Experiencing information across the phenomenon of health information literacy

Interest in the concept of information literacy in different contexts is a topic that has steadily gained increased attention in information literacy discourse and research efforts over recent years. In particular the emergence of the term ‘health information literacy’ attests to this interest and has elevated awareness about the importance and relevance of information literacy in a health context. This paper reports on research that has taken a relational perspective to explore how people experience health information literacy. Initially established by Bruce (1997) the relational perspective draws from an experiential framework that emphasizes the relationship between users and information when learning in different contexts. This approach seeks outcomes that are deeply embedded in users’ informational life worlds and complements experiential phenomenological perspectives that have been used in health research. In keeping with the relational approach this research interprets health information literacy as being the different ways in which people experience using information to learn about health. Using interpretive phenomenography, this research explored variation in the lived experience of how people use information to learn about their health, and variation in what is constituted as information when learning about their health. Participants included 23 males and females aged between 45 and 64 years. All participants were residents from the Greater Brisbane area of Queensland, Australia. The research used semi-structured interviews for data collection. The types of questions posed during interviews included ‘Can you describe a time when you used information to learn about your health?’ and ‘What kinds of information have you used to learn about your health?’. This paper will focus on presenting one element of research findings that concerns the differences in ‘what’ participants experienced as information. Analysis of interview data identified significant variation in the experienced nature of information, specifically the different qualities or elements that comprised the ‘object’ of information, or in other words, what was perceived as ‘informing’. Illustrations of this variation include information experienced as traditional information sources, facts and experiences, something exhibiting particular qualities, physical or psychological changes, other people and role models. These findings provide new insights into what people may experience as information, and build upon existing literature regarding information as a theoretical construct. In addition the potential implications of these findings with respect to the design and delivery of health information literacy education will also be discussed. These research findings contribute to the emergence of information literacy investigations in everyday life and community. Although such settings have long been identified as a significant gap for exploration, research to date in this field has predominantly focused on educational and workplace environments. In this way the knowledge gained from this research has further revealed the contextual nature of information literacy, as well as its complexity as a phenomenon and focus of study.

Informed for health : exploring variation in ways of experiencing health information literacy

This research was a qualitative study that explored the experience of health information literacy. It used a research approach that emphasised identifying and describing variation in experience to investigate people's experience of using information to learn about health, and what they experienced as information for learning about health. The study's findings identified seven categories that represented qualitatively different ways in which people experienced health information literacy, and provide new knowledge about people's engagement with health information for learning in everyday life. The study contributes to consumer health information research and is significant to the disciplines of health and information science.

A formalization of logical imaging for information retrieval using quantum theory

In this paper we introduce a formalization of Logical Imaging applied to IR in terms of Quantum Theory through the use of an analogy between states of a quantum system and terms in text documents. Our formalization relies upon the Schrodinger Picture, creating an analogy between the dynamics of a physical system and the kinematics of probabilities generated by Logical Imaging. By using Quantum Theory, it is possible to model more precisely contextual information in a seamless and principled fashion within the Logical Imaging process. While further work is needed to empirically validate this, the foundations for doing so are provided.

Revisiting logical imaging for information retrieval

Retrieval with Logical Imaging is derived from belief revision and provides a novel mechanism for estimating the relevance of a document through logical implication (i.e. P(q -> d)). In this poster, we perform the first comprehensive evaluation of Logical Imaging (LI) in Information Retrieval (IR) across several TREC test Collections. When compared against standard baseline models, we show that LI fails to improve performance. This failure can be attributed to a nuance within the model that means non-relevant documents are promoted in the ranking, while relevant documents are demoted. This is an important contribution because it not only contextualizes the effectiveness of LI, but crucially ex- plains why it fails. By addressing this nuance, future LI models could be significantly improved.

