Semantic search and inferencing in health informatics

Consider a person searching electronic health records, a search for the term ‘cracked skull’ should return documents that contain the term ‘cranium fracture’. A information retrieval systems is required that matches concepts, not just keywords. Further more, determining relevance of a query to a document requires inference – its not simply matching concepts. For example a document containing ‘dialysis machine’ should align with a query for ‘kidney disease’. Collectively we describe this problem as the ‘semantic gap’ – the difference between the raw medical data and the way a human interprets it. This paper presents an approach to semantic search of health records by combining two previous approaches: an ontological approach using the SNOMED CT medical ontology; and a distributional approach using semantic space vector space models. Our approach will be applied to a specific problem in health informatics: the matching of electronic patient records to clinical trials.

Semantic oscillations : encoding context and structure in complex valued holographic vectors

In computational linguistics, information retrieval and applied cognition, words and concepts are often represented as vectors in high dimensional spaces computed from a corpus of text. These high dimensional spaces are often referred to as Semantic Spaces. We describe a novel and efficient approach to computing these semantic spaces via the use of complex valued vector representations. We report on the practical implementation of the proposed method and some associated experiments. We also briefly discuss how the proposed system relates to previous theoretical work in Information Retrieval and Quantum Mechanics and how the notions of probability, logic and geometry are integrated within a single Hilbert space representation. In this sense the proposed system has more general application and gives rise to a variety of opportunities for future research.

Towards defining semantic foundations for purpose-based privacy policies

We define a semantic model for purpose, based on which purpose-based privacy policies can be meaningfully expressed and enforced in a business system. The model is based on the intuition that the purpose of an action is determined by its situation among other inter-related actions. Actions and their relationships can be modeled in the form of an action graph which is based on the business processes in a system. Accordingly, a modal logic and the corresponding model checking algorithm are developed for formal expression of purpose-based policies and verifying whether a particular system complies with them. It is also shown through various examples, how various typical purpose-based policies as well as some new policy types can be expressed and checked using our model.

Utilising semantic tags in XML clustering

This paper presents an overview of the experiments conducted using Hybrid Clustering of XML documents using Constraints (HCXC) method for the clustering task in the INEX 2009 XML Mining track. This technique utilises frequent subtrees generated from the structure to extract the content for clustering the XML documents. It also presents the experimental study using several data representations such as the structure-only, content-only and using both the structure and the content of XML documents for the purpose of clustering them. Unlike previous years, this year the XML documents were marked up using the Wiki tags and contains categories derived by using the YAGO ontology. This paper also presents the results of studying the effect of these tags on XML clustering using the HCXC method.

Inclusive universal design practice and activism : a case study

This paper reports on a unique approach to inclusive practice that responds to several critical issues highlighted in the first Universal Design (UD) Conference in Yokohama as well as in more recent literature on universal design. The approach, as explained in the paper, involves a not-for-profit community organization, university researchers, and a design action group comprising practitioners from across the design disciplines, together with other specialist consultants, developing a voluntary capacity an independent housing model for people with disabilities and their families or caretakers. With a focus on relationships and "a system that places human beings at the centre in all respects", this paper presents the approach and the ermerging theoretical framework which addresses three issues that afacan and Erbug (2009) propose hinder the integration of universal design with design practice, namely: theory-practice inconsistency involving the lack of flow-on of universal design awareness into design practice; a way of thinking that exhibits very little empathy with and understanding of the requirements of diverse users; and poorly implemented and coordinated collaboration and communication involving designers and other professionals (pp. 731 - 732).

Semantic modeling method for configurable enterprise information systems

Business practices vary from one company to another and business practices often need to be changed due to changes of business environments. To satisfy different business practices, enterprise systems need to be customized. To keep up with ongoing business practice changes, enterprise systems need to be adapted. Because of rigidity and complexity, the customization and adaption of enterprise systems often takes excessive time with potential failures and budget shortfall. Moreover, enterprise systems often drag business behind because they cannot be rapidly adapted to support business practice changes. Extensive literature has addressed this issue by identifying success or failure factors, implementation approaches, and project management strategies. Those efforts were aimed at learning lessons from post implementation experiences to help future projects. This research looks into this issue from a different angle. It attempts to address this issue by delivering a systematic method for developing flexible enterprise systems which can be easily tailored for different business practices or rapidly adapted when business practices change. First, this research examines the role of system models in the context of enterprise system development; and the relationship of system models with software programs in the contexts of computer aided software engineering (CASE), model driven architecture (MDA) and workflow management system (WfMS). Then, by applying the analogical reasoning method, this research initiates a concept of model driven enterprise systems. The novelty of model driven enterprise systems is that it extracts system models from software programs and makes system models able to stay independent of software programs. In the paradigm of model driven enterprise systems, system models act as instructors to guide and control the behavior of software programs. Software programs function by interpreting instructions in system models. This mechanism exposes the opportunity to tailor such a system by changing system models. To make this true, system models should be represented in a language which can be easily understood by human beings and can also be effectively interpreted by computers. In this research, various semantic representations are investigated to support model driven enterprise systems. The significance of this research is 1) the transplantation of the successful structure for flexibility in modern machines and WfMS to enterprise systems; and 2) the advancement of MDA by extending the role of system models from guiding system development to controlling system behaviors. This research contributes to the area relevant to enterprise systems from three perspectives: 1) a new paradigm of enterprise systems, in which enterprise systems consist of two essential elements: system models and software programs. These two elements are loosely coupled and can exist independently; 2) semantic representations, which can effectively represent business entities, entity relationships, business logic and information processing logic in a semantic manner. Semantic representations are the key enabling techniques of model driven enterprise systems; and 3) a brand new role of system models; traditionally the role of system models is to guide developers to write system source code. This research promotes the role of system models to control the behaviors of enterprise.

