866 resultados para twitter, conversation retrieval


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The Australian e-Health Research Centre and Queensland University of Technology recently participated in the TREC 2011 Medical Records Track. This paper reports on our methods, results and experience using a concept-based information retrieval approach. Our concept-based approach is intended to overcome specific challenges we identify in searching medical records. Queries and documents are transformed from their term-based originals into medical concepts as de ned by the SNOMED-CT ontology. Results show our concept-based approach performed above the median in all three performance metrics: bref (+12%), R-prec (+18%) and Prec@10 (+6%).

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Debates over the role and relevance of what has been described as citizen journalism have existed at least since the late 1990s; positions have ranged from the fulsome dismissal of such bottom-up journalism activities (and indeed, almost all user-led content creation) as being part of a new "cult ofthe amateur" (Keen, 2007) to nearly equally simplistic perspectives which predicted citizen journalists would replace the mainstream journalism industry within a short timeframe. A more considered, more realistic perspective would take a somewhat more moderate view. Aided by circumstances including the long-term financial crisis enveloping journalism industries in many developed nations, the creeping corporatization and politicization of journalistic activities in democratic and non-democratic countries alike, and the largely unmet challenge of new, Internet-based media fonns, citizen journalism (as well as other parajournalistic media, including TV comedy such as The Daily Show) has been able to make credible inroads into what used to be the domain of journalism proper.

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Twitter has developed an increasingly visible presence in Australian journalism, and in the discussion of news. Many journalists have begun to explore manageable approaches to incorporating Twitter into their work practices, and for some – like the ABC’s ‘star recruits’ Annabel Crabb and Latika Bourke – it has already become a career driver. This article examines the positioning of journalists as ‘personal brands’ on Twitter, by documenting the visibility of leading personal and institutional accounts during two major political events in Australia: the Rudd/Gillard leadership spill on 23 June 2010, and the day of the subsequent federal election on 21 August 2010. It highlights the fact that in third-party networks such as Twitter, journalists and news organisations no longer operate solely on their own terms, as they do on their own Websites, but gain and maintain prominence in the network and reach for their messages only in concert with other users. It places these observations in a wider context of journalist/audience relations, a decade after the emergence of the first citizen journalism Websites.

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This case study reports on the impact and business transformation of an IMP³rove assessment and follow-up workshop on Australian SME LEVESYS (www.levesys.com), which was undertaken by QMI Solutions. Innovation was not a foreign term to the company, which focuses on the development of enterprise resource planning (ERP) software for the Australian construction sector. However, before seeing and undergoing the IMP³rove process, this company had difficulty articulating their innovation problems and, therefore, had not achieved growth targets from its R&D efforts. This case study highlights the role of IMP³rove in assisting LEVESYS to take the first step in transforming itself through innovation.

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This paper addresses the issue of analogical inference, and its potential role as the mediator of new therapeutic discoveries, by using disjunction operators based on quantum connectives to combine many potential reasoning pathways into a single search expression. In it, we extend our previous work in which we developed an approach to analogical retrieval using the Predication-based Semantic Indexing (PSI) model, which encodes both concepts and the relationships between them in high-dimensional vector space. As in our previous work, we leverage the ability of PSI to infer predicate pathways connecting two example concepts, in this case comprising of known therapeutic relationships. For example, given that drug x TREATS disease z, we might infer the predicate pathway drug x INTERACTS WITH gene y ASSOCIATED WITH disease z, and use this pathway to search for drugs related to another disease in similar ways. As biological systems tend to be characterized by networks of relationships, we evaluate the ability of quantum-inspired operators to mediate inference and retrieval across multiple relations, by testing the ability of different approaches to recover known therapeutic relationships. In addition, we introduce a novel complex vector based implementation of PSI, based on Plate’s Circular Holographic Reduced Representations, which we utilize for all experiments in addition to the binary vector based approach we have applied in our previous research.

