Automatic domain ontology extraction for context-sensitive opinion mining

Automated analysis of the sentiments presented in online consumer feedbacks can facilitate both organizations’ business strategy development and individual consumers’ comparison shopping. Nevertheless, existing opinion mining methods either adopt a context-free sentiment classification approach or rely on a large number of manually annotated training examples to perform context sensitive sentiment classification. Guided by the design science research methodology, we illustrate the design, development, and evaluation of a novel fuzzy domain ontology based contextsensitive opinion mining system. Our novel ontology extraction mechanism underpinned by a variant of Kullback-Leibler divergence can automatically acquire contextual sentiment knowledge across various product domains to improve the sentiment analysis processes. Evaluated based on a benchmark dataset and real consumer reviews collected from Amazon.com, our system shows remarkable performance improvement over the context-free baseline.

Effective pattern discovery for text mining

Many data mining techniques have been proposed for mining useful patterns in text documents. However, how to effectively use and update discovered patterns is still an open research issue, especially in the domain of text mining. Since most existing text mining methods adopted term-based approaches, they all suffer from the problems of polysemy and synonymy. Over the years, people have often held the hypothesis that pattern (or phrase) based approaches should perform better than the term-based ones, but many experiments did not support this hypothesis. This paper presents an innovative technique, effective pattern discovery which includes the processes of pattern deploying and pattern evolving, to improve the effectiveness of using and updating discovered patterns for finding relevant and interesting information. Substantial experiments on RCV1 data collection and TREC topics demonstrate that the proposed solution achieves encouraging performance.

Mining positive and negative patterns for relevance feature discovery

It is a big challenge to guarantee the quality of discovered relevance features in text documents for describing user preferences because of the large number of terms, patterns, and noise. Most existing popular text mining and classification methods have adopted term-based approaches. However, they have all suffered from the problems of polysemy and synonymy. Over the years, people have often held the hypothesis that pattern-based methods should perform better than term-based ones in describing user preferences, but many experiments do not support this hypothesis. The innovative technique presented in paper makes a breakthrough for this difficulty. This technique discovers both positive and negative patterns in text documents as higher level features in order to accurately weight low-level features (terms) based on their specificity and their distributions in the higher level features. Substantial experiments using this technique on Reuters Corpus Volume 1 and TREC topics show that the proposed approach significantly outperforms both the state-of-the-art term-based methods underpinned by Okapi BM25, Rocchio or Support Vector Machine and pattern based methods on precision, recall and F measures.

Rough sets based reasoning and pattern mining for a two-stage information filtering system

This paper presents a novel two-stage information filtering model which combines the merits of term-based and pattern- based approaches to effectively filter sheer volume of information. In particular, the first filtering stage is supported by a novel rough analysis model which efficiently removes a large number of irrelevant documents, thereby addressing the overload problem. The second filtering stage is empowered by a semantically rich pattern taxonomy mining model which effectively fetches incoming documents according to the specific information needs of a user, thereby addressing the mismatch problem. The experiments have been conducted to compare the proposed two-stage filtering (T-SM) model with other possible "term-based + pattern-based" or "term-based + term-based" IF models. The results based on the RCV1 corpus show that the T-SM model significantly outperforms other types of "two-stage" IF models.

Image-based safety assessment : automated spatial safety risk identification of earthmoving and surface mining activities

This paper presents an automated image‐based safety assessment method for earthmoving and surface mining activities. The literature review revealed the possible causes of accidents on earthmoving operations, investigated the spatial risk factors of these types of accident, and identified spatial data needs for automated safety assessment based on current safety regulations. Image‐based data collection devices and algorithms for safety assessment were then evaluated. Analysis methods and rules for monitoring safety violations were also discussed. The experimental results showed that the safety assessment method collected spatial data using stereo vision cameras, applied object identification and tracking algorithms, and finally utilized identified and tracked object information for safety decision making.

Prognostic modelling options for remaining useful life estimation by industry

Over recent years a significant amount of research has been undertaken to develop prognostic models that can be used to predict the remaining useful life of engineering assets. Implementations by industry have only had limited success. By design, models are subject to specific assumptions and approximations, some of which are mathematical, while others relate to practical implementation issues such as the amount of data required to validate and verify a proposed model. Therefore, appropriate model selection for successful practical implementation requires not only a mathematical understanding of each model type, but also an appreciation of how a particular business intends to utilise a model and its outputs. This paper discusses business issues that need to be considered when selecting an appropriate modelling approach for trial. It also presents classification tables and process flow diagrams to assist industry and research personnel select appropriate prognostic models for predicting the remaining useful life of engineering assets within their specific business environment. The paper then explores the strengths and weaknesses of the main prognostics model classes to establish what makes them better suited to certain applications than to others and summarises how each have been applied to engineering prognostics. Consequently, this paper should provide a starting point for young researchers first considering options for remaining useful life prediction. The models described in this paper are Knowledge-based (expert and fuzzy), Life expectancy (stochastic and statistical), Artificial Neural Networks, and Physical models.

