942 resultados para USERS
Resumo:
Cultural objects are increasingly generated and stored in digital form, yet effective methods for their indexing and retrieval still remain an important area of research. The main problem arises from the disconnection between the content-based indexing approach used by computer scientists and the description-based approach used by information scientists. There is also a lack of representational schemes that allow the alignment of the semantics and context with keywords and low-level features that can be automatically extracted from the content of these cultural objects. This paper presents an integrated approach to address these problems, taking advantage of both computer science and information science approaches. We firstly discuss the requirements from a number of perspectives: users, content providers, content managers and technical systems. We then present an overview of our system architecture and describe various techniques which underlie the major components of the system. These include: automatic object category detection; user-driven tagging; metadata transform and augmentation, and an expression language for digital cultural objects. In addition, we discuss our experience on testing and evaluating some existing collections, analyse the difficulties encountered and propose ways to address these problems.
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This talk proceeds from the premise that IR should engage in a more substantial dialogue with cognitive science. After all, how users decide relevance, or how they chose terms to modify a query are processes rooted in human cognition. Recently, there has been a growing literature applying quantum theory (QT) to model cognitive phenomena. This talk will survey recent research, in particular, modelling interference effects in human decision making. One aspect of QT will be illustrated - how quantum entanglement can be used to model word associations in human memory. The implications of this will be briefly discussed in terms of a new approach for modelling concept combinations. Tentative links to human adductive reasoning will also be drawn. The basic theme behind this talk is QT can potentially provide a new genre of information processing models (including search) more aligned with human cognition.
Resumo:
Our students come from diverse backgrounds. They need flexibility in their learning, and opportunities to review aspects of curriculum they are less confident with. An online teaching and learning programme called the Histology Challenge has been developed to supplement learning experiences offered in several first year anatomy and anatomy & physiology units at QUT. The programme is designed to be integrated with the existing Blackboard sites. The Histology Challenge emphasises the foundation concept that a complex system, such as the human body, can be better understood by examining its simpler components. The tutorial allows students to examine the cells and tissues which ultimately determine structural and functional properties of body organs. The program is interactive, asking students to make decisions and choices, demonstrating an integrated understanding of systemic and cellular aspects. It provides users with the ability to progress at their own pace and to test their understanding and knowledge. For the developer the learning activity can be easily controlled and modified via the use of text files. There are several key elements of this programme, designed to promote specific aspects of student learning. Minimum text is used, instead there is a strong emphasis on instructive artwork and original, high quality histology images presented within a framework that reinforces learning and promotes problem solving skills.
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Current multimedia Web search engines still use keywords as the primary means to search. Due to the richness in multimedia contents, general users constantly experience some difficulties in formulating textual queries that are representative enough for their needs. As a result, query reformulation becomes part of an inevitable process in most multimedia searches. Previous Web query formulation studies did not investigate the modification sequences and thus can only report limited findings on the reformulation behavior. In this study, we propose an automatic approach to examine multimedia query reformulation using large-scale transaction logs. The key findings show that search term replacement is the most dominant type of modifications in visual searches but less important in audio searches. Image search users prefer the specified search strategy more than video and audio users. There is also a clear tendency to replace terms with synonyms or associated terms in visual queries. The analysis of the search strategies in different types of multimedia searching provides some insights into user’s searching behavior, which can contribute to the design of future query formulation assistance for keyword-based Web multimedia retrieval systems.
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Searching for multimedia is an important activity for users of Web search engines. Studying user's interactions with Web search engine multimedia buttons, including image, audio, and video, is important for the development of multimedia Web search systems. This article provides results from a Weblog analysis study of multimedia Web searching by Dogpile users in 2006. The study analyzes the (a) duration, size, and structure of Web search queries and sessions; (b) user demographics; (c) most popular multimedia Web searching terms; and (d) use of advanced Web search techniques including Boolean and natural language. The current study findings are compared with results from previous multimedia Web searching studies. The key findings are: (a) Since 1997, image search consistently is the dominant media type searched followed by audio and video; (b) multimedia search duration is still short (>50% of searching episodes are <1 min), using few search terms; (c) many multimedia searches are for information about people, especially in audio search; and (d) multimedia search has begun to shift from entertainment to other categories such as medical, sports, and technology (based on the most repeated terms). Implications for design of Web multimedia search engines are discussed.
