Open source information retrieval : a report on the SIGIR 2012 workshop

On August 16, 2012 the SIGIR 2012 Workshop on Open Source Information Retrieval was held as part of the SIGIR 2012 conference in Portland, Oregon, USA. There were 2 invited talks, one from industry and one from academia. There were 6 full papers and 6 short papers presented as well as demonstrations of 4 open source tools. Finally there was a lively discussion on future directions for the open source Information Retrieval community. This contribution discusses the events of the workshop and outlines future directions for the community.

An evaluation of corpus-driven measures of medical concept similarity for information retrieval

Measures of semantic similarity between medical concepts are central to a number of techniques in medical informatics, including query expansion in medical information retrieval. Previous work has mainly considered thesaurus-based path measures of semantic similarity and has not compared different corpus-driven approaches in depth. We evaluate the effectiveness of eight common corpus-driven measures in capturing semantic relatedness and compare these against human judged concept pairs assessed by medical professionals. Our results show that certain corpus-driven measures correlate strongly (approx 0.8) with human judgements. An important finding is that performance was significantly affected by the choice of corpus used in priming the measure, i.e., used as evidence from which corpus-driven similarities are drawn. This paper provides guidelines for the implementation of semantic similarity measures for medical informatics and concludes with implications for medical information retrieval.

Performance configurations over time: implications for growth-and profit-oriented strategies

Entrepreneurship research and practice places emphasis on company growth as a measure of entrepreneurial success. In many cases, there has been a tendency to give growth a very central role, with some researchers even seeing growth as the very essence of entrepreneurship (Cole, 1949; Sexton, 1997; Stevenson & Gumpert, 1991). A large number of empirical studies of the performance of young and/or small firms use growth as the dependent variable (see reviews by Ardishvili, Cardozo, Harmon, & Vadakath, 1998; Delmar, 1997; Wiklund, 1998). By contrast, the two most prominent views of strategic management – strategic positioning (Porter, 1980) and the resource-based view (Barney, 1991; Wernerfelt, 1984) – are both concerned with achieving competitive advantage and regard achieving economic rents and profitability relative to other competitors as the central measures of firm performance. Strategic entrepreneurship integrates these two perspectives and is simultaneously concerned with opportunity seeking and advantage seeking (Hitt, Ireland, Camp, & Sexton, 2002; Ireland, Hitt, & Sirmon, 2003). Consequently, both company growth and relative profitability are together relevant measures of firm performance in the domain of strategic entrepreneurship.

Oriented graphitic carbon films for hydrogen gas sensors

An oriented graphitic nanostructured carbon film has been employed as a conductometric hydrogen gas sensor. The carbon film was energetically deposited using a filtered cathodic vacuum arc with a -75 V bias applied to a stainless steel grid placed 1cm from the surface of the Si substrate. The substrate was heated to 400°C prior to deposition. Electron microscopy showed evidence that the film consisted largely of vertically oriented graphitic sheets and had a density of 2.06 g/cm3. 76% of the atoms were bonded in sp2 or graphitic configurations. A change in the device resistance of >; 1.5% was exhibited upon exposure to 1 % hydrogen gas (in synthetic, zero humidity air) at 100°C. The time for the sensor resistance to increase by 1.5 % under these conditions was approximately 60 s and the baseline (zero hydrogen exposure) resistance remained constant to within 0.01% during and after the hydrogen exposures.

