Personalized ontology learning for enhancing text mining effectiveness

Over the last decade, the majority of existing search techniques is either keyword- based or category-based, resulting in unsatisfactory effectiveness. Meanwhile, studies have illustrated that more than 80% of users preferred personalized search results. As a result, many studies paid a great deal of efforts (referred to as col- laborative filtering) investigating on personalized notions for enhancing retrieval performance. One of the fundamental yet most challenging steps is to capture precise user information needs. Most Web users are inexperienced or lack the capability to express their needs properly, whereas the existent retrieval systems are highly sensitive to vocabulary. Researchers have increasingly proposed the utilization of ontology-based tech- niques to improve current mining approaches. The related techniques are not only able to refine search intentions among specific generic domains, but also to access new knowledge by tracking semantic relations. In recent years, some researchers have attempted to build ontological user profiles according to discovered user background knowledge. The knowledge is considered to be both global and lo- cal analyses, which aim to produce tailored ontologies by a group of concepts. However, a key problem here that has not been addressed is: how to accurately match diverse local information to universal global knowledge. This research conducts a theoretical study on the use of personalized ontolo- gies to enhance text mining performance. The objective is to understand user information needs by a \bag-of-concepts" rather than \words". The concepts are gathered from a general world knowledge base named the Library of Congress Subject Headings. To return desirable search results, a novel ontology-based mining approach is introduced to discover accurate search intentions and learn personalized ontologies as user profiles. The approach can not only pinpoint users' individual intentions in a rough hierarchical structure, but can also in- terpret their needs by a set of acknowledged concepts. Along with global and local analyses, another solid concept matching approach is carried out to address about the mismatch between local information and world knowledge. Relevance features produced by the Relevance Feature Discovery model, are determined as representatives of local information. These features have been proven as the best alternative for user queries to avoid ambiguity and consistently outperform the features extracted by other filtering models. The two attempt-to-proposed ap- proaches are both evaluated by a scientific evaluation with the standard Reuters Corpus Volume 1 testing set. A comprehensive comparison is made with a num- ber of the state-of-the art baseline models, including TF-IDF, Rocchio, Okapi BM25, the deploying Pattern Taxonomy Model, and an ontology-based model. The gathered results indicate that the top precision can be improved remarkably with the proposed ontology mining approach, where the matching approach is successful and achieves significant improvements in most information filtering measurements. This research contributes to the fields of ontological filtering, user profiling, and knowledge representation. The related outputs are critical when systems are expected to return proper mining results and provide personalized services. The scientific findings have the potential to facilitate the design of advanced preference mining models, where impact on people's daily lives.

Nonrigid face alignment for unknown subject in video

Non-rigid face alignment is a very important task in a large range of applications but the existing tracking based non-rigid face alignment methods are either inaccurate or requiring person-specific model. This dissertation has developed simultaneous alignment algorithms that overcome these constraints and provide alignment with high accuracy, efficiency, robustness to varying image condition, and requirement of only generic model.

A critical analysis of business process management education and alignment with industry demand : an Australian perspective

Business Process Management (BPM) is accepted globally as an organizational approach to enhance productivity and drive cost efficiencies. Studies confirm a shortage of BPM skilled professionals with limited opportunities to develop the required BPM expertise. This study investigates this gap starting from a critical analysis of BPM courses offered by Australian universities and training institutions. These courses were analyzed and mapped against a leading BPM capability framework to determine how well current BPM education and training offerings in Australia address the core capabilities required by BPM professionals globally. To determine the BPM skill-sets sought by industry, online recruitment advertisements were collated, analyzed, and mapped against this BPM capability framework. The outcomes provide a detailed overview on the alignment of available BPM education/training and industry demand. These insights are useful for BPM professionals and their employers to build awareness of the BPM capabilities required for a BPM mature organization. Universities and other training institutions will benefit from these results by understanding where demand is, where the gaps are, and what other BPM education providers are supplying. This structured comparison method could continue to provide a common ground for future discussion across university-industry boundaries and continuous alignment of their respective practices.

Ontology-based product's reputation model

Different reputation models are used in the web in order to generate reputation values for products using uses' review data. Most of the current reputation models use review ratings and neglect users' textual reviews, because it is more difficult to process. However, we argue that the overall reputation score for an item does not reflect the actual reputation for all of its features. And that's why the use of users' textual reviews is necessary. In our work we introduce a new reputation model that defines a new aggregation method for users' extracted opinions about products' features from users' text. Our model uses features ontology in order to define general features and sub-features of a product. It also reflects the frequencies of positive and negative opinions. We provide a case study to show how our results compare with other reputation models.