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PERWAPI is a component for reading and writing .NET PE-files. The name is a compound acronym for Program Executable – Reader/Writer – Application Programming Interface. The code was written by one of us (Diane Corney) with some contributions from some of the early users of the tool. PERWAPI is a managed component, written entirely in safe C#. The design of the writer part of the component is loosely based on Diane Corney’s previous PEAPI component. It is open source software, and is released under a “FreeBSD-like” license. The source may be downloaded from “http://plas.fit.qut.edu.au/perwapi/” As of the date of this document the code has facilities for reading and writing PEfiles compatible with the latest (beta-2) release of the ”Whidbey” version of .NET, that is, the Visual Studio 2005 framework. An invocation option allows earlier versions of the framework to be targeted.
Resumo:
As user involvement becomes a necessary part of the product development process, various ways of accessing users' latent needs have been developed and studied. Reviews of literatures in user involvement and product development have revealed that accessing users' latent needs and transferring them into design process could be facilitated by effectively implementing user-designer collaboration during the early stage of the design process. In this paper, various types of user-designer collaboration were observed and then distinct characteristics of user-designer collaboration were classified into three categories. 1) Passive objectivity, 2) workplace democratisation, and 3) shared contexts were observed as strategies for better user-designer collaboration, which have been employed in the area of user-centred design, user participatory design and design for experiencing. Based on the literature review, this paper proposed a basic collaboration mechanism between the users and the designers during the early stage of the design process and then discussed how its mechanism will help to describe the interactions between the users and the designers during the user involvement sessions.
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The World Wide Web has become a medium for people to share information. People use Web-based collaborative tools such as question answering (QA) portals, blogs/forums, email and instant messaging to acquire information and to form online-based communities. In an online QA portal, a user asks a question and other users can provide answers based on their knowledge, with the question usually being answered by many users. It can become overwhelming and/or time/resource consuming for a user to read all of the answers provided for a given question. Thus, there exists a need for a mechanism to rank the provided answers so users can focus on only reading good quality answers. The majority of online QA systems use user feedback to rank users’ answers and the user who asked the question can decide on the best answer. Other users who didn’t participate in answering the question can also vote to determine the best answer. However, ranking the best answer via this collaborative method is time consuming and requires an ongoing continuous involvement of users to provide the needed feedback. The objective of this research is to discover a way to recommend the best answer as part of a ranked list of answers for a posted question automatically, without the need for user feedback. The proposed approach combines both a non-content-based reputation method and a content-based method to solve the problem of recommending the best answer to the user who posted the question. The non-content method assigns a score to each user which reflects the users’ reputation level in using the QA portal system. Each user is assigned two types of non-content-based reputations cores: a local reputation score and a global reputation score. The local reputation score plays an important role in deciding the reputation level of a user for the category in which the question is asked. The global reputation score indicates the prestige of a user across all of the categories in the QA system. Due to the possibility of user cheating, such as awarding the best answer to a friend regardless of the answer quality, a content-based method for determining the quality of a given answer is proposed, alongside the non-content-based reputation method. Answers for a question from different users are compared with an ideal (or expert) answer using traditional Information Retrieval and Natural Language Processing techniques. Each answer provided for a question is assigned a content score according to how well it matched the ideal answer. To evaluate the performance of the proposed methods, each recommended best answer is compared with the best answer determined by one of the most popular link analysis methods, Hyperlink-Induced Topic Search (HITS). The proposed methods are able to yield high accuracy, as shown by correlation scores: Kendall correlation and Spearman correlation. The reputation method outperforms the HITS method in terms of recommending the best answer. The inclusion of the reputation score with the content score improves the overall performance, which is measured through the use of Top-n match scores.
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Over the last decade, the rapid growth and adoption of the World Wide Web has further exacerbated user needs for e±cient mechanisms for information and knowledge location, selection, and retrieval. How to gather useful and meaningful information from the Web becomes challenging to users. The capture of user information needs is key to delivering users' desired information, and user pro¯les can help to capture information needs. However, e®ectively acquiring user pro¯les is di±cult. It is argued that if user background knowledge can be speci¯ed by ontolo- gies, more accurate user pro¯les can be acquired and thus information needs can be captured e®ectively. Web users implicitly possess concept models that are obtained from their experience and education, and use the concept models in information gathering. Prior to this work, much research has attempted to use ontologies to specify user background knowledge and user concept models. However, these works have a drawback in that they cannot move beyond the subsumption of super - and sub-class structure to emphasising the speci¯c se- mantic relations in a single computational model. This has also been a challenge for years in the knowledge engineering community. Thus, using ontologies to represent user concept models and to acquire user pro¯les remains an unsolved problem in personalised Web information gathering and knowledge engineering. In this thesis, an ontology learning and mining model is proposed to acquire user pro¯les for personalised Web information gathering. The proposed compu- tational model emphasises the speci¯c is-a and part-of semantic relations in one computational model. The world knowledge and users' Local Instance Reposito- ries are used to attempt to discover and specify user background knowledge. From a world knowledge base, personalised ontologies are constructed by adopting au- tomatic or semi-automatic techniques to extract user interest concepts, focusing on user information needs. A multidimensional ontology mining method, Speci- ¯city and Exhaustivity, is also introduced in this thesis for analysing the user background knowledge discovered and speci¯ed in user personalised ontologies. The ontology learning and mining model is evaluated by comparing with human- based and state-of-the-art computational models in experiments, using a large, standard data set. The experimental results are promising for evaluation. The proposed ontology learning and mining model in this thesis helps to develop a better understanding of user pro¯le acquisition, thus providing better design of personalised Web information gathering systems. The contributions are increasingly signi¯cant, given both the rapid explosion of Web information in recent years and today's accessibility to the Internet and the full text world.
