Dramatic flow in interactive 3D narrative
- Authors: Macfadyen, Alyx , Stranieri, Andrew , Yearwood, John
- Date: 2007
- Type: Text , Conference paper
- Relation: Paper presented at Fourth Australiasian Conference on Interactive Entertainment, IE2007, RMIT University, Melbourne, Victoria : 3rd-5th December 2007
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- Description: The concept of dramatic level is crucial for a model of dramatic flow. We present a framework to maintain optimal dramatic flow in an interactive 3D environment where both linear and emergent narratives co-exist. Unlike all other interactive narrative prototypes the framework advanced focuses on the optimal dramatic flow of the emerging user narrative so that although fragmented, it can be engaging and make sense. Using a sample narrative from Ovid’s Metamorphoses [18] we demonstrate a method to evaluate dramatic levels as plot points so that movement across narratives retains a strong dramatic flow. Although users may never choose to explore any given linear narrative in its entirety, the result is an engaging and rich narrative experience.
- Description: 2003004706
Narrative-based interactive learning environments from modelling reasoning
- Authors: Yearwood, John , Stranieri, Andrew
- Date: 2007
- Type: Text , Journal article
- Relation: Educational Technology and Society Vol. 10, no. 3 (2007), p. 192-208
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- Description: Narrative and story telling has a long history of use in structuring, organising and communicating human experience. This paper describes a narrative based interactive intelligent learning environment which aims to elucidate practical reasoning using interactive emergent narratives that can be used in training novices in decision making. Its design is based on an approach to generating narrative from knowledge that has been modelled in specific decision/reasoning domains. The approach uses a narrative model that is guided partially by inference and contextual information contained in the particular knowledge representation used, the Generic/Actual argument model of structured reasoning. The approach is described with examples in the area of critical care nursing training and positive learning outcomes are reported. © International Forum of Educational Technology & Society (IFETS).
- Description: C1
- Description: 2003002522
Opinion search in web logs
- Authors: Osman, Deanna , Yearwood, John
- Date: 2007
- Type: Text , Conference paper
- Relation: Paper presented at Eighteenth Australasian Database Conference, ADC 2007, Ballarat, Victoria : 29th January-2nd February 2007 p. 133-139
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- Description: Web logs(blogs) are a fast growing forum for people of all ages to express their feelings and opinions on topics of interest. The entries are often written in informal language without the structure found in newswire or published articles. One blog entry may contain many topics, these topics may express an opinion or a fact on a particular topic. This research is in contrast to work on opinion detection which has been carried out on more formally authored texts and on segments that are either whole documents or sentences. Whole web logs are divided into topics using a simple text segmentation approach. Similarity scores are used to distinguish where topic changers occur. The results are compared to human-evaluated topic changes and the most accurate algorithm is used in the remainder of the research. Words within each topic-block are allocated weightings depending on their opinion-bearing strength. Two approaches of using these weights, the sum and the maximum, are used to determine whether the topic-block is opinion-bearing or non-opinion-bearing. The opinion-bearing topic-blocks are rated by human evaluators as either opinion-bearing or non-opinion-bearing with precision of 67% for approach A and 70% for approach B. These results are compared with two approaches on published text to identify the difference between web logs and published articles.
- Description: 2003004895
Two-step comprehensive open domain text annotation with frame semantics
- Authors: Ofoghi, Bahadorreza , Yearwood, John , Ma, Liping
- Date: 2007
- Type: Text , Conference paper
- Relation: Paper presented at Australasian Language Technology Workshop 2007, Melbourne Zoo, Melbourne, Victoria : 10th-11th December 2007 p. 83-91
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- Description: With shallow semantic parsing tasks receiving more attention in many natural language applications, there is a need for labelled corpora for learning the specific tags under consideration. In this paper, we discuss a two-step semantic class and semantic role assignment based on the FrameNet elements over a subset of the AQUAINT collection with a reasonable coverage over the semantic frames in FrameNet. The quality of the annotation task is examined through inter-annotator agreement. The methodology described in this work for measuring inter-annotator agreement can be adapted for similar tasks. Some central aspects of the task are also detailed in this paper.
