415 resultados para Event Log Mining


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Automated process discovery techniques aim at extracting models from information system logs in order to shed light into the business processes supported by these systems. Existing techniques in this space are effective when applied to relatively small or regular logs, but otherwise generate large and spaghetti-like models. In previous work, trace clustering has been applied in an attempt to reduce the size and complexity of automatically discovered process models. The idea is to split the log into clusters and to discover one model per cluster. The result is a collection of process models -- each one representing a variant of the business process -- as opposed to an all-encompassing model. Still, models produced in this way may exhibit unacceptably high complexity. In this setting, this paper presents a two-way divide-and-conquer process discovery technique, wherein the discovered process models are split on the one hand by variants and on the other hand hierarchically by means of subprocess extraction. The proposed technique allows users to set a desired bound for the complexity of the produced models. Experiments on real-life logs show that the technique produces collections of models that are up to 64% smaller than those extracted under the same complexity bounds by applying existing trace clustering techniques.

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This study uses borehole geophysical log data of sonic velocity and electrical resistivity to estimate permeability in sandstones in the northern Galilee Basin, Queensland. The prior estimates of permeability are calculated according to the deterministic loglog linear empirical correlations between electrical resistivity and measured permeability. Both negative and positive relationships are influenced by the clay content. The prior estimates of permeability are updated in a Bayesian framework for three boreholes using both the cokriging (CK) method and a normal linear regression (NLR) approach to infer the likelihood function. The results show that the mean permeability estimated from the CK-based Bayesian method is in better agreement with the measured permeability when a fairly apparent linear relationship exists between the logarithm of permeability and sonic velocity. In contrast, the NLR-based Bayesian approach gives better estimates of permeability for boreholes where no linear relationship exists between logarithm permeability and sonic velocity.

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It is a big challenge to find useful associations in databases for user specific needs. The essential issue is how to provide efficient methods for describing meaningful associations and pruning false discoveries or meaningless ones. One major obstacle is the overwhelmingly large volume of discovered patterns. This paper discusses an alternative approach called multi-tier granule mining to improve frequent association mining. Rather than using patterns, it uses granules to represent knowledge implicitly contained in databases. It also uses multi-tier structures and association mappings to represent association rules in terms of granules. Consequently, association rules can be quickly accessed and meaningless association rules can be justified according to the association mappings. Moreover, the proposed structure is also an precise compression of patterns which can restore the original supports. The experimental results shows that the proposed approach is promising.

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A value-shift began to influence global political thinking in the late 20th century, characterised by recognition of the need for environmentally, socially and culturally sustainable resource development. This shift entailed a move away from thinking of ‘nature’ and ‘culture’ as separate entities – the former existing to serve the latter – toward the possibility of embracing the intrinsic worth of the nonhuman world. Cultural landscape theory recognises ‘nature’ as at once both ‘natural’, and a ‘cultural’ construct. As such, it may offer a framework through which to progress in the quest for ‘sustainable development’. This study makes a contribution to this quest by asking whether contemporary developments in cultural landscape theory can contribute to rehabilitation strategies for Australian open-cut coal mining landscapes. The answer is ‘yes’. To answer the research question, a flexible, ‘emergent