Integration of sentiment analysis into customer relational model : the importance of feature ontology and synonym

Online business or Electronic Commerce (EC) is getting popular among customers today, as a result large number of product reviews have been posted online by the customers. This information is very valuable not only for prospective customers to make decision on buying product but also for companies to gather information of customers’ satisfaction about their products. Opinion mining is used to capture customer reviews and separated this review into subjective expressions (sentiment word) and objective expressions (no sentiment word). This paper proposes a novel, multi-dimensional model for opinion mining, which integrates customers’ characteristics and their opinion about any products. The model captures subjective expression from product reviews and transfers to fact table before representing in multi-dimensions named as customers, products, time and location. Data warehouse techniques such as OLAP and Data Cubes were used to analyze opinionated sentences. A comprehensive way to calculate customers’ orientation on products’ features and attributes are presented in this paper.

Unsupervised temporal ensemble alignment for rapid annotation

This paper presents a novel framework for the unsupervised alignment of an ensemble of temporal sequences. This approach draws inspiration from the axiom that an ensemble of temporal signals stemming from the same source/class should have lower rank when "aligned" rather than "misaligned". Our approach shares similarities with recent state of the art methods for unsupervised images ensemble alignment (e.g. RASL) which breaks the problem into a set of image alignment problems (which have well known solutions i.e. the Lucas-Kanade algorithm). Similarly, we propose a strategy for decomposing the problem of temporal ensemble alignment into a similar set of independent sequence problems which we claim can be solved reliably through Dynamic Time Warping (DTW). We demonstrate the utility of our method using the Cohn-Kanade+ dataset, to align expression onset across multiple sequences, which allows us to automate the rapid discovery of event annotations.

Agility in consumer retail: sense-response alignment through the eyes of customers

In hyper competition, firms that are agile: sensing and responding better to customer requirements tend to be more successful and achieve supernormal profits. In spite of the widely accepted importance of customer agility, research is limited on this construct. The limited research also has predominantly focussed on the firm’s perspective of agility. However, we propose that the customers are better positioned to determine how well a firm is responding to their requirements (aka a firm’s customer agility). Taking the customers’ stand point, we address the issue of sense and respond alignment in two perspectives-matching and mediating. Based on data collected from customers in a field study, we tested hypothesis pertaining to the two methods of alignment using polynomial regression and response surface methodology. The results provide a good explanation for the role of both forms of alignment on customer satisfaction. Implication for research and practice are discussed.

Automatic classification of free-text radiology reports to identify limb fractures using machine learning and the SNOMED CT ontology

Objective To develop and evaluate machine learning techniques that identify limb fractures and other abnormalities (e.g. dislocations) from radiology reports. Materials and Methods 99 free-text reports of limb radiology examinations were acquired from an Australian public hospital. Two clinicians were employed to identify fractures and abnormalities from the reports; a third senior clinician resolved disagreements. These assessors found that, of the 99 reports, 48 referred to fractures or abnormalities of limb structures. Automated methods were then used to extract features from these reports that could be useful for their automatic classification. The Naive Bayes classification algorithm and two implementations of the support vector machine algorithm were formally evaluated using cross-fold validation over the 99 reports. Result Results show that the Naive Bayes classifier accurately identifies fractures and other abnormalities from the radiology reports. These results were achieved when extracting stemmed token bigram and negation features, as well as using these features in combination with SNOMED CT concepts related to abnormalities and disorders. The latter feature has not been used in previous works that attempted classifying free-text radiology reports. Discussion Automated classification methods have proven effective at identifying fractures and other abnormalities from radiology reports (F-Measure up to 92.31%). Key to the success of these techniques are features such as stemmed token bigrams, negations, and SNOMED CT concepts associated with morphologic abnormalities and disorders. Conclusion This investigation shows early promising results and future work will further validate and strengthen the proposed approaches.

An ontology-based service discovery approach for the provisioning of product-service bundles

More and more traditional manufacturing companies form or join inter-organizational networks to bundle their physical products with related services to offer superior value propositions to their customers. Some of these product-related services can be digitized completely and thus fully delivered electronically. Other services require the physical integration of external factors, but can still be coordinated electronically. In both cases companies and consumers face the problem of discovering appropriate product-related service offerings in the network or market. Based on ideas from the web service discovery discipline we propose a meet-in-the-middle approach between heavy-weight semantic technologies and simple boolean search to address this issue. Our approach is able to consider semantic relations in service descriptions and queries and thus delivers better results than syntax-based search. However – unlike most semantic approaches – it does not require the use of any formal language for semantic markup and thus requires less resources and skills for both service providers and consumers. To fully realize the potentials of the proposed approach a domain ontology is needed. In this research-in-progress paper we construct such an ontology for the domain of product-service bundles through analysis and synthesis of related work on service description. This will serve as an anchor for future research to iteratively improve and evaluate the ontology through collaborative design efforts and practical application.

