3,182 research outputs found
Unsupervised Sense-Aware Hypernymy Extraction
In this paper, we show how unsupervised sense representations can be used to
improve hypernymy extraction. We present a method for extracting disambiguated
hypernymy relationships that propagates hypernyms to sets of synonyms
(synsets), constructs embeddings for these sets, and establishes sense-aware
relationships between matching synsets. Evaluation on two gold standard
datasets for English and Russian shows that the method successfully recognizes
hypernymy relationships that cannot be found with standard Hearst patterns and
Wiktionary datasets for the respective languages.Comment: In Proceedings of the 14th Conference on Natural Language Processing
(KONVENS 2018). Vienna, Austri
AutoDesc: Facilitating Convenient Perusal of Web Data Items for Blind Users
Web data items such as shopping products, classifieds, and job listings are indispensable components of most e-commerce websites. The information on the data items are typically distributed over two or more webpages, e.g., a âQuery-Resultsâ page showing the summaries of the items, and âDetailsâ pages containing full information about the items. While this organization of data mitigates information overload and visual cluttering for sighted users, it however increases the interaction overhead and effort for blind users, as back-and-forth navigation between webpages using screen reader assistive technology is tedious and cumbersome. Existing usability-enhancing solutions are unable to provide adequate support in this regard as they predominantly focus on enabling efficient content access within a single webpage, and as such are not tailored for content distributed across multiple webpages. As an initial step towards addressing this issue, we developed AutoDesc, a browser extension that leverages a custom extraction model to automatically detect and pull out additional item descriptions from the âdetailsâ pages, and then proactively inject the extracted information into the âQuery-Resultsâ page, thereby reducing the amount of back-and-forth screen reader navigation between the two webpages. In a study with 16 blind users, we observed that within the same time duration, the participants were able to peruse significantly more data items on average with AutoDesc, compared to that with their preferred screen readers as well as with a state-of-the-art solution
AutoSVD++: An Efficient Hybrid Collaborative Filtering Model via Contractive Auto-encoders
Collaborative filtering (CF) has been successfully used to provide users with
personalized products and services. However, dealing with the increasing
sparseness of user-item matrix still remains a challenge. To tackle such issue,
hybrid CF such as combining with content based filtering and leveraging side
information of users and items has been extensively studied to enhance
performance. However, most of these approaches depend on hand-crafted feature
engineering, which are usually noise-prone and biased by different feature
extraction and selection schemes. In this paper, we propose a new hybrid model
by generalizing contractive auto-encoder paradigm into matrix factorization
framework with good scalability and computational efficiency, which jointly
model content information as representations of effectiveness and compactness,
and leverage implicit user feedback to make accurate recommendations. Extensive
experiments conducted over three large scale real datasets indicate the
proposed approach outperforms the compared methods for item recommendation.Comment: 4 pages, 3 figure
Facilitating Disaster Knowledge Management with Agent-Based Modelling
In developed countries, for recurring disasters (e.g. floods), there are dedicated document repositories of Disaster Management Plans (DISPLANs) that can be accessed as needs arise. Nevertheless, accessing the appropriate plan in a timely manner and sharing activities between plans often requires domain knowledge and intimate knowledge of the plans in the first place. In this paper, we introduce an Agent-Based (AB) knowledge analysis framework to convert DISPLANs into a collection of knowledge units that can be stored in a unified repository. The repository of DM actions then enables the mixing and matching knowledge between different plans. The repository is structured as a layered abstraction according to Meta Object Facility (MOF) to allow the free flow access to the knowledge across the layers. We use the flood DISPLAN of the SES (State Emergency Service), an authoritative DM agency in NSW (New State Wales) State of Australia to illustrate and validate the developed framework
A Twitter narrative of the COVID-19 pandemic in Australia
Social media platforms contain abundant data that can provide comprehensive
knowledge of historical and real-time events. During crisis events, the use of
social media peaks, as people discuss what they have seen, heard, or felt.
