Aspect-based opinion mining from product reviews using conditional random fields

Product reviews are the foremost source of information for customers and manufacturers to help them make appropriate purchasing and production decisions. Natural language data is typically very sparse; the most common words are those that do not carry a lot of semantic content, and occurrences of any particular content-bearing word are rare, while co-occurrences of these words are rarer. Mining product aspects, along with corresponding opinions, is essential for Aspect-Based Opinion Mining (ABOM) as a result of the e-commerce revolution. Therefore, the need for automatic mining of reviews has reached a peak. In this work, we deal with ABOM as sequence labelling problem and propose a supervised extraction method to identify product aspects and corresponding opinions. We use Conditional Random Fields (CRFs) to solve the extraction problem and propose a feature function to enhance accuracy. The proposed method is evaluated using two different datasets. We also evaluate the effectiveness of feature function and the optimisation through multiple experiments.

Translating road safety research on night-time visibility to the context of mining

In recent years a significant amount of research has been undertaken in collision avoidance and personnel location technology in order to reduce the number of incidents involving pedestrians and mobile plant equipment which are a high risk in underground coal mines. Improving the visibility of pedestrians to drivers would potentially reduce the likelihood of these incidents. In the road safety context, a variety of approaches have been used to make pedestrians more conspicuous to drivers at night (including vehicle and roadway lighting technologies and night vision enhancement systems). However, emerging research from our group and others has demonstrated that clothing incorporating retroreflective markers on the movable joints as well as the torso can provide highly significant improvements in pedestrian visibility in reduced illumination. Importantly, retroreflective markers are most effective when positioned on the moveable joints creating a sensation of “biological motion”. Based only on the motion of points on the moveable joints of an otherwise invisible body, observers can quickly recognize a walking human form, and even correctly judge characteristics such as gender and weight. An important and as yet unexplored question is whether the benefits of these retroreflective clothing configurations translate to the context of mining where workers are operating under low light conditions. Given that the benefits of biomotion clothing are effective for both young and older drivers, as well as those with various eye conditions common in those >50 years reinforces their potential application in the mining industry which employs many workers in this age bracket. This paper will summarise the visibility benefits of retroreflective markers in a biomotion configuration for the mining industry, highlighting that this form of clothing has the potential to be an affordable and convenient way to provide a sizeable safety benefit. It does not involve modifications to vehicles, drivers, or infrastructure. Instead, adding biomotion markings to standard retroreflective vests can enhance the night-time conspicuity of mining workers by capitalising on perceptual capabilities that have already been well documented.

New graph-based algorithms to efficiently solve large scale open pit mining optimisation problems

In the mining optimisation literature, most researchers focused on two strategic-level and tactical-level open-pit mine optimisation problems, which are respectively termed ultimate pit limit (UPIT) or constrained pit limit (CPIT). However, many researchers indicate that the substantial numbers of variables and constraints in real-world instances (e.g., with 50-1000 thousand blocks) make the CPIT’s mixed integer programming (MIP) model intractable for use. Thus, it becomes a considerable challenge to solve the large scale CPIT instances without relying on exact MIP optimiser as well as the complicated MIP relaxation/decomposition methods. To take this challenge, two new graph-based algorithms based on network flow graph and conjunctive graph theory are developed by taking advantage of problem properties. The performance of our proposed algorithms is validated by testing recent large scale benchmark UPIT and CPIT instances’ datasets of MineLib in 2013. In comparison to best known results from MineLib, it is shown that the proposed algorithms outperform other CPIT solution approaches existing in the literature. The proposed graph-based algorithms leads to a more competent mine scheduling optimisation expert system because the third-party MIP optimiser is no longer indispensable and random neighbourhood search is not necessary.

The hidden injuries of mining: Frontier cultural conflict

This chapter addresses a topic of growing significance to green criminology - the harmful effects of mining on local communities and the environment (Ruggiero and South 2013; White 2013a). While mining has long been recognised as an agent of environmental harm (White 2013a), less recognised is that its global expansion also has harmful effects on localised patterns of violence, work and community life in mining towns. Australia provides an excellent case study for exploring some of these mining impacts.

A process mining-based investigation of adverse events in care processes

This paper proposes the Clinical Pathway Analysis Method (CPAM) approach that enables the extraction of valuable organisational and medical information on past clinical pathway executions from the event logs of healthcare information systems. The method deals with the complexity of real-world clinical pathways by introducing a perspective-based segmentation of the date-stamped event log. CPAM enables the clinical pathway analyst to effectively and efficiently acquire a profound insight into the clinical pathways. By comparing the specific medical conditions of patients with the factors used for characterising the different clinical pathway variants, the medical expert can identify the best therapeutic option. Process mining-based analytics enables the acquisition of valuable insights into clinical pathways, based on the complete audit traces of previous clinical pathway instances. Additionally, the methodology is suited to assess guideline compliance and analyse adverse events. Finally, the methodology provides support for eliciting tacit knowledge and providing treatment selection assistance.