Vertical alignment of process models – how can we get there?

There is a wide variety of drivers for business process modelling initiatives, reaching from business evolution and process optimisation over compliance checking and process certification to process enactment. That, in turn, results in models that differ in content due to serving different purposes. In particular, processes are modelled on different abstraction levels and assume different perspectives. Vertical alignment of process models aims at handling these deviations. While the advantages of such an alignment for inter-model analysis and change propagation are out of question, a number of challenges has still to be addressed. In this paper, we discuss three main challenges for vertical alignment in detail. Against this background, the potential application of techniques from the field of process integration is critically assessed. Based thereon, we identify specific research questions that guide the design of a framework for model alignment.

Introspective service interface synthesis in business networks

Service mismatches involve the adaptation of structural and behavioural interfaces of services, which in practice incurs long lead times through manual, coding e ort. We propose a framework, complementary to conventional service adaptation, to extract comprehensive and seman- tically normalised service interfaces, useful for interoperability in large business networks and the Internet of Services. The framework supports introspection and analysis of large and overloaded operational signa- tures to derive focal artefacts, namely the underlying business objects of services. A more simpli ed and comprehensive service interface layer is created based on these, and rendered into semantically normalised in- terfaces, given an ontology accrued through the framework from service analysis history. This opens up the prospect of supporting capability comparisons across services, and run-time request backtracking and ad- justment, as consumers discover new features of a service's operations through corresponding features of similar services. This paper provides a rst exposition of the service interface synthesis framework, describing patterns having novel requirements for unilateral service adaptation, and algorithms for interface introspection and business object alignment. A prototype implementation and analysis of web services drawn from com- mercial logistic systems are used to validate the algorithms and identify open challenges and future research directions.

Alignment and differences between the Australian Water Accounting Standard and the Water Accounting Framework for the Minerals Industry

In 2012, the Bureau of Meteorology under the banner of the Water Accounting Standards Board released the Australian Water Accounting Standard 1 (AWAS 1). This standard has been in development since 2007 with key milestones being the release of the Preliminary Australian Water Accounting Standard in 2009, and the exposure draft of the Australian Water Accounting Standard in 2010. Throughout this period, the Minerals Council of Australia’s Water Accounting Framework has developed concurrently with the Australian standards and the standards have informed elements of the framework. However, the framework is not identical to the standard as the objectives between the two are different. The objective of the Water Accounting Framework is to create consistency in water reporting of the minerals industry and to assist companies reporting to corporate sustainability initiatives. The objective of AWAS 1 is to provide information to water management bodies to facilitate decisions about the allocation of water resources. Companies are to report on an annual basis, not only physical flows of water but contractual requirements to supply and obtain water, regardless of whether the transaction has been fulfilled in the reporting period. In contrast, the Water Accounting Framework only reports on flows that have physically happened. The paper will provide summary information on aspects of AWAS 1 that are most relevant to the minerals industry, show the alignment and differences between AWAS 1 and the Water Accounting Framework and explain how to obtain the information for the AWAS 1 reporting statements.

One-step macroscopic alignment of conjugated polymer systems by epitaxial crystallization during spin-coating

The one-step preparation of highly anisotropic polymer semiconductor thin films directly from solution is demonstrated. The conjugated polymer poly(3-hexylthiophene) (P3HT) as well as P3HT:fullerene bulk-heterojunction blends can be spin-coated from a mixture of the crystallizable solvent 1,3,5-trichlorobenzene (TCB) and a second carrier solvent such as chlorobenzene. Solidification is initiated by growth of macroscopic TCB spherulites followed by epitaxial crystallization of P3HT on TCB crystals. Subsequent sublimation of TCB leaves behind a replica of the original TCB spherulites. Thus, highly ordered thin films are obtained, which feature square-centimeter-sized domains that are composed of one spherulite-like structure each. A combination of optical microscopy and polarized photoluminescence spectroscopy reveals radial alignment of the polymer backbone in case of P3HT, whereas P3HT:fullerene blends display a tangential orientation with respect to the center of spherulite-like structures. Moreover, grazing-incidence wide-angle X-ray scattering reveals an increased relative degree of crystallinity and predominantly flat-on conformation of P3HT crystallites in the blend. The use of other processing methods such as dip-coating is also feasible and offers uniaxial orientation of the macromolecule. Finally, the applicability of this method to a variety of other semi-crystalline conjugated polymer systems is established. Those include other poly(3-alkylthiophene)s, two polyfluorenes, the low band-gap polymer PCPDTBT, a diketopyrrolopyrrole (DPP) small molecule as well as a number of polymer:fullerene and polymer:polymer blends. Macroscopic spherulite-like structures of the conjugated polymer poly(3-hexylthiophene) (P3HT) grow directly during spin-coating. This is achieved by processing P3HT or P3HT:fullerene bulk heterojunction blends from a mixture of the crystallizable solvent 1,3,5-trichlorobenzene and a second carrier solvent such as chlorobenzene. Epitaxial growth of the polymer on solidified solvent crystals gives rise to circular-symmetric, spherulite-like structures that feature a high degree of anisotropy.