Previous studies confirm the usefulness of such socially generated discussions
for the public, first responders, and decision-makers to gain a better
understanding of events as they unfold at the ground level. This study performs
an extensive analysis of COVID-19-related Twitter discussions generated in
Australia between January 2020, and October 2022. We explore the Australian
Twitterverse by employing state-of-the-art approaches from both supervised and
unsupervised domains to perform network analysis, topic modeling, sentiment
analysis, and causality analysis. As the presented results provide a
comprehensive understanding of the Australian Twitterverse during the COVID-19
pandemic, this study aims to explore the discussion dynamics to aid the
development of future automated information systems for epidemic/pandemic
management.Comment: Accepted to ISCRAM 202
Comparative study of healthcare messaging standards for interoperability in ehealth systems
Advances in the information and communication technology have created the field of "health informatics," which amalgamates healthcare, information technology and business. The use of information systems in healthcare organisations dates back to 1960s, however the use of technology for healthcare records, referred to as Electronic Medical Records (EMR), management has surged since 1990âs (Net-Health, 2017) due to advancements the internet and web technologies. Electronic Medical Records (EMR) and sometimes referred to as Personal Health Record (PHR) contains the patientâs medical history, allergy information, immunisation status, medication, radiology images and other medically related billing information that is relevant. There are a number of benefits for healthcare industry when sharing these data recorded in EMR and PHR systems between medical institutions (AbuKhousa et al., 2012). These benefits include convenience for patients and clinicians, cost-effective healthcare solutions, high quality of care, resolving the resource shortage and collecting a large volume of data for research and educational needs. My Health Record (MyHR) is a major project funded by the Australian government, which aims to have all data relating to health of the Australian population stored in digital format, allowing clinicians to have access to patient data at the point of care. Prior to 2015, MyHR was known as Personally Controlled Electronic Health Record (PCEHR). Though the Australian government took consistent initiatives there is a significant delay (Pearce and Haikerwal, 2010) in implementing eHealth projects and related services. While this delay is caused by many factors, interoperability is identified as the main problem (Benson and Grieve, 2016c) which is resisting this project delivery. To discover the current interoperability challenges in the Australian healthcare industry, this comparative study is conducted on Health Level 7 (HL7) messaging models such as HL7 V2, V3 and FHIR (Fast Healthcare Interoperability Resources). In this study, interoperability, security and privacy are main elements compared. In addition, a case study conducted in the NSW Hospitals to understand the popularity in usage of health messaging standards was utilised to understand the extent of use of messaging standards in healthcare sector. Predominantly, the project used the comparative study method on different HL7 (Health Level Seven) messages and derived the right messaging standard which is suitable to cover the interoperability, security and privacy requirements of electronic health record. The issues related to practical implementations, change over and training requirements for healthcare professionals are also discussed
Performance assessment of urban precinct design: a scoping study
Executive Summary: Significant advances have been made over the past decade in the development of scientifically and industry accepted tools for the performance assessment of buildings in terms of energy, carbon, water, indoor environment quality etc. For resilient, sustainable low carbon urban development to be realised in the 21st century, however, will require several radical transitions in design performance beyond the scale of individual buildings. One of these involves the creation and application of leading edge tools (not widely available to built environment professions and practitioners) capable of being applied to an assessment of performance across all stages of development at a precinct scale (neighbourhood, community and district) in either greenfield, brownfield or greyfield settings. A core aspect here is the development of a new way of modelling precincts, referred to as Precinct Information Modelling (PIM) that provides for transparent sharing and linking of precinct object information across the development life cycle together with consistent, accurate and reliable access to reference data, including that associated with the urban context of the precinct.
Neighbourhoods are the âbuilding blocksâ of our cities and represent the scale at which urban design needs to make its contribution to city performance: as productive, liveable, environmentally sustainable and socially inclusive places (COAG 2009). Neighbourhood design constitutes a major area for innovation as part of an urban design protocol established by the federal government (Department of Infrastructure and Transport 2011, see Figure 1). The ability to efficiently and effectively assess urban design performance at a neighbourhood level is in its infancy.
This study was undertaken by Swinburne University of Technology, University of New South Wales, CSIRO and buildingSMART Australasia on behalf of the CRC for Low Carbon Living
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