Creation of a new evaluation benchmark for information retrieval targeting patient information needs

Searching for health advice on the web is becoming increasingly common. Because of the great importance of this activity for patients and clinicians and the effect that incorrect information may have on health outcomes, it is critical to present relevant and valuable information to a searcher. Previous evaluation campaigns on health information retrieval (IR) have provided benchmarks that have been widely used to improve health IR and record these improvements. However, in general these benchmarks have targeted the specialised information needs of physicians and other healthcare workers. In this paper, we describe the development of a new collection for evaluation of effectiveness in IR seeking to satisfy the health information needs of patients. Our methodology features a novel way to create statements of patients’ information needs using realistic short queries associated with patient discharge summaries, which provide details of patient disorders. We adopt a scenario where the patient then creates a query to seek information relating to these disorders. Thus, discharge summaries provide us with a means to create contextually driven search statements, since they may include details on the stage of the disease, family history etc. The collection will be used for the first time as part of the ShARe/-CLEF 2013 eHealth Evaluation Lab, which focuses on natural language processing and IR for clinical care.

Combining word semantics within complex Hilbert space for information retrieval

Complex numbers are a fundamental aspect of the mathematical formalism of quantum physics. Quantum-like models developed outside physics often overlooked the role of complex numbers. Specifically, previous models in Information Retrieval (IR) ignored complex numbers. We argue that to advance the use of quantum models of IR, one has to lift the constraint of real-valued representations of the information space, and package more information within the representation by means of complex numbers. As a first attempt, we propose a complex-valued representation for IR, which explicitly uses complex valued Hilbert spaces, and thus where terms, documents and queries are represented as complex-valued vectors. The proposal consists of integrating distributional semantics evidence within the real component of a term vector; whereas, ontological information is encoded in the imaginary component. Our proposal has the merit of lifting the role of complex numbers from a computational byproduct of the model to the very mathematical texture that unifies different levels of semantic information. An empirical instantiation of our proposal is tested in the TREC Medical Record task of retrieving cohorts for clinical studies.

ShARe/CLEF eHealth Evaluation Lab 2013, Task 3: Information retrieval to address patients' questions when reading clinical reports

This paper presents the results of task 3 of the ShARe/CLEF eHealth Evaluation Lab 2013. This evaluation lab focuses on improving access to medical information on the web. The task objective was to investigate the effect of using additional information such as the discharge summaries and external resources such as medical ontologies on the IR effectiveness. The participants were allowed to submit up to seven runs, one mandatory run using no additional information or external resources, and three each using or not using discharge summaries.

Quality Information System: Investigating the conception, role, models and suggesting conceptual and hierarchal models

In the current business world which companies’ competition is very compact in the business arena, quality in manufacturing and providing products and services can be considered as a means of seeking excellence and success of companies in this competition arena. Entering the era of e-commerce and emergence of new production systems and new organizational structures, traditional management and quality assurance systems have been challenged. Consequently, quality information system has been gained a special seat as one of the new tools of quality management. In this paper, quality information system has been studied with a review of the literature of the quality information system, and the role and position of quality Information System (QIS) among other information systems of a organization is investigated. The quality Information system models are analyzed and by analyzing and assessing presented models in quality information system a conceptual and hierarchical model of quality information system is suggested and studied. As a case study the hierarchical model of quality information system is developed by evaluating hierarchical models presented in the field of quality information system based on the Shetabkar Co.

Combining recommender and reputation systems to produce better online advice

Although recommender systems and reputation systems have quite different theoretical and technical bases, both types of systems have the purpose of providing advice for decision making in e-commerce and online service environments. The similarity in purpose makes it natural to integrate both types of systems in order to produce better online advice, but their difference in theory and implementation makes the integration challenging. In this paper, we propose to use mappings to subjective opinions from values produced by recommender systems as well as from scores produced by reputation systems, and to combine the resulting opinions within the framework of subjective logic.

Using a public key registry for improved trust and scalability in national E-health systems

An increasing number of countries are faced with an aging population increasingly needing healthcare services. For any e-health information system, the need for increased trust by such clients with potentially little knowledge of any security scheme involved is paramount. In addition notable scalability of any system has become a critical aspect of system design, development and ongoing management. Meanwhile cryptographic systems provide the security provisions needed for confidentiality, authentication, integrity and non-repudiation. Cryptographic key management, however, must be secure, yet efficient and effective in developing an attitude of trust in system users. Digital certificate-based Public Key Infrastructure has long been the technology of choice or availability for information security/assurance; however, there appears to be a notable lack of successful implementations and deployments globally. Moreover, recent issues with associated Certificate Authority security have damaged trust in these schemes. This paper proposes the adoption of a centralised public key registry structure, a non-certificate based scheme, for large scale e-health information systems. The proposed structure removes complex certificate management, revocation and a complex certificate validation structure while maintaining overall system security. Moreover, the registry concept may be easier for both healthcare professionals and patients to understand and trust.