Using Wikipedia to improve web service discovery

Building and maintaining software are not easy tasks. However, thanks to advances in web technologies, a new paradigm is emerging in software development. The Service Oriented Architecture (SOA) is a relatively new approach that helps bridge the gap between business and IT and also helps systems remain exible. However, there are still several challenges with SOA. As the number of available services grows, developers are faced with the problem of discovering the services they need. Public service repositories such as Programmable Web provide only limited search capabilities. Several mechanisms have been proposed to improve web service discovery by using semantics. However, most of these require manually tagging the services with concepts in an ontology. Adding semantic annotations is a non-trivial process that requires a certain skill-set from the annotator and also the availability of domain ontologies that include the concepts related to the topics of the service. These issues have prevented these mechanisms becoming widespread. This thesis focuses on two main problems. First, to avoid the overhead of manually adding semantics to web services, several automatic methods to include semantics in the discovery process are explored. Although experimentation with some of these strategies has been conducted in the past, the results reported in the literature are mixed. Second, Wikipedia is explored as a general-purpose ontology. The benefit of using it as an ontology is assessed by comparing these semantics-based methods to classic term-based information retrieval approaches. The contribution of this research is significant because, to the best of our knowledge, a comprehensive analysis of the impact of using Wikipedia as a source of semantics in web service discovery does not exist. The main output of this research is a web service discovery engine that implements these methods and a comprehensive analysis of the benefits and trade-offs of these semantics-based discovery approaches.

Small business entity tax concessions : through the eyes of the practitioner

Australia’s small business sector has pursued often-competing imperatives of simplicity, equity and efficiency in the income tax regime (particularly focusing on the notion of simplicity) over the last decade. In 2001, there was an attempt to provide such simplification and reduce the compliance burden faced by Australian small businesses through the ‘simplified tax system’ (‘STS’). However, despite amendments over the years, the regime is much criticised. This article explores how the STS (now known as the ‘small business entity’ regime or ‘SBE’) is utilised from the perspective of tax practitioners, by analysing their recommendations to small business clients in respect of the regime. The results indicate that practitioners believe the regime did nothing to simplify the tax system for small businesses or reduce tax compliance costs. Indeed, the practitioners believed that the introduction of small business concessions had actually achieved the opposite result — it had increased tax compliance costs for their small business clients. However, tax practitioners still recommend the regime highly because it minimises their client’s tax liability.

A tensor encoding model of word meaning : theory and application to information retrieval

This project was a step forward in developing and evaluating a novel, mathematical model that can deduce the meaning of words based on their use in language. This model can be applied to a wide range of natural language applications, including the information seeking process most of us undertake on a daily basis.

The ability of YSR DSM-oriented depression scales to predict DSM-IV depression in young adults : a longitudinal study

Background The Achenbach child behaviour checklist (CBCL/YSR) is a widely used screening tool for affective problems. Several studies report good association between the checklists and psychiatric diagnoses; although with varying degrees of agreement. Most are cross-sectional studies involving adolescents referred to mental health services. This paper aims to evaluate the performance of the youth self report (YSR) empirical and DSM-oriented internalising scales in predicting later depressive disorders in young adults. Methods Sample was 2431 young adults from an Australian birth cohort study. The strength of association between the empirical and DSM-oriented scales assessed at 14 and 21 years and structured-interview derived depression in young adulthood (18 to 22 years) were tested using odds ratios, ROC analyses and related diagnostic efficiency tests (sensitivity, specificity, positive and negative predictive values). Results Adolescents with internalising symptoms were twice (OR 2.3, 95%CI 1.7 to 3.1) as likely to be diagnosed with DSM-IV depression by age 21. Use of DSM-oriented depressive scales did not improve the concordance between the internalising behaviour and DSM-IV diagnosed depression at age 14 (ORs ranged from 1.9 to 2.5). Limitations Some loss to follow-up over the 7-year gap between the two waves of follow-up. Conclusion DSM-oriented scales perform no better than the standard internalising or anxious/depressed scales in identifying young adults with later DSM-IV depressive disorder.