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Tagging has become one of the key activities in next generation websites which allow users selecting short labels to annotate, manage, and share multimedia information such as photos, videos and bookmarks. Tagging does not require users any prior training before participating in the annotation activities as they can freely choose any terms which best represent the semantic of contents without worrying about any formal structure or ontology. However, the practice of free-form tagging can lead to several problems, such as synonymy, polysemy and ambiguity, which potentially increase the complexity of managing the tags and retrieving information. To solve these problems, this research aims to construct a lightweight indexing scheme to structure tags by identifying and disambiguating the meaning of terms and construct a knowledge base or dictionary. News has been chosen as the primary domain of application to demonstrate the benefits of using structured tags for managing the rapidly changing and dynamic nature of news information. One of the main outcomes of this work is an automatically constructed vocabulary that defines the meaning of each named entity tag, which can be extracted from a news article (including person, location and organisation), based on experts suggestions from major search engines and the knowledge from public database such as Wikipedia. To demonstrate the potential applications of the vocabulary, we have used it to provide more functionalities in an online news website, including topic-based news reading, intuitive tagging, clipping and sharing of interesting news, as well as news filtering or searching based on named entity tags. The evaluation results on the impact of disambiguating tags have shown that the vocabulary can help to significantly improve news searching performance. The preliminary results from our user study have demonstrated that users can benefit from the additional functionalities on the news websites as they are able to retrieve more relevant news, clip and share news with friends and families effectively.
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These National Guidelines and Case Studies for Digital Modelling are the outcomes from one of a number of Building Information Modelling (BIM)-related projects undertaken by the CRC for Construction Innovation. Since the CRC opened its doors in 2001, the industry has seen a rapid increase in interest in BIM, and widening adoption. These guidelines and case studies are thus very timely, as the industry moves to model-based working and starts to share models in a new context called integrated practice. Governments, both federal and state, and in New Zealand are starting to outline the role they might take, so that in contrast to the adoption of 2D CAD in the early 90s, we ensure that a national, industry-wide benefit results from this new paradigm of working. Section 1 of the guidelines give us an overview of BIM: how it affects our current mode of working, what we need to do to move to fully collaborative model-based facility development. The role of open standards such as IFC is described as a mechanism to support new processes, and make the extensive design and construction information available to asset operators and managers. Digital collaboration modes, types of models, levels of detail, object properties and model management complete this section. It will be relevant for owners, managers and project leaders as well as direct users of BIM. Section 2 provides recommendations and guides for key areas of model creation and development, and the move to simulation and performance measurement. These are the more practical parts of the guidelines developed for design professionals, BIM managers, technical staff and ‘in the field’ workers. The guidelines are supported by six case studies including a summary of lessons learnt about implementing BIM in Australian building projects. A key aspect of these publications is the identification of a number of important industry actions: the need for BIM-compatible product information and a national context for classifying product data; the need for an industry agreement and setting process-for-process definition; and finally, the need to ensure a national standard for sharing data between all of the participants in the facility-development process.