The use of semantic priming as a paradigm for the detection of faking on self-report psychological tests

It is recognised that individuals do not always respond honestly when completing psychological tests. One of the foremost issues for research in this area is the inability to detect individuals attempting to fake. While a number of strategies have been identified in faking, a commonality of these strategies is the latent role of long term memory. Seven studies were conducted in order to examine whether it is possible to detect the activation of faking related cognitions using a lexical decision task. Study 1 found that engagement with experiential processing styles predicted the ability to fake successfully, confirming the role of associative processing styles in faking. After identifying appropriate stimuli for the lexical decision task (Studies 2A and 2B), Studies 3 to 5 examined whether a cognitive state of faking could be primed and subsequently identified, using a lexical decision task. Throughout the course of these studies, the experimental methodology was increasingly refined in an attempt to successfully identify the relevant priming mechanisms. The results were consistent and robust throughout the three priming studies: faking good on a personality test primed positive faking related words in the lexical decision tasks. Faking bad, however, did not result in reliable priming of negative faking related cognitions. To more completely address potential issues with the stimuli and the possible role of affective priming, two additional studies were conducted. Studies 6A and 6B revealed that negative faking related words were more arousing than positive faking related words, and that positive faking related words were more abstract than negative faking related words and neutral words. Study 7 examined whether the priming effects evident in the lexical decision tasks occurred as a result of an unintentional mood induction while faking the psychological tests. Results were equivocal in this regard. This program of research aligned the fields of psychological assessment and cognition to inform the preliminary development and validation of a new tool to detect faking. Consequently, an implicit technique to identify attempts to fake good on a psychological test has been identified, using long established and robust cognitive theories in a novel and innovative way. This approach represents a new paradigm for the detection of individuals responding strategically to psychological testing. With continuing development and validation, this technique may have immense utility in the field of psychological assessment.

The Tension between a constructed self and universal reason in considerations of elective death

Review of Coping with Choices to Die, by C. G. Prado. Cambridge: Cambridge University Press, 2011.

Trading spaces : on the lore and limitations of latent semantic analysis

Two decades after its inception, Latent Semantic Analysis(LSA) has become part and parcel of every modern introduction to Information Retrieval. For any tool that matures so quickly, it is important to check its lore and limitations, or else stagnation will set in. We focus here on the three main aspects of LSA that are well accepted, and the gist of which can be summarized as follows: (1) that LSA recovers latent semantic factors underlying the document space, (2) that such can be accomplished through lossy compression of the document space by eliminating lexical noise, and (3) that the latter can best be achieved by Singular Value Decomposition. For each aspect we performed experiments analogous to those reported in the LSA literature and compared the evidence brought to bear in each case. On the negative side, we show that the above claims about LSA are much more limited than commonly believed. Even a simple example may show that LSA does not recover the optimal semantic factors as intended in the pedagogical example used in many LSA publications. Additionally, and remarkably deviating from LSA lore, LSA does not scale up well: the larger the document space, the more unlikely that LSA recovers an optimal set of semantic factors. On the positive side, we describe new algorithms to replace LSA (and more recent alternatives as pLSA, LDA, and kernel methods) by trading its l2 space for an l1 space, thereby guaranteeing an optimal set of semantic factors. These algorithms seem to salvage the spirit of LSA as we think it was initially conceived.

Towards semantic search and inference in electronic medical records : an approach using concept-based information retrieval

For more than a decade research in the field of context aware computing has aimed to find ways to exploit situational information that can be detected by mobile computing and sensor technologies. The goal is to provide people with new and improved applications, enhanced functionality and better use experience (Dey, 2001). Early applications focused on representing or computing on physical parameters, such as showing your location and the location of people or things around you. Such applications might show where the next bus is, which of your friends is in the vicinity and so on. With the advent of social networking software and microblogging sites such as Facebook and Twitter, recommender systems and so on context-aware computing is moving towards mining the social web in order to provide better representations and understanding of context, including social context. In this paper we begin by recapping different theoretical framings of context. We then discuss the problem of context- aware computing from a design perspective.