Exploring the impact of shared domain knowledge on strategic alignment in the Australian public sector

In this age of ever-increasing information technology (IT) driven environments, governments/or public sector organisations (PSOs) are expected to demonstrate the business value of the investment in IT and take advantage of the opportunities offered by technological advancements. Strategic alignment (SA) emerged as a mechanism to bridge the gap between business and IT missions, objectives, and plans in order to ensure value optimisation from investment in IT and enhance organisational performance. However, achieving and sustaining SA remains a challenge requiring even more agility nowadays to keep up with turbulent organisational environments. The shared domain knowledge (SDK) between the IT department and other diverse organisational groups is considered as one of the factors influencing the successful implementation of SA. However, SDK in PSOs has received relatively little empirical attention. This paper presents findings from a study which investigated the influence of SDK on SA within organisations in the Australian public sector. The developed research model examined the relationship of SDK between business and IT domains with SA using a survey of 56 public sector professionals and executives. A key research contribution is the empirical demonstration that increasing levels of SDK between IT and business groups leads to increased SA.

Degree of value alignment : a grounded theory of rural nurse resignations

INTRODUCTION: The shortage of nurses willing to work in rural Australian healthcare settings continues to worsen. Australian rural areas have a lower retention rate of nurses than metropolitan counterparts, with more remote communities experiencing an even higher turnover of nursing staff. When retention rates are lower, patient outcomes are known to be poorer. This article reports a study that sought to explore the reasons why registered nurses resign from rural hospitals in the state of New South Wales, Australia. METHODS: Using grounded theory methods, this study explored the reasons why registered nurses resigned from New South Wales rural hospitals. Data were collected from 12 participants using semi-structured interviews; each participant was a registered nurse who had resigned from a rural hospital. Nurses who had resigned due to retirement, relocation or maternity leave were excluded. Interviews were transcribed verbatim and imported into NVivo software. The constant comparative method of data collection and analysis was followed until a core category emerged. RESULTS: Nurses resigned from rural hospitals when their personal value of how nursing should occur conflicted with the hospital's organisational values driving the practice of nursing. These conflicting values led to a change in the degree of value alignment between the nurse and hospital. The degree of value alignment occurred in three dynamic stages that nurses moved through prior to resigning. The first stage, sharing values, was a time when a nurse and a hospital shared similar values. The second stage was conceding values where, due to perceived changes in a hospital's values, a nurse felt that patient care became compromised and this led to a divergence of values. The final stage was resigning, a stage where a nurse 'gave up' as they felt that their professional integrity was severely compromised. The findings revealed that when a nurse and organisational values were not aligned, conflict was created for a nurse about how they could perform nursing that aligned with their internalised professional values and integrity. Resignation occurred when nurses were unable to realign their personal values to changed organisational values - the organisational values changed due to rural area health service restructures, centralisation of budgets and resources, cumbersome hierarchies and management structures that inhibited communication and decision making, out-dated and ineffective operating systems, insufficient and inexperienced staff, bullying, and a lack of connectedness and shared vision. CONCLUSIONS: To fully comprehend rural nurse resignations, this study identified three stages that nurses move through prior to resignation. Effective retention strategies for the nursing workforce should address contributors to a decrease in value alignment and work towards encouraging the coalescence of nurses' and hospitals' values. It is imperative that strategies enable nurses to provide high quality patient care and promote a sense of connectedness and a shared vision between nurse and hospital. Senior managers need to have clear ways to articulate and imbue organisational values and be explicit in how these values accommodate nurses' values. Ward-level nurse managers have a significant responsibility to ensure that a hospital's values (both explicit and implicit) are incorporated into ward culture.