- Description: 2003005522
Using corpus analysis to inform research into opinion detection in blogs
- Authors: Osman, Deanna , Yearwood, John , Vamplew, Peter
- Date: 2007
- Type: Text , Conference paper
- Relation: Paper presented at Sixth Australasian Data Mining Conference, AusDM 2007, Gold Coast, Queensland, Victoria : 3rd-4th December 2007 p. 65-75
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- Description: Opinion detection research relies on labeled documents for training data, either by assumptions based on the document's origin or by using human assessors to categorise the documents. In recent years, blogs have become a source for opinion identification research (TREC Blog06). This study analyses the part-of-speech proportion and the words used within various corpora, determining key differences and similarities useful when preparing for opinion identification research. The resulting comparisons between the characteristics of the various corpora is detailed and discussed. In particular, opinion bearing and non opinion Blog06 documents were found to display a high level of similarity, indicating that blog documents assessed at the document level cannot be used as training data in opinion identification research.
- Description: 2003004892
Using links to aid web classification
- Authors: Xie, Wei , Mammadov, Musa , Yearwood, John
- Date: 2007
- Type: Text , Conference paper
- Relation: Paper presented at 6th IEEE/ACIS International Conference on Computer and Information Science, ICIS 2007, Melbourne, Victoria : 11th-13th July 2007 p. 981-986
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- Description: In this paper, we will present a new approach of using link information to improve the accuracy and efficiency of web classification. However, different from others, we only use the mappings between linked documents and their own class or classes. In this case, we only need to add a few features called linked-class features into the datasets. We apply SVM and BoosTexter for classification. We show that the classification accuracy can be improved based on mixtures of ordinary word features and out-linked-class features. We analyze and discuss the reason of this improvement.
- Description: 2003005438
Visual tools for analysing evolution, emergence, and error in data streams
- Authors: Hart, Sol , Yearwood, John , Bagirov, Adil
- Date: 2007
- Type: Text , Conference paper
- Relation: Paper presented at 6th IEEE/ACIS International Conference on Computer and Information Science, ICIS 2007, Melbourne, Victoria : 11th-13th July 2007 p. 987-992
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- Description: The relatively new field of stream mining has necessitated the development of robust drift-aware algorithms that provide accurate, real time, data handling capabilities. Tools are needed to assess and diagnose important trends and investigate drift evolution parameters. In this paper, we present two new and novel visualisation techniques, Pixie and Luna graphs, which incorporate salient group statistics coupled with intuitive visual representations of multidimensional groupings over time. Through the novel representations presented here, spatial interactions between temporal divisions can be diagnosed and overall distribution patterns identified. It provides a means of evaluating in non-constrained capacity, commonly constrained evolutionary problems.
- Description: 2003005432
A new scoring system in Cystic Fibrosis : Statistical tools for database analysis - A preliminary report
- Authors: Hafen, Gaudenz , Hurst, Cameron , Yearwood, John , Smith, Julie , Dzalilov, Zari , Robinson, P. J.
- Date: 2008
- Type: Text , Journal article
- Relation: BMC Medical Informatics and Decision Making Vol. 8, no. 44 (2008), p.1-11
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- Description: Background. Cystic fibrosis is the most common fatal genetic disorder in the Caucasian population. Scoring systems for assessment of Cystic fibrosis disease severity have been used for almost 50 years, without being adapted to the milder phenotype of the disease in the 21st century. The aim of this current project is to develop a new scoring system using a database and employing various statistical tools. This study protocol reports the development of the statistical tools in order to create such a scoring system. Methods. The evaluation is based on the Cystic Fibrosis database from the cohort at the Royal Children's Hospital in Melbourne. Initially, unsupervised clustering of the all data records was performed using a range of clustering algorithms. In particular incremental clustering algorithms were used. The clusters obtained were characterised using rules from decision trees and the results examined by clinicians. In order to obtain a clearer definition of classes expert opinion of each individual's clinical severity was sought. After data preparation including expert-opinion of an individual's clinical severity on a 3 point-scale (mild, moderate and severe disease), two multivariate techniques were used throughout the analysis to establish a method that would have a better success in feature selection and model derivation: 'Canonical Analysis of Principal Coordinates' and 'Linear Discriminant Analysis'. A 3-step procedure was performed with (1) selection of features, (2) extracting 5 severity classes out of a 3 severity class as defined per expert-opinion and (3) establishment of calibration datasets. Results. (1) Feature selection: CAP has a more effective "modelling" focus than DA. (2) Extraction of 5 severity classes: after variables were identified as important in discriminating contiguous CF severity groups on the 3-point scale as mild/moderate and moderate/severe, Discriminant Function (DF) was used to determine the new groups mild, intermediate moderate, moderate, intermediate severe and severe disease. (3) Generated confusion tables showed a misclassification rate of 19.1% for males and 16.5% for females, with a majority of misallocations into adjacent severity classes particularly for males. Conclusion. Our preliminary data show that using CAP for detection of selection features and Linear DA to derive the actual model in a CF database might be helpful in developing a scoring system. However, there are several limitations, particularly more data entry points are needed to finalize a score and the statistical tools have further to be refined and validated, with re-running the statistical methods in the larger dataset. © 2008 Hafen et al; licensee BioMed Central Ltd.