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Search technologies are critical to enable clinical sta to rapidly and e ectively access patient information contained in free-text medical records. Medical search is challenging as terms in the query are often general but those in rel- evant documents are very speci c, leading to granularity mismatch. In this paper we propose to tackle granularity mismatch by exploiting subsumption relationships de ned in formal medical domain knowledge resources. In symbolic reasoning, a subsumption (or `is-a') relationship is a parent-child rela- tionship where one concept is a subset of another concept. Subsumed concepts are included in the retrieval function. In addition, we investigate a number of initial methods for combining weights of query concepts and those of subsumed concepts. Subsumption relationships were found to provide strong indication of relevant information; their inclusion in retrieval functions yields performance improvements. This result motivates the development of formal models of rela- tionships between medical concepts for retrieval purposes.

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The Australian e-Health Research Centre and Queensland University of Technology recently participated in the TREC 2012 Medical Records Track. This paper reports on our methods, results and experience using an approach that exploits the concept and inter-concept relationships defined in the SNOMED CT medical ontology. Our concept-based approach is intended to overcome specific challenges in searching medical records, namely vocabulary mismatch and granularity mismatch. Queries and documents are transformed from their term-based originals into medical concepts as defined by the SNOMED CT ontology, this is done to tackle vocabulary mismatch. In addition, we make use of the SNOMED CT parent-child `is-a' relationships between concepts to weight documents that contained concept subsumed by the query concepts; this is done to tackle the problem of granularity mismatch. Finally, we experiment with other SNOMED CT relationships besides the is-a relationship to weight concepts related to query concepts. Results show our concept-based approach performed significantly above the median in all four performance metrics. Further improvements are achieved by the incorporation of weighting subsumed concepts, overall leading to improvement above the median of 28% infAP, 10% infNDCG, 12% R-prec and 7% Prec@10. The incorporation of other relations besides is-a demonstrated mixed results, more research is required to determined which SNOMED CT relationships are best employed when weighting related concepts.

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IT-supported field data management benefits on-site construction management by improving accessibility to the information and promoting efficient communication between project team members. However, most of on-site safety inspections still heavily rely on subjective judgment and manual reporting processes and thus observers’ experiences often determine the quality of risk identification and control. This study aims to develop a methodology to efficiently retrieve safety-related information so that the safety inspectors can easily access to the relevant site safety information for safer decision making. The proposed methodology consists of three stages: (1) development of a comprehensive safety database which contains information of risk factors, accident types, impact of accidents and safety regulations; (2) identification of relationships among different risk factors based on statistical analysis methods; and (3) user-specified information retrieval using data mining techniques for safety management. This paper presents an overall methodology and preliminary results of the first stage research conducted with 101 accident investigation reports.

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To date, the available literature mainly discusses Twitter activity patterns in the context of individual case studies, while comparative research on a large number of communicative events and their dynamics and patterns is missing. By conducting a comparative study of more than 40 different cases (covering topics such as elections, natural disasters, corporate crises, and televised events) we identify a number of distinct types of discussion that can be observed on Twitter. Drawing on a range of communicative metrics, we show that thematic and contextual factors influence the usage of different communicative tools available to Twitter users, such as original tweets, @replies, retweets, and URLs. Based on this first analysis of the overall metrics of Twitter discussions, we also demonstrate stable patterns in the use of Twitter in the context of major topics and events.

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By any measure, 2011 was a year marked by disasters. In Australia, it began with major flooding which saw vast portions of the state of Queensland, including Brisbane and surrounding areas, under water. A significant earthquake caused massive destruction and serious loss of life in Christchurch, New Zealand. And a 9.0 quake off the Sendai coast caused an unprecedented tsunami in Japan and led to the Fukushima meltdown. All this before the end of March; later months would see a range of human-made crises from the Arab Spring to the London riots.

