in terms of user modelling features. We believe that the Sensing Presence ( PreSense ) Ontology is a first step toward the integration of user modelling and "smart environments". In order to motivate our work we present a scenario and demonstrate how the ontology could be applied in order to enable context-sensitive services. © 2012 Springer-Verlag.

An integrated environment for semantic knowledge work

In this demonstration, we will present a semantic environment called the K-Box. The K-Box supports the lightweight integration of knowledge tools, with a focus on semantic tools, but with the flexibility to integrate natural language and conventional tools. We discuss the implementation of the framework, and two existing applications, including details of a new application for developers of semantic workflows. The demonstration will be of interest to developers and researchers of ontology-based knowledge management systems, and semantic desktops, and to analysts working with cross-media information. © 2011 ACM.

Ontology augmentation:combining semantic web and text resources

This work investigates the process of selecting, extracting and reorganizing content from Semantic Web information sources, to produce an ontology meeting the specifications of a particular domain and/or task. The process is combined with traditional text-based ontology learning methods to achieve tolerance to knowledge incompleteness. The paper describes the approach and presents experiments in which an ontology was built for a diet evaluation task. Although the example presented concerns the specific case of building a nutritional ontology, the methods employed are domain independent and transferrable to other use cases. © 2011 ACM.

Semantic search meets the Web

While semantic search technologies have been proven to work well in specific domains, they still have to confront two main challenges to scale up to the Web in its entirety. In this work we address this issue with a novel semantic search system that a) provides the user with the capability to query Semantic Web information using natural language, by means of an ontology-based Question Answering (QA) system [14] and b) complements the specific answers retrieved during the QA process with a ranked list of documents from the Web [3]. Our results show that ontology-based semantic search capabilities can be used to complement and enhance keyword search technologies.

An infrastructure for semantic web portals

This paper presents our Semantic Web portal infrastructure, which focuses on how to enhance knowledge access in traditional Web portals by gathering and exploiting semantic metadata. Special attention is paid to three important issues that affect the performance of knowledge access: i) high quality metadata acquisition, which concerns how to ensure high quality while gathering semantic metadata from heterogeneous data sources; ii) semantic search, which addresses how to meet the information querying needs of ordinary end users who are not necessarily familiar with the problem domain or the supported query language; and iii) semantic browsing, which concerns how to help users understand and explore the problem domain.

Browsing for information by highlighting automatically generated annotations:a user study and evaluation

The realization of the Semantic Web is constrained by a knowledge acquisition bottleneck, i.e. the problem of how to add RDF mark-up to the millions of ordinary web pages that already exist. Information Extraction (IE) has been proposed as a solution to the annotation bottleneck. In the task based evaluation reported here, we compared the performance of users without access to annotation, users working with annotations which had been produced from manually constructed knowledge bases, and users working with annotations augmented using IE. We looked at retrieval performance, overlap between retrieved items and the two sets of annotations, and usage of annotation options. Automatically generated annotations were found to add value to the browsing experience in the scenario investigated. Copyright 2005 ACM.

From syntatic standards to semantic standards in the agri-food logistics domain

This paper identifies gaps in standardization of agri-food logistics. Out of the European FP7 SmartAgriFood project a framework for classifying existing standards within the agri-food supply chain is introduced. Furthermore the characteristics to which a semantic standard should adhere are investigated. The standards classified as semantic out of the framework are assessed along these properties. The resulting conclusion is that the standards that are already present in the chain are more focused on syntax and lack semantic properties.

Sierra : cooperative request-response for resource management in disasters using semantic web principles

Disasters cause widespread harm and disrupt the normal functioning of society, and effective management requires the participation and cooperation of many actors. While advances in information and networking technology have made transmission of data easier than it ever has been before, communication and coordination of activities between actors remain exceptionally difficult. This paper employs semantic web technology and Linked Data principles to create a network of intercommunicating and inter-dependent on-line sites for managing resources. Each site publishes available resources openly and a lightweight opendata protocol is used to request and respond to requests for resources between sites in the network.

Visual hallucinations in the psychosis spectrum and comparative information from neurodegenerative disorders and eye disease

Much of the research on visual hallucinations (VHs) has been conducted in the context of eye disease and neurodegenerative conditions, but little is known about these phenomena in psychiatric and nonclinical populations. The purpose of this article is to bring together current knowledge regarding VHs in the psychosis phenotype and contrast this data with the literature drawn from neurodegenerative disorders and eye disease. The evidence challenges the traditional views that VHs are atypical or uncommon in psychosis. The weighted mean for VHs is 27% in schizophrenia, 15% in affective psychosis, and 7.3% in the general community. VHs are linked to a more severe psychopathological profile and less favorable outcome in psychosis and neurodegenerative conditions. VHs typically co-occur with auditory hallucinations, suggesting a common etiological cause. VHs in psychosis are also remarkably complex, negative in content, and are interpreted to have personal relevance. The cognitive mechanisms of VHs in psychosis have rarely been investigated, but existing studies point to source-monitoring deficits and distortions in top-down mechanisms, although evidence for visual processing deficits, which feature strongly in the organic literature, is lacking. Brain imaging studies point to the activation of visual cortex during hallucinations on a background of structural and connectivity changes within wider brain networks. The relationship between VHs in psychosis, eye disease, and neurodegeneration remains unclear, although the pattern of similarities and differences described in this review suggests that comparative studies may have potentially important clinical and theoretical implications. © 2014 The Author.

Internet search:subdivision-based interactive query expansion and the soft semantic web

The expansion of the Internet has made the task of searching a crucial one. Internet users, however, have to make a great effort in order to formulate a search query that returns the required results. Many methods have been devised to assist in this task by helping the users modify their query to give better results. In this paper we propose an interactive method for query expansion. It is based on the observation that documents are often found to contain terms with high information content, which can summarise their subject matter. We present experimental results, which demonstrate that our approach significantly shortens the time required in order to accomplish a certain task by performing web searches.