A web-based Narrative construction environment
- Authors: Yearwood, John , Stranieri, Andrew , Osman, Deanna
- Date: 2008
- Type: Text , Conference paper
- Relation: Paper presented at NILE 2008: 5th International Conference on Narrative and Interactive Learning Environments, Edinburgh, Scotland : 6th-8th August 2008 p. 78-81
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- Description: This paper describes a web-based environment for constructing narrative from story snippets contributed by a community of interest. The underlying model uses an argument based structure to infer the next event in the narrative sequence. The approach makes use of both events and higher level story elements derived from Polti’s dramatic situations. Dramatic situations used are consistent with a theme, and events are generally constrained by the dramatic situation. The narrative generated is a function of the event history, the dramatic situations chosen and the plausible inferences about next events that are contributed by a community of interest in the theme. At this stage, a player’s actions are simulated using a random selection from a set and the implementation of a nonsense filter. Example outputs from the system are provided and discussed.
- Description: 2003006499
AWSum - applying data mining in a health care scenario
- Authors: Quinn, Anthony , Jelinek, Herbert , Stranieri, Andrew , Yearwood, John
- Date: 2008
- Type: Text , Conference paper
- Relation: Paper presented at International Conference on Intelligent Sensors, Sensor Networks and Information Processing, ISSNIP 2008, Sydney, New South Wales : 15th-18th December 2008 p. 291-296
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- Description: This paper investigates the application of a new data mining algorithm called Automated Weighted Sum, (AWSum), to diabetes screening data to explore its use in providing researchers with new insight into the disease and secondarily to explore the potential the algorithm has for the generation of prognostic models for clinical use. There are many data mining classifiers that produce high levels of predictive accuracy but their application to health research and clinical applications is limited because they are complex, produce results that are difficult to interpret and are difficult to integrate with current knowledge and practises. This is because most focus on accuracy at the expense of informing the user as to the influences that lead to their classification results. By providing this information on influences a researcher can be pointed to new potentially interesting avenues for investigation. AWSum measures influence by calculating a weight for each feature value that represents its influence on a class value relative to other class values. The results produced, although on limited data, indicated the approach has potential uses for research and has some characteristics that may be useful in the future development of prognostic models.
- Description: 2003006660
Dramatic level analysis for interactive narrative
- Authors: Macfadyen, Alyx , Stranieri, Andrew , Yearwood, John
- Date: 2008
- Type: Text , Conference paper
- Relation: Paper presented at NILE 2008: 5th International Conference on Narrative and Interactive Learning Environments, Edinburgh, Scotland : 6th-8th August 2008 p. 17-22
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- Description: In interactive 3D narratives, a user’s narrative emerges through interactions with the system and embodied agencies (characters) mediated through the 3D environment. We present a methodology that identifies and measures four factors in interactive narrative where agency is present. We describe a technique for measuring drama, agency and engagement and compare the centrality of a designed interactive narrative with the emergent participatory narrative. This methodology has application as an analytic device for any interactive narrative where agency is fundamental. The adoption of the FrameNet semantic resource and the interpretation of interaction in narrative, situate this work in the domain of 3D interactive narratives, mixed and augmented realities and polymorphic narratives that cross forms of media.