A data mining approach for fault diagnosis: An application of anomaly detection algorithm

Rolling-element bearing failures are the most frequent problems in rotating machinery, which can be catastrophic and cause major downtime. Hence, providing advance failure warning and precise fault detection in such components are pivotal and cost-effective. The vast majority of past research has focused on signal processing and spectral analysis for fault diagnostics in rotating components. In this study, a data mining approach using a machine learning technique called anomaly detection (AD) is presented. This method employs classification techniques to discriminate between defect examples. Two features, kurtosis and Non-Gaussianity Score (NGS), are extracted to develop anomaly detection algorithms. The performance of the developed algorithms was examined through real data from a test to failure bearing. Finally, the application of anomaly detection is compared with one of the popular methods called Support Vector Machine (SVM) to investigate the sensitivity and accuracy of this approach and its ability to detect the anomalies in early stages.

The case for “n«all”: Why the Big Data revolution will probably happen differently in the mining sector

Big Data and predictive analytics have received significant attention from the media and academic literature throughout the past few years, and it is likely that these emerging technologies will materially impact the mining sector. This short communication argues, however, that these technological forces will probably unfold differently in the mining industry than they have in many other sectors because of significant differences in the marginal cost of data capture and storage. To this end, we offer a brief overview of what Big Data and predictive analytics are, and explain how they are bringing about changes in a broad range of sectors. We discuss the “N=all” approach to data collection being promoted by many consultants and technology vendors in the marketplace but, by considering the economic and technical realities of data acquisition and storage, we then explain why a “n « all” data collection strategy probably makes more sense for the mining sector. Finally, towards shaping the industry’s policies with regards to technology-related investments in this area, we conclude by putting forward a conceptual model for leveraging Big Data tools and analytical techniques that is a more appropriate fit for the mining sector.

Enhancement of relevant features for text mining

With the explosion of information resources, there is an imminent need to understand interesting text features or topics in massive text information. This thesis proposes a theoretical model to accurately weight specific text features, such as patterns and n-grams. The proposed model achieves impressive performance in two data collections, Reuters Corpus Volume 1 (RCV1) and Reuters 21578.

Using global formulary apportionment for international profit allocation: The case of Indonesia's mining industry

My thesis examined an alternative approach, referred to as the unitary taxation approach to the allocation of profit, which arises from the notion that as a multinational group exists as a single economic entity, it should be taxed as one taxable unit. The plausibility of a unitary taxation regime achieving international acceptance and agreement is highly contestable due to its implementation issues, and economic and political feasibility. Using a case-study approach focusing on Freeport-McMoRan and Rio Tinto's mining operations in Indonesia, this thesis compares both tax regimes against the criteria for a good tax system - equity, efficiency, neutrality and simplicity. This thesis evaluates key issues that arise when implementing a unitary taxation approach with formulary apportionment based on the context of mining multinational firms in Indonesia.

Business process performance mining with staged process flows

Existing process mining techniques provide summary views of the overall process performance over a period of time, allowing analysts to identify bottlenecks and associated performance issues. However, these tools are not de- signed to help analysts understand how bottlenecks form and dissolve over time nor how the formation and dissolution of bottlenecks – and associated fluctua- tions in demand and capacity – affect the overall process performance. This paper presents an approach to analyze the evolution of process performance via a notion of Staged Process Flow (SPF). An SPF abstracts a business process as a series of queues corresponding to stages. The paper defines a number of stage character- istics and visualizations that collectively allow process performance evolution to be analyzed from multiple perspectives. The approach has been implemented in the ProM process mining framework. The paper demonstrates the advantages of the SPF approach over state-of-the-art process performance mining tools using two real-life event logs publicly available.

Coastal Wetlands Resources Investigation of the Burdekin Delta for declaration as fisheries reserves. Report to Ocean Rescue 2000

A project to investigate the coastal wetland resources of the Burdekin Delta, north Queensland, was undertaken as part of the long-term assessment of the coastal fisheries resources of Queensland. Extending from November 1993 to May 1995, fieldwork was undertaken in November 1993 and August 1994. The scope of the coastal wetlands resources investigation of the Burdekin Delta for declaration as a Fish Habitat Area was: 1. To document and map the marine wetland vegetation communities in the Burdekin River delta. 2. To document levels of existing disturbance to wetlands, existing recreational and commercial fisheries resources, and existing fishing activities. 3. To evaluate the conservation values of the areas investigated from the viewpoint of fisheries productivity and as habitat for important/threatened species. 4. To initiate Fish Habitat Area declaration under Section 120 of the Queensland Fisheries Act 1994 with formal consultation to all stakeholders. This report concentrates on Points 1 and 3, the documentation of the marine wetland vegetation communities and the evaluation of conservation values from a fisheries viewpoint. Dataset URL Link: Queensland Coastal Wetlands Resources Mapping data. [Dataset]

Declining soil phosphorus reserves on sustainable agricultural production systems

PhD scholarship investigating the relative sensitivity of nitrogen fixation in adapted grain and ley legume species to low soil phosphorus.

