Query expansion using term relationships in language models for information retrieval

Language Modeling (LM) has been successfully applied to Information Retrieval (IR). However, most of the existing LM approaches only rely on term occurrences in documents, queries and document collections. In traditional unigram based models, terms (or words) are usually considered to be independent. In some recent studies, dependence models have been proposed to incorporate term relationships into LM, so that links can be created between words in the same sentence, and term relationships (e.g. synonymy) can be used to expand the document model. In this study, we further extend this family of dependence models in the following two ways: (1) Term relationships are used to expand query model instead of document model, so that query expansion process can be naturally implemented; (2) We exploit more sophisticated inferential relationships extracted with Information Flow (IF). Information flow relationships are not simply pairwise term relationships as those used in previous studies, but are between a set of terms and another term. They allow for context-dependent query expansion. Our experiments conducted on TREC collections show that we can obtain large and significant improvements with our approach. This study shows that LM is an appropriate framework to implement effective query expansion.

Improving patient privacy and confidentiality in one regional Emergency Department – a quality project

Background: Patient privacy and confidentiality (PPaC) is an important consideration for nurses and other members of the health care team. Can a patient expect to have confidentiality and in particular privacy in the current climate of emergency health care? Do staff who work in the Emergency Department (ED) see confidentiality as an important factor when providing emergency care? These questions are important to consider. Methods: This is a two phased quality improvement project, developed and implemented over a six month period in a busy regional, tertiary referral ED. Results: Issues identified for this department included department design and layout, overcrowding due to patient flow and access block, staff practices and department policies which were also impacted upon by culture of the team, and use of space. Conclusions: Changes successful in improving this issue include increased staff awareness about PPaC, intercom paging prior to nursing handover to remove visitors during handover, one visitor per patient policy, designated places for handover, allocated bed space for patient reviews/assessment and a strategy to temporarily move the patient if procedures would have been undertaken in shared bed space. These are important issues when considering policy, practice and department design in the ED.

Fast and effective focused retrieval

Building an efficient and an effective search engine is a very challenging task. In this paper, we present the efficiency and effectiveness of our search engine at the INEX 2009 Efficiency and Ad Hoc Tracks. We have developed a simple and effective pruning method for fast query evaluation, and used a two-step process for Ad Hoc retrieval. The overall results from both tracks show that our search engine performs very competitively in terms of both efficiency and effectiveness.

The subjective experience of negative symptoms : characteristics of emotional withdrawal

According to the diagnosis of schizophrenia in the DSM-IV-TR (American Psychiatric Association, 2000), negative symptoms are those personal characteristics that are thought to be reduced from normal functioning, while positive symptoms are aspects of functioning that exist as an excess or distortion of normal functioning. Negative symptoms are generally considered to be a core feature of people diagnosed with schizophrenia. However, negative symptoms are not always present in those diagnosed, and a diagnosis can be made with only negative or only positive symptoms, or with a combination of both. Negative symptoms include an observed loss of emotional expression (affective flattening), loss of motivation or self directedness (avolition), loss of speech (alogia), and also a loss of interests and pleasures (anhedonia). Positive symptoms include the perception of things that others do not perceive (hallucinations), and extraordinary explanations for ordinary events (delusions) (American Psychiatric Association, 2000). Both negative and positive symptoms are derived from watching the patient and thus do not consider the patient’s subjective experience. However, aspects of negative symptoms, such as observed affective flattening are highly contended. Within conventional psychiatry, the absence of emotional expression is assumed to coincide with an absence of emotional experience. Contrasting research findings suggests that patients who were observed to score low on displayed emotional expression, scored high on self ratings of emotional experience. Patients were also observed to be significantly lower on emotional expression when compared with others (Aghevli, Blanchard, & Horan, 2003; Selton, van der Bosch, & Sijben, 1998). It appears that there is little correlation between emotional experience and emotional expression in patients, and that observer ratings cannot help us to understand the subjective experience of the negative symptoms. This chapter will focus on research into the subjective experiences of negative symptoms. A framework for these experiences will be used from the qualitative research findings of the primary author (Le Lievre, 2010). In this study, the primary author found that subjective experiences of the negative symptoms belonged to one of the two phases of the illness experience; “transitioning into emotional shutdown” or “recovering from emotional shutdown”. This chapter will use the six themes from the phase of “transitioning into emotional shutdown”. This phase described the experience of turning the focus of attention away from the world and onto the self and the past, thus losing contact with the world and others (emotional shutdown). Transitioning into emotional shutdown involved; “not being acknowledged”, “relational confusion”, “not being expressive”, “reliving the past”, “detachment”, and “no sense of direction” (Le Lievre, 2010). Detail will be added to this framework of experience from other qualitative research in this area. We will now review the six themes that constitute a “transition into emotional shutdown” and corresponding previous research findings.