- Description: 2003006540
New traceability codes and identification algorithm for tracing pirates
- Authors: Wu, Xinwen , Watters, Paul , Yearwood, John
- Date: 2008
- Type: Text , Conference paper
- Relation: Paper presented at 2008 International Symposium on Parallel and Distributed Processing with Applications, ISPA 2008, Sydney, New South Wales : 10th-12th December 2008 p. 719-724
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- Description: With the increasing popularity of digital products, there is a strong desire to protect the rights of owners against illegal redistribution. Traditional encryption schemes alone do not provide a comprehensive solution to digital rights management, since they do not prevent users who are authorized to use a digital product for their own use from transferring the cleartext content to unauthorized users. However, traceability schemes can be used to trace the illegitimate redistributors effectively. Two types of traceability schemes have been proposed in the literature - traceability codes (TA codes), and codes with the identifiable parent properties (IPP codes). TA codes are special IPP codes, and many TA codes implement an efficient identification algorithm which can determine at least one redistributor. However, many IPP codes are not TA codes, in which case, no efficient identification algorithms are available. In this paper, we generalize the definition of TA codes to derive a new family of traceability codes that is much larger than the family of traditional TA codes. By using existing decoding algorithms with respect to the Lee distance, an efficient identification algorithm is proposed for generalized TA codes. Furthermore, we show that the identification algorithm of generalized TA codes can find more redistributors than those of traditional TA codes.
- Description: 2003006288
Toward computer mediated elicitation of a community's core values for sustainable decision making
- Authors: Stranieri, Andrew , Yearwood, John , Afshar, Faye
- Date: 2008
- Type: Text , Conference paper
- Relation: Paper presented at 11th Annual Australian Conference on Knowledge Management and Intelligent Decision Support ACKMIDS 2008 p. 1-14
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Weblogs for market research : Improving opinion detection using system fusion
- Authors: Osman, Deanna , Yearwood, John , Vamplew, Peter
- Date: 2008
- Type: Text , Conference paper
- Relation: Paper presented at International Conference on Service Systems and Service Management, 2008, Melbourne, Victoria : 30th June - 2nd July 2008 p. 1-6
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- Description: Searching for opinions on a specific product or service within blogs is a new frontier for market researchers. This research investigates the use of system fusion methods to improve mean average precision (MAP) results achieved by the Text REtrieval Conference (TREC) Blog06 participants and reports the improved MAP results. It is hypothesized that diversity of the inputs is vital to maximising the MAP improvements. This is shown in the improvement in MAP values achieved by some of the participantpsilas ranked lists. The growth in the number of blog authors who write valuable opinions about their life experiences has led to an unsolicited resource of opinions on products, politics and services. In 2006, TREC collected blogs and set a task of detecting opinions on given topics to their participants, reporting the results using MAP.
- Description: 2003007757
A classification algorithm that derives weighted sum scores for insight into disease
- Authors: Quinn, Anthony , Stranieri, Andrew , Yearwood, John , Hafen, Gaudenz
- Date: 2009
- Type: Text , Conference paper
- Relation: Paper presented at Third Australasian Workshop on Health Informatics and Knowledge Management (HIKM 2009), Wellington, New Zealand : Vol. 97, p. 13-17
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- Description: Data mining is often performed with datasets associated with diseases in order to increase insights that can ultimately lead to improved prevention or treatment. Classification algorithms can achieve high levels of predictive accuracy but have limited application for facilitating the insight that leads to deeper understanding of aspects of the disease. This is because the representation of knowledge that arises from classification algorithms is too opaque, too complex or too sparse to facilitate insight. Clustering, association and visualisation approaches enable greater scope for clinicians to be engaged in a way that leads to insight, however predictive accuracy is compromised or non-existent. This research investigates the practical applications of Automated Weighted Sum, (AWSum), a classification algorithm that provides accuracy comparable to other techniques whilst providing some insight into the data. This is achieved by calculating a weight for each feature value that represents its influence on the class value. Clinicians are very familiar with weighted sum scoring scales so the internal representation is intuitive and easily understood. This paper presents results from the use of the AWSum approach with data from patients suffering from Cystic Fibrosis.