Predicting depressive and anxiety disorders with the YASR internalising scales (empirical and DSM-oriented)

Background The Achenbach problem behaviour scales (CBCL/YSR) are widely used. The DSM-oriented anxiety and depression scales have been created to improve concordance between Achenbach’s internalising scales and DSM-IV depression and anxiety. To date no study has examined the concurrent utility of the young adult (YASR) internalising scales, either the empirical or newly developed DSM-oriented depressive or anxiety scales. Methods A sample of 2,551 young adults, aged 18–23 years, from an Australian cohort study. The association between the empirical and DSM-oriented anxiety and depression scales were individually assessed against DSMIV depression and anxiety diagnoses derived from structured interview. Odds ratios, ROC analyses and diagnostic efficiency tests (sensitivity, specificity, positive and negative predictive values) were used to report findings. Results YASR empirical internalising scale predicted DSM-IV mood disorders (depression OR = 6.9, 95% CI 5.0–9.5; anxiety OR = 5.1, 95% CI 3.8–6.7) in the previous 12 months. DSM-oriented depressive or anxiety scales did not appear to improve the concordance with DSM-IV diagnosed depression or anxiety. The internalising scales were much more effective at identifying those with comorbid depression and anxiety, with Ors between 10.1 and 21.7 depending on the internalising scale used. Conclusion DSM-oriented scales perform no better than the standard internalising in identifying young adults with DSM-IV mood or anxiety disorder.

Postgraduate response to an information retrieval credit course

Information skills instruction for research candidates bas recently been formalised as coursework at the Queensland University of Technology. Feedback solicited from participants suggests that students benefit from such coursework in a number of ways. Their perception of the value of specific content areas to their literature review and thesis presentation is favourable. A small group of students who participated in Interviews identified five ways in which the coursework assisted the research process. As Instructors continue to work with the post·graduate community it would be useful to deepen our understanding of how such instruction is perceived and the benefits which can be derived from it.

Secured e-health data retrieval in DaaS and Big Data

Big Data is a rising IT trend similar to cloud computing, social networking or ubiquitous computing. Big Data can offer beneficial scenarios in the e-health arena. However, one of the scenarios can be that Big Data needs to be kept secured for a long period of time in order to gain its benefits such as finding cures for infectious diseases and protecting patient privacy. From this connection, it is beneficial to analyse Big Data to make meaningful information while the data is stored securely. Therefore, the analysis of various database encryption techniques is essential. In this study, we simulated 3 types of technical environments, namely, Plain-text, Microsoft Built-in Encryption, and custom Advanced Encryption Standard, using Bucket Index in Data-as-a-Service. The results showed that custom AES-DaaS has a faster range query response time than MS built-in encryption. Furthermore, while carrying out the scalability test, we acknowledged that there are performance thresholds depending on physical IT resources. Therefore, for the purpose of efficient Big Data management in eHealth it is noteworthy to examine their scalability limits as well even if it is under a cloud computing environment. In addition, when designing an e-health database, both patient privacy and system performance needs to be dealt as top priorities.

Towards the retrieval of accurate OD matrices from Bluetooth data : lessons learned from 2 years of data

The Bluetooth technology is being increasingly used to track vehicles throughout their trips, within urban networks and across freeway stretches. One important opportunity offered by this type of data is the measurement of Origin-Destination patterns, emerging from the aggregation and clustering of individual trips. In order to obtain accurate estimations, however, a number of issues need to be addressed, through data filtering and correction techniques. These issues mainly stem from the use of the Bluetooth technology amongst drivers, and the physical properties of the Bluetooth sensors themselves. First, not all cars are equipped with discoverable Bluetooth devices and the Bluetooth-enabled vehicles may belong to some small socio-economic groups of users. Second, the Bluetooth datasets include data from various transport modes; such as pedestrian, bicycles, cars, taxi driver, buses and trains. Third, the Bluetooth sensors may fail to detect all of the nearby Bluetooth-enabled vehicles. As a consequence, the exact journey for some vehicles may become a latent pattern that will need to be extracted from the data. Finally, sensors that are in close proximity to each other may have overlapping detection areas, thus making the task of retrieving the correct travelled path even more challenging. The aim of this paper is twofold. We first give a comprehensive overview of the aforementioned issues. Further, we propose a methodology that can be followed, in order to cleanse, correct and aggregate Bluetooth data. We postulate that the methods introduced by this paper are the first crucial steps that need to be followed in order to compute accurate Origin-Destination matrices in urban road networks.