Resumo:
These National Guidelines and Case Studies for Digital Modelling are the outcomes from one of a number of Building Information Modelling (BIM)-related projects undertaken by the CRC for Construction Innovation. Since the CRC opened its doors in 2001, the industry has seen a rapid increase in interest in BIM, and widening adoption. These guidelines and case studies are thus very timely, as the industry moves to model-based working and starts to share models in a new context called integrated practice. Governments, both federal and state, and in New Zealand are starting to outline the role they might take, so that in contrast to the adoption of 2D CAD in the early 90s, we ensure that a national, industry-wide benefit results from this new paradigm of working. Section 1 of the guidelines give us an overview of BIM: how it affects our current mode of working, what we need to do to move to fully collaborative model-based facility development. The role of open standards such as IFC is described as a mechanism to support new processes, and make the extensive design and construction information available to asset operators and managers. Digital collaboration modes, types of models, levels of detail, object properties and model management complete this section. It will be relevant for owners, managers and project leaders as well as direct users of BIM. Section 2 provides recommendations and guides for key areas of model creation and development, and the move to simulation and performance measurement. These are the more practical parts of the guidelines developed for design professionals, BIM managers, technical staff and ‘in the field’ workers. The guidelines are supported by six case studies including a summary of lessons learnt about implementing BIM in Australian building projects. A key aspect of these publications is the identification of a number of important industry actions: the need for BIMcompatible product information and a national context for classifying product data; the need for an industry agreement and setting process-for-process definition; and finally, the need to ensure a national standard for sharing data between all of the participants in the facility-development process.
Resumo:
The two outcome indices described in a companion paper (Sanson et al., Child Indicators Research, 2009) were developed using data from the Longitudinal Study of Australian Children (LSAC). These indices, one for infants and the other for 4 year to 5 year old children, were designed to fill the need for parsimonious measures of children’s developmental status to be used in analyses by a broad range of data users and to guide government policy and interventions to support young children’s optimal development. This paper presents evidence from Wave 1data from LSAC to support the validity of these indices and their three domain scores of Physical, Social/Emotional, and Learning. Relationships between the indices and child, maternal, family, and neighborhood factors which are known to relate concurrently to child outcomes were examined. Meaningful associations were found with the selected variables, thereby demonstrating the usefulness of the outcome indices as tools for understanding children’s development in their family and socio-cultural contexts. It is concluded that the outcome indices are valuable tools for increasing understanding of influences on children’s development, and for guiding policy and practice to optimize children’s life chances.
Resumo:
The Longitudinal Study of Australian Children (LSAC) is a major national study examining the lives of Australian children, using a cross-sequential cohort design and data from parents, children, and teachers for 5,107 infants (3–19 months) and 4,983 children (4–5 years). Its data are publicly accessible and are used by researchers from many disciplinary backgrounds. It contains multiple measures of children’s developmental outcomes as well as a broad range of information on the contexts of their lives. This paper reports on the development of summary outcome indices of child development using the LSAC data. The indices were developed to fill the need for indicators suitable for use by diverse data users in order to guide government policy and interventions which support young children’s optimal development. The concepts underpinning the indices and the methods of their development are presented. Two outcome indices (infant and child) were developed, each consisting of three domains—health and physical development, social and emotional functioning, and learning competency. A total of 16 measures are used to make up these three domains in the Outcome Index for the Child Cohort and six measures for the Infant Cohort. These measures are described and evidence supporting the structure of the domains and their underlying latent constructs is provided for both cohorts. The factorial structure of the Outcome Index is adequate for both cohorts, but was stronger for the child than infant cohort. It is concluded that the LSAC Outcome Index is a parsimonious measure representing the major components of development which is suitable for non-specialist data users. A companion paper (Sanson et al. 2010) presents evidence of the validity of the Index.
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Credentials are a salient form of cultural capital and if a student’s learning and productions are not assessed, they are invisible in current social systems of education and employment. In this field, invisible equals non-existent. This paper arises from the context of an alternative education institution where conventional educational assessment techniques currently fail to recognise the creativity and skills of a cohort of marginalised young people. In order to facilitate a new assessment model an electronic portfolio system (EPS) is being developed and trialled to capture evidence of students’ learning and their productions. In so doing a dynamic system of arranging, exhibiting, exploiting and disseminating assessment data in the form of coherent, meaningful and valuable reports will be maintained. The paper investigates the notion of assessing development of creative thinking and skills through the means of a computerised system that operates in an area described as the efield. A model of the efield is delineated and is explained as a zone existing within the internet where free users exploit the cloud and cultivate social and cultural capital. Drawing largely on sociocultural theory and Bourdieu’s concepts of field, habitus and capitals, the article positions the efield as a potentially productive instrument in assessment for learning practices. An important aspect of the dynamics of this instrument is the recognition of teachers as learners. This is seen as an integral factor in the sociocultural approach to assessment for learning practices that will be deployed with the EPS. What actually takes place is argued to be assessment for learning as a field of exchange. The model produced in this research is aimed at delivering visibility and recognition through an engaging instrument that will enhance the prospects of marginalised young people and shift the paradigm for assessment in a creative world.