Enhancing business continuity management capacities in the insurance industry : a Southeast Asian perspective

As a resilience enhancing practice, business continuity management (BCM) can play an important role in aiding preparation of the insurance industry for coping with the losses incurred by major discontinuity incidents: regardless of cause. Acknowledging the increasing frequency of unpredictable man-made disasters and natural catastrophes, the insurance industry would benefit from examining and implementing, where suitable, key elements of BCM. Such strategic decisions would assist insurers and re-insurers collectively to enhance mutual capability to respond to, and recover from, the impact of significant losses. This paper presents a comparison of opinions about BCM practitioners in both retail and re-insurance companies on the importance of generic continuity practices with actual levels of BCM practice across the two industry groups in Southeast Asia. It suggests means by which multi-lateral cooperation across Asian economies and between retail and re-insurance market segments might enhance the viability of the insurance industry in the face of increased stress from major natural and socio-technical hazards.

Independent cinema in the Chinese film industry

Chinese independent cinema has developed for more than twenty years. Two sorts of independent cinema exist in China. One is underground cinema, which is produced without official approvals and cannot be circulated in China, and the other are the films which are legally produced by small private film companies and circulated in the domestic film market. This sort of ‘within-system’ independent cinema has played a significant role in the development of Chinese cinema in terms of culture, economics and ideology. In contrast to the amount of comment on underground filmmaking in China, the significance of ‘within-system’ independent cinema has been underestimated by most scholars. This thesis is a study of how political management has determined the development of Chinese independent cinema and how Chinese independent cinema has developed during its various historical trajectories. This study takes media economics as the research approach, and its major methods utilise archive analysis and interviews. The thesis begins with a general review of the definition and business of American independent cinema. Then, after a literature review of Chinese independent cinema, it identifies significant gaps in previous studies and reviews issues of traditional definition and suggests a new definition. After several case studies on the changes in the most famous Chinese directors’ careers, the thesis shows that state studios and private film companies are two essential domestic backers for filmmaking in China. After that, the body of the thesis provides an examination of the development of ‘within-system’ independent cinema. Specifically, three factors: government intervention, the majors’ performance (state studios and, later, the conglomerates) and the market conduct of independent cinema at various points in their trajectories are studied. The key findings of the study are as follows: First, most scholars have overlooked the existence and the significance of within-system Chinese independent cinema. Drawing on an American definition of the independent sector, this thesis proposes a definition of the sector in China: namely, any film that has not been financed, produced, and/or distributed by majors. The thesis also notes important contradictions in applying this definition: i.e. film-making is still dependent on policies that frame industry development. The thesis recognises that major tensions apply to filmmaking in China, which significantly differentiates the Chinese independents from those in the US. Second, the development of Chinese independent cinema is the result the rise of the private sector and the decline of the state studio system. As state studios encountered difficulties the private sector moved forward; consequently the environment improved for independent cinema. Third, before 2003, the film industry in China had little commercialisation. The government controlled independent cinema by means of license and censorship. State studios produced main melody films and Hollywood attracted most of the audiences. Many independent filmmakers focused on commercial films, thus contributing to film commercialisation. Fourth, after 2003, the film industry became increasingly fragmented. The government created distribution and exhibition opportunities for main melody films; conglomerates collaborated with Hong Kong players; Hong Kong co-productions and Hollywood occupied the film market; and small private film companies produced main melody films in order to earn meagre profits. The original contribution of the thesis is to advance the study of Chinese independent cinema. The study suggests a reasonable and practical definition of Chinese independent cinema. It shows how the Chinese government authorities have implemented economic measures to gain ideological control in the film industry. Finally, this the first study on Chinese independent cinema applying a synthesis of economic, political and historical perspectives.

Innovation strategies for developing the traditional souvenir craft industry

This paper describes the concept of innovation strategies for traditional souvenir craft industries. There are many traditional souvenir craft industries in Indonesia, and they have to compete in today‘s global markets. The craftsmanship and uniqueness of traditional crafts must be developed to attract a larger market. This competition is not easy for craftspeople, neither financially nor culturally. The authors propose some innovation strategies to facilitate craftspeople in generating ideas based on their traditional value, to ensure their sustainability in global context. However, even though there are a number of studies about the craft industry and souvenirs, there is little research focused on the souvenir product development process, especially in the traditional craft industry. Considering that souvenirs are products for pleasure which require hedonic value more than utilitarian value, the offered innovation strategy refers to the strategy applied in existing industries that produce hedonic products. Innovation strategy in the fashion industry is selected as a reference, which is discussed by considering the context of the traditional souvenir craft industry. This investigation will support further research about knowledge sharing systems to enable collaborative learning within traditional craftspeople.