Cat's claw creeper leaf-mining jewel beetle Hylaeogena jureceki Obenberger (Coleoptera: Buprestidae), a host-specific biological control agent for Dolichandra unguis-cati (Bignoniaceae) in Australia

Cat's claw creeper, Dolichandra unguis-cati (L.) L.G. Lohman (syn: Macfadyena unguis-cati (L.) A.H. Gentry) (Bignoniaceae), a major environmental weed in Queensland and New South Wales, is a Weed of National Significance and an approved target for biological control. A leaf-mining jewel beetle, Hylaeogena jureceki Obenberger (Coleoptera: Buprestidae), first collected in 2002 from D. unguis-cati in Brazil and Argentina, was imported from South Africa into a quarantine facility in Brisbane in 2009 for host-specificity testing. H. jureceki adults chew holes in leaves and lay eggs on leaf margins and the emerging larvae mine within the leaves of D. unguis-cati. The generation time (egg to adult) of H. jureceki under quarantine conditions was 55.4 ± 0.2 days. Host-specificity trials conducted in Australia on 38 plant species from 11 families supplement and support South African studies which indicated that H. jureceki is highly host-specific and does not pose a risk to any non-target plant species in Australia. In no-choice tests, adults survived significantly longer (>32 weeks) on D. unguis-cati than on non-target test plant species (<3 weeks). Oviposition occurred on D. unguis-cati and one non-target test plant species, Citharexylum spinosum (Verbenaceae), but no larval development occurred on the latter species. In choice tests involving D. unguis-cati, C. spinosum and Avicennia marina (Avicenniaceae), feeding and oviposition were evident only on D. unguis-cati. The insect was approved for field release in Australia in May 2012.

Phosphorus in agricultural soils of Finland - characterization of reserves and retention in mineral soil profiles

An overwhelming majority of all the research on soil phosphorus (P) has been carried out with soil samples taken from the surface soils only, and our understanding of the forms and the reactions of P at a soil profile scale is based on few observations. In Finland, the interest in studying the P in complete soil profiles has been particularly small because of the lack of tradition in studying soil genesis, morphology, or classification. In this thesis, the P reserves and the retention of orthophosphate phosphorus (PO4-P) were examined in four cultivated mineral soil profiles in Finland (three Inceptisols and one Spodosol). The soils were classified according to the U.S. Soil Taxonomy and soil samples were taken from the genetic horizons in the profiles. The samples were analyzed for total P concentration, Chang and Jackson P fractions, P sorption properties, concentrations of water-extractable P, and for concentrations of oxalate-extractable Al and Fe. Theoretical P sorption capacities and degrees of P saturation were calculated with the data from the oxalate-extractions and the P fractionations. The studied profiles can be divided into sections with clearly differing P characteristics by their master horizons Ap, B and C. The C (or transitional BC) horizons below an approximate depth of 70 cm were dominated by, assumingly apatitic, H2SO4-soluble P. The concentration of total P in the C horizons ranged from 729 to 810 mg kg-1. In the B horizons between the depths of 30 and 70 cm, a significant part of the primary acid-soluble P has been weathered and transformed to secondary P forms. A mean weathering rate of the primary P in the soils was estimated to vary between 230 and 290 g ha-1 year-1. The degrees of P saturation in the B and C horizons were smaller than 7%, and the solubility of PO4-P was negligible. The P conditions in the Ap horizons differed drastically from those in the subsurface horizons. The high concentrations of total P (689-1870 mg kg-1) in the Ap horizons are most likely attributable to long-term cultivation with positive P balances. A significant proportion of the P in the Ap horizons occurred in the NH4F- and NaOH-extractable forms and as organic P. These three P pools, together with the concentrations of oxalate-extractable Al and Fe, seem to control the dynamics of PO4-P in the soils. The degrees of P saturation in the Ap horizons were greater (8-36%) than in the subsurface horizons. This was also reflected in the sorption experiments: Only the Ap horizons were able to maintain elevated PO4-P concentrations in the solution phase − all the subsoil horizons acted as sinks for PO4-P. Most of the available sorption capacity in the soils is located in the B horizons. The results suggest that this capacity could be utilized in reducing the losses of soluble P from excessively fertilized soils by mixing highly sorptive material from the B horizons with the P-enriched surface soil. The drastic differences in the P characteristics observed between adjoining horizons have to be taken into consideration when conducting soil sampling. Sampling of subsoils has to be made according to the genetic horizons or at small depth increments. Otherwise, contrasting materials are likely to be mixed in the same sample; and the results of such samples are not representative of any material present in the studied profile. Air-drying of soil samples was found to alter the results of the sorption experiments and the water extractions. This indicates that the studies on the most labile P forms in soil should be carried out with moist samples.