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Twitter is now well-established as an important platform for real-time public communication. Twitter research continues to lag behind these developments, with many studies remaining focused on individual case studies and utilizing home-grown, idiosyncratic, non-repeatable, and non-verifiable research methodologies. While the development of a full-blown “science of Twitter” may remain illusory, it is nonetheless necessary to move beyond such individual scholarship and toward the development of more comprehensive, transferable, and rigorous tools and methods for the study of Twitter on a large scale and in close to real time.

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Amongst the most prominent uses of Twitter at present is its role in the discussion of widely televised events: Twitter’s own statistics for 2011, for example, list major entertainment spectacles (the MTV Music Awards, the BET Awards) and sports matches (the UEFA Champions League final, the FIFA Women’s World Cup final) amongst the events generating the most tweets per second during the year (Twitter, 2011). User activities during such televised events constitute a specific, unique category of Twitter use, which differs clearly from the other major events which generate a high rate of tweets per second (such as crises and breaking news, from the Japanese earthquake and tsunami to the death of Steve Jobs), as preliminary research has shown. During such major media events, by contrast, Twitter is used most predominantly as a technology of fandom instead: it serves in the first place as a backchannel to television and other streaming audiovisual media, enabling users offer their own running commentary on the universally shared media text of the event broadcast as it unfolds live. Centrally, this communion of fans around the shared text is facilitated by the use of Twitter hashtags – unifying textual markers which are now often promoted to prospective audiences by the broadcasters well in advance of the live event itself. This paper examines the use of Twitter as a technology for the expression of shared fandom in the context of a major, internationally televised annual media event: the Eurovision Song Contest. It constitutes a highly publicised, highly choreographed media spectacle whose eventual outcomes are unknown ahead of time and attracts a diverse international audience. Our analysis draws on comprehensive datasets for the ‘official’ event hashtags, #eurovision, #esc, and #sbseurovision. Using innovative methods which combine qualitative and quantitative approaches to the analysis of Twitter datasets containing several hundreds of thousands, we examine overall patterns of participation to discover how audiences express their fandom throughout the event. Minute-by-minute tracking of Twitter activity during the live broadcasts enables us to identify the most resonant moments during each event; we also examine the networks of interaction between participants to detect thematically or geographically determined clusters of interaction, and to identify the most visible and influential participants in each network. Such analysis is able to provide a unique insight into the use of Twitter as a technology for fandom and for what in cultural studies research is called ‘audiencing’: the public performance of belonging to the distributed audience for a shared media event. Our work thus contributes to the examination of fandom practices led by Henry Jenkins (2006) and other scholars, and points to Twitter as an important new medium facilitating the connection and communion of such fans.

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Our paper approaches Twitter through the lens of “platform politics” (Gillespie, 2010), focusing in particular on controversies around user data access, ownership, and control. We characterise different actors in the Twitter data ecosystem: private and institutional end users of Twitter, commercial data resellers such as Gnip and DataSift, data scientists, and finally Twitter, Inc. itself; and describe their conflicting interests. We furthermore study Twitter’s Terms of Service and application programming interface (API) as material instantiations of regulatory instruments used by the platform provider and argue for a more promotion of data rights and literacy to strengthen the position of end users.

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This study makes out the case for the use of the Conversational Analytic method as a research approach that might both extricate and chronicle the features of the journalism interview. It seeks to encourage such research to help inform understanding of this form and to provide further lessons as to the nature of journalism practice. Such studies might follow many paths but this paper focuses more particularly on the outcomes for the debate as to the continued relevance of "objectivity" in informing journalism professional practice. To make out the case for the veracity of CA as a means through which the conduct of journalism practice might be explored the paper examines: the theories of the interaction order that gave rise to the CA method; outlines the key features of the journalism interview as explicated through the CA approach; outlines the implications of such research for the establishment of the standing of "objectivity". It concludes as to the wider relevance of such studies of journalism practice for a fracturing journalism field, which suffers from a lack of benchmarks to measure the public benefit of the range of forms that now proliferate on the internet.