Retrieval of health advice on the web: AEHRC at ShARe/CLEF eHealth Evaluation Lab Task 3

This paper details the participation of the Australian e- Health Research Centre (AEHRC) in the ShARe/CLEF 2013 eHealth Evaluation Lab { Task 3. This task aims to evaluate the use of information retrieval (IR) systems to aid consumers (e.g. patients and their relatives) in seeking health advice on the Web. Our submissions to the ShARe/CLEF challenge are based on language models generated from the web corpus provided by the organisers. Our baseline system is a standard Dirichlet smoothed language model. We enhance the baseline by identifying and correcting spelling mistakes in queries, as well as expanding acronyms using AEHRC's Medtex medical text analysis platform. We then consider the readability and the authoritativeness of web pages to further enhance the quality of the document ranking. Measures of readability are integrated in the language models used for retrieval via prior probabilities. Prior probabilities are also used to encode authoritativeness information derived from a list of top-100 consumer health websites. Empirical results show that correcting spelling mistakes and expanding acronyms found in queries signi cantly improves the e ectiveness of the language model baseline. Readability priors seem to increase retrieval e ectiveness for graded relevance at early ranks (nDCG@5, but not precision), but no improvements are found at later ranks and when considering binary relevance. The authoritativeness prior does not appear to provide retrieval gains over the baseline: this is likely to be because of the small overlap between websites in the corpus and those in the top-100 consumer-health websites we acquired.

Privacy oriented access control for electronic health records

Information privacy is a critical success/failure factor in information technology supported healthcare (eHealth). eHealth systems utilise electronic health records (EHR) as the main source of information, thus, implementing appropriate privacy preserving methods for EHRs is vital for the proliferation of eHealth. Whilst information privacy may be a fundamental requirement for eHealth consumers, healthcare professionals demand non-restricted access to patient information for improved healthcare delivery, thus, creating an environment where stakeholder requirements are contradictory. Therefore, there is a need to achieve an appropriate balance of requirements in order to build successful eHealth systems. Towards achieving this balance, a new genre of eHealth systems called Accountable-eHealth (AeH) systems has been proposed. In this paper, an access control model for EHRs is presented that can be utilised by AeH systems to create information usage policies that fulfil both stakeholders’ requirements. These policies are used to accomplish the aforementioned balance of requirements creating a satisfactory eHealth environment for all stakeholders. The access control model is validated using a Web based prototype as a proof of concept.

Modeling the viability of the free-ranging cheetah population in Namibia : an object-oriented Bayesian network approach

Conservation of free-ranging cheetah (Acinonyx jubatus) populations is multi faceted and needs to be addressed from an ecological, biological and management perspective. There is a wealth of published research, each focusing on a particular aspect of cheetah conservation. Identifying the most important factors, making sense of various (and sometimes contrasting) findings, and taking decisions when little or no empirical data is available, are everyday challenges facing conservationists. Bayesian networks (BN) provide a statistical modeling framework that enables analysis and integration of information addressing different aspects of conservation. There has been an increased interest in the use of BNs to model conservation issues, however the development of more sophisticated BNs, utilizing object-oriented (OO) features, is still at the frontier of ecological research. We describe an integrated, parallel modeling process followed during a BN modeling workshop held in Namibia to combine expert knowledge and data about free-ranging cheetahs. The aim of the workshop was to obtain a more comprehensive view of the current viability of the free-ranging cheetah population in Namibia, and to predict the effect different scenarios may have on the future viability of this free-ranging cheetah population. Furthermore, a complementary aim was to identify influential parameters of the model to more effectively target those parameters having the greatest impact on population viability. The BN was developed by aggregating diverse perspectives from local and independent scientists, agents from the national ministry, conservation agency members and local fieldworkers. This integrated BN approach facilitates OO modeling in a multi-expert context which lends itself to a series of integrated, yet independent, subnetworks describing different scientific and management components. We created three subnetworks in parallel: a biological, ecological and human factors network, which were then combined to create a complete representation of free-ranging cheetah population viability. Such OOBNs have widespread relevance to the effective and targeted conservation management of vulnerable and endangered species.