A constraint-based evolutionary learning approach to the expectation maximization for optimal estimation of the hidden Markov model for speech signal modeling
- Authors: Huda, Shamsul , Yearwood, John , Togneri, Roberto
- Date: 2009
- Type: Text , Journal article
- Relation: IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics Vol. 39, no. 1 (2009), p. 182-197
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- Description: This paper attempts to overcome the tendency of the expectation-maximization (EM) algorithm to locate a local rather than global maximum when applied to estimate the hidden Markov model (HMM) parameters in speech signal modeling. We propose a hybrid algorithm for estimation of the HMM in automatic speech recognition (ASR) using a constraint-based evolutionary algorithm (EA) and EM, the CEL-EM. The novelty of our hybrid algorithm (CEL-EM) is that it is applicable for estimation of the constraint-based models with many constraints and large numbers of parameters (which use EM) like HMM. Two constraint-based versions of the CEL-EM with different fusion strategies have been proposed using a constraint-based EA and the EM for better estimation of HMM in ASR. The first one uses a traditional constraint-handling mechanism of EA. The other version transforms a constrained optimization problem into an unconstrained problem using Lagrange multipliers. Fusion strategies for the CEL-EM use a staged-fusion approach where EM has been plugged with the EA periodically after the execution of EA for a specific period of time to maintain the global sampling capabilities of EA in the hybrid algorithm. A variable initialization approach (VIA) has been proposed using a variable segmentation to provide a better initialization for EA in the CEL-EM. Experimental results on the TIMIT speech corpus show that CEL-EM obtains higher recognition accuracies than the traditional EM algorithm as well as a top-standard EM (VIA-EM, constructed by applying the VIA to EM). © 2008 IEEE.
A formula for multiple classifiers in data mining based on Brandt semigroups
- Authors: Kelarev, Andrei , Yearwood, John , Mammadov, Musa
- Date: 2009
- Type: Text , Journal article
- Relation: Semigroup Forum Vol. 78, no. 2 (2009), p. 293-309
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- Description: A general approach to designing multiple classifiers represents them as a combination of several binary classifiers in order to enable correction of classification errors and increase reliability. This method is explained, for example, in Witten and Frank (Data Mining: Practical Machine Learning Tools and Techniques, 2005, Sect. 7.5). The aim of this paper is to investigate representations of this sort based on Brandt semigroups. We give a formula for the maximum number of errors of binary classifiers, which can be corrected by a multiple classifier of this type. Examples show that our formula does not carry over to larger classes of semigroups. © 2008 Springer Science+Business Media, LLC.
A polynomial ring construction for the classification of data
- Authors: Kelarev, Andrei , Yearwood, John , Vamplew, Peter
- Date: 2009
- Type: Text , Journal article
- Relation: Bulletin of the Australian Mathematical Society Vol. 79, no. 2 (2009), p. 213-225
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- Description: Drensky and Lakatos (Lecture Notes in Computer Science, 357 (Springer, Berlin, 1989), pp. 181-188) have established a convenient property of certain ideals in polynomial quotient rings, which can now be used to determine error-correcting capabilities of combined multiple classifiers following a standard approach explained in the well-known monograph by Witten and Frank (Data Mining: Practical Machine Learning Tools and Techniques (Elsevier, Amsterdam, 2005)). We strengthen and generalise the result of Drensky and Lakatos by demonstrating that the corresponding nice property remains valid in a much larger variety of constructions and applies to more general types of ideals. Examples show that our theorems do not extend to larger classes of ring constructions and cannot be simplified or generalised.
Applying clustering and ensemble clustering approaches to phishing profiling
- Authors: Webb, Dean , Yearwood, John , Vamplew, Peter , Ma, Liping , Ofoghi, Bahadorreza , Kelarev, Andrei
- Date: 2009
- Type: Text , Conference paper
- Relation: Paper presented at Eighth Australasian Data Mining Conference, AusDM 2009, University of Melbourne, Melbourne, Victoria : 1st–4th December 2009
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- Description: 2003007911
Cayley graphs as classifiers for data mining : The influence of asymmetries
- Authors: Kelarev, Andrei , Ryan, Joe , Yearwood, John
- Date: 2009
- Type: Text , Journal article
- Relation: Discrete Mathematics Vol. 309, no. 17 (2009), p. 5360-5369
- Relation: http://purl.org/au-research/grants/arc/DP0211866
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- Description: The endomorphism monoids of graphs have been actively investigated. They are convenient tools expressing asymmetries of the graphs. One of the most important classes of graphs considered in this framework is that of Cayley graphs. Our paper proposes a new method of using Cayley graphs for classification of data. We give a survey of recent results devoted to the Cayley graphs also involving their endomorphism monoids. © 2008 Elsevier B.V. All rights reserved.