Cognitive shifts related to interactive information retrieval

Purpose – Interactive information retrieval (IR) involves many human cognitive shifts at different information behaviour levels. Cognitive science defines a cognitive shift or shift in cognitive focus as triggered by the brain's response and change due to some external force. This paper aims to provide an explication of the concept of “cognitive shift” and then report results from a study replicating Spink's study of cognitive shifts during interactive IR. This work aims to generate promising insights into aspects of cognitive shifts during interactive IR and a new IR evaluation measure – information problem shift. Design/methodology/approach – The study participants (n=9) conducted an online search on an in-depth personal medical information problem. Data analysed included the pre- and post-search questionnaires completed by each study participant. Implications for web services and further research are discussed. Findings – Key findings replicated the results in Spink's study, including: all study participants reported some level of cognitive shift in their information problem, information seeking and personal knowledge due to their search interaction; and different study participants reported different levels of cognitive shift. Some study participants reported major cognitive shifts in various user-based variables such as information problem or information-seeking stage. Unlike Spink's study, no participant experienced a negative shift in their information problem stage or level of information problem understanding. Originality/value – This study builds on the previous study by Spink using a different dataset. The paper provides valuable insights for further research into cognitive shifts during interactive IR.

Patient-Specific Modeling of Scoliosis

Current complication rates for adolescent spinal deformity surgery are unacceptably high and in order to improve patient outcomes, the development of a simulation tool which enables the surgical strategy for an individual patient to be optimized is necessary. In this chapter we will present our work to date in developing and validating patient-specific modeling techniques to simulate and predict patient outcomes for surgery to correct adolescent scoliosis deformity. While these simulation tools are currently being developed to simulate adolescent idiopathic scoliosis patients, they will have broader applications in simulating spinal disorders and optimizing surgical planning for other types of spine surgery. Our studies to date have highlighted the need for not only patient-specific anatomical data, but also patient-specific tissue parameters and biomechanical loading data, in order to accurately predict the physiological behaviour of the spine. Even so, patient-specific computational models are the state-of-the art in computational biomechanics and offer much potential as a pre-operative surgical planning tool.

How quantum theory is developing the field of information retrieval

This position paper provides an overview of work conducted and an outlook of future directions within the field of Information Retrieval (IR) that aims to develop novel models, methods and frameworks inspired by Quantum Theory (QT).

Personalised search – a hybrid approach for web information retrieval and its evaluation

Nowadays, everyone can effortlessly access a range of information on the World Wide Web (WWW). As information resources on the web continue to grow tremendously, it becomes progressively more difficult to meet high expectations of users and find relevant information. Although existing search engine technologies can find valuable information, however, they suffer from the problems of information overload and information mismatch. This paper presents a hybrid Web Information Retrieval approach allowing personalised search using ontology, user profile and collaborative filtering. This approach finds the context of user query with least user’s involvement, using ontology. Simultaneously, this approach uses time-based automatic user profile updating with user’s changing behaviour. Subsequently, this approach uses recommendations from similar users using collaborative filtering technique. The proposed method is evaluated with the FIRE 2010 dataset and manually generated dataset. Empirical analysis reveals that Precision, Recall and F-Score of most of the queries for many users are improved with proposed method.

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.

Semantics-based web service discovery using information retrieval techniques

This paper demonstrates an experimental study that examines the accuracy of various information retrieval techniques for Web service discovery. The main goal of this research is to evaluate algorithms for semantic web service discovery. The evaluation is comprehensively benchmarked using more than 1,700 real-world WSDL documents from INEX 2010 Web Service Discovery Track dataset. For automatic search, we successfully use Latent Semantic Analysis and BM25 to perform Web service discovery. Moreover, we provide linking analysis which automatically links possible atomic Web services to meet the complex requirements of users. Our fusion engine recommends a final result to users. Our experiments show that linking analysis can improve the overall performance of Web service discovery. We also find that keyword-based search can quickly return results but it has limitation of understanding users’ goals.

A quantum information retrieval approach to memory

As computers approach the physical limits of information storable in memory, new methods will be needed to further improve information storage and retrieval. We propose a quantum inspired vector based approach, which offers a contextually dependent mapping from the subsymbolic to the symbolic representations of information. If implemented computationally, this approach would provide exceptionally high density of information storage, without the traditionally required physical increase in storage capacity. The approach is inspired by the structure of human memory and incorporates elements of Gardenfors’ Conceptual Space approach and Humphreys et al.’s matrix model of memory.