On the use of complex numbers in quantum models for information retrieval

Quantum-inspired models have recently attracted increasing attention in Information Retrieval. An intriguing characteristic of the mathematical framework of quantum theory is the presence of complex numbers. However, it is unclear what such numbers could or would actually represent or mean in Information Retrieval. The goal of this paper is to discuss the role of complex numbers within the context of Information Retrieval. First, we introduce how complex numbers are used in quantum probability theory. Then, we examine van Rijsbergen’s proposal of evoking complex valued representations of informations objects. We empirically show that such a representation is unlikely to be effective in practice (confuting its usefulness in Information Retrieval). We then explore alternative proposals which may be more successful at realising the power of complex numbers.

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.

Secure coprocessor-based private information retrieval without periodical preprocessing

Early works on Private Information Retrieval (PIR) focused on minimizing the necessary communication overhead. They seemed to achieve this goal but at the expense of query response time. To mitigate this weakness, protocols with secure coprocessors were introduced. They achieve optimal communication complexity and better online processing complexity. Unfortunately, all secure coprocessor-based PIR protocols require heavy periodical preprocessing. In this paper, we propose a new protocol, which is free from the periodical preprocessing while offering the optimal communication complexity and almost optimal online processing complexity. The proposed protocol is proven to be secure.

Crowdsourcing interactions : using crowdsourcing for evaluating interactive information retrieval systems

In the field of information retrieval (IR), researchers and practitioners are often faced with a demand for valid approaches to evaluate the performance of retrieval systems. The Cranfield experiment paradigm has been dominant for the in-vitro evaluation of IR systems. Alternative to this paradigm, laboratory-based user studies have been widely used to evaluate interactive information retrieval (IIR) systems, and at the same time investigate users’ information searching behaviours. Major drawbacks of laboratory-based user studies for evaluating IIR systems include the high monetary and temporal costs involved in setting up and running those experiments, the lack of heterogeneity amongst the user population and the limited scale of the experiments, which usually involve a relatively restricted set of users. In this paper, we propose an alternative experimental methodology to laboratory-based user studies. Our novel experimental methodology uses a crowdsourcing platform as a means of engaging study participants. Through crowdsourcing, our experimental methodology can capture user interactions and searching behaviours at a lower cost, with more data, and within a shorter period than traditional laboratory-based user studies, and therefore can be used to assess the performances of IIR systems. In this article, we show the characteristic differences of our approach with respect to traditional IIR experimental and evaluation procedures. We also perform a use case study comparing crowdsourcing-based evaluation with laboratory-based evaluation of IIR systems, which can serve as a tutorial for setting up crowdsourcing-based IIR evaluations.

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.

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.

Integrating understandability in the evaluation of consumer health search engines

In this paper we propose a method that integrates the no- tion of understandability, as a factor of document relevance, into the evaluation of information retrieval systems for con- sumer health search. We consider the gain-discount evaluation framework (RBP, nDCG, ERR) and propose two understandability-based variants (uRBP) of rank biased precision, characterised by an estimation of understandability based on document readability and by different models of how readability influences user understanding of document content. The proposed uRBP measures are empirically contrasted to RBP by comparing system rankings obtained with each measure. The findings suggest that considering understandability along with topicality in the evaluation of in- formation retrieval systems lead to different claims about systems effectiveness than considering topicality alone.

Document clustering algorithms, representations and evaluation for information retrieval

This thesis presents new methods for classification and thematic grouping of billions of web pages, at scales previously not achievable. This process is also known as document clustering, where similar documents are automatically associated with clusters that represent various distinct topic. These automatically discovered topics are in turn used to improve search engine performance by only searching the topics that are deemed relevant to particular user queries.

Health information literacy and ageing Australians : applications for practice

This practice framework is designed for health practitioners and allied health care workers. The framework provides empirically-based descriptions of ageing Australians’ experiences of health information literacy and suggests how these may provide a foundation for helping ageing Australians enhance their health information literacy. Health information literacy is understood here to be people’s use of relevant information to learn about health.