On managing information technology capabilities

Information technology (IT) plays a critical role of enabler of activities that improve the performance of business processes. This enabling role of IT resources means continuous investment in IT is a strategic necessity. It is established that organizations’ IT-related capabilities leverage the enabling potential of IT resources. Today’s turbulent and challenging business environment requires organizations to do more from their existing and newly acquired IT resources. To achieve this, organizations need to discover ways or establish environments to nourish their existing IT-related capabilities, and develop new IT-related capabilities. We suggest one such environment, a dynamic IT-learning environment that could contribute to nourishing existing IT-related capabilities, and developing new IT-related capabilities. This environment is a product of coordination of four organizational factors that relate to the ways in which IT-related knowledge is applied to business processes, the accompanying reward structures, and ways in which the IT-related learning and knowledge is shared within the organization. Using 216 field survey responses, this paper shows that two IT-related capabilities of top management commitment to IT initiatives, and shared organizational knowledge between the IT and business unit managers has a stronger positive influence on business process performance in the presence of this dynamic IT-learning environment. The study also shows that a marginal IT-related capability, technical IT skills, has a positive and significant influence on business process performance in the presence of this environment. These outcomes imply that organizations’ internal environments could contribute to the management of their IT-related capabilities.

On the maturity of open source BPM systems

In this Article, Petia Wohed, Arthur H. M. ter Hofstede, Nick Russell, Birger Andersson, and Wil M. P. van der Aalst present the results of their examination of existing open source BPM systems. Their conclusions are illuminating for both Open Source developers as well as the user community. Read their Article for the details of their study.

Flexible service systems

Service science combines scientific, management, and engineering disciplines to improve the understanding of how service systems cooperate to create business value. Service systems are complex configurations of people, technologies, and resources that coexist in a common environment of service provisioning. While the general concepts of service science are understood and agreed upon, the representation of service systems using models is still in its infancy. In this chapter, we look at business processes and their role in properly representing service systems. We propose flexible process graphs, a high-level process modeling language, and extend it in order to specify service systems and their compositions within shared environments in a flexible way. The discussion in this chapter is the first step towards a formal description of service science environment, including service systems, networks, and whole ecology.

Understanding the information literacy experiences of EFL (English as a Foreign Language) students

This thesis investigated the information literacy experiences of EFL (English as a Foreign Language) students in a higher education institution in the United Arab Emirates (UAE). Phenomenography was used to investigate how EFL students' 'used information to learn' (ie. information literacy). The study revealed that EFL students' experienced information literacy across four categories and had varying experiences of information and learning. The research also showed that EFL students' faced a number of challenges and barriers due to language that impacted on their experiences of reading, understanding, accessing and translating information.

Knowledge ecosystems of early career academics : a grounded theory of experiencing information use for learning in developmental networks

This study explored early career academics' experiences in using information to learn while building their networks for professional development. A 'knowledge ecosystem' model was developed consisting of informal learning interactions such as relating to information to create knowledge and engaging in mutually supportive relationships. Findings from this study present an alternative interpretation of information use for learning that is focused on processes manifesting as human interactions with informing entities revolving around the contexts of reciprocal human relationships.

Understanding negation and family history to improve clinical information retrieval

We present a study to understand the effect that negated terms (e.g., "no fever") and family history (e.g., "family history of diabetes") have on searching clinical records. Our analysis is aimed at devising the most effective means of handling negation and family history. In doing so, we explicitly represent a clinical record according to its different content types: negated, family history and normal content; the retrieval model weights each of these separately. Empirical evaluation shows that overall the presence of negation harms retrieval effectiveness while family history has little effect. We show negation is best handled by weighting negated content (rather than the common practise of removing or replacing it). However, we also show that many queries benefit from the inclusion of negated content and that negation is optimally handled on a per-query basis. Additional evaluation shows that adaptive handing of negated and family history content can have significant benefits.

Relevation! : an open source system for information retrieval relevance assessment

Relevation! is a system for performing relevance judgements for information retrieval evaluation. Relevation! is web-based, fully configurable and expandable; it allows researchers to effectively collect assessments and additional qualitative data. The system is easily deployed allowing assessors to smoothly perform their relevance judging tasks, even remotely. Relevation! is available as an open source project at: http://ielab.github.io/relevation.

Informed systems approach : new directions for organizational learning

The Informed Systems Approach offers models for advancing workplace learning within collaboratively designed systems that promote using information to learn through collegial exchange and reflective dialogue. This systemic approach integrates theoretical antecedents and process models, including the learning theories of Peter Checkland (Soft Systems Methodology), which advance systems design and informed action, and Christine Bruce (informed learning), which generate information experiences and professional practices. Ikujiro Nonaka’s systems ideas (SECI model) and Mary Crossan’s learning framework (4i framework) further animate workplace knowledge creation through learning relationships engaging individuals with ideas.

The Quantum Probability Ranking Principle for Information Retrieval

While the Probability Ranking Principle for Information Retrieval provides the basis for formal models, it makes a very strong assumption regarding the dependence between documents. However, it has been observed that in real situations this assumption does not always hold. In this paper we propose a reformulation of the Probability Ranking Principle based on quantum theory. Quantum probability theory naturally includes interference effects between events. We posit that this interference captures the dependency between the judgement of document relevance. The outcome is a more sophisticated principle, the Quantum Probability Ranking Principle, that provides a more sensitive ranking which caters for interference/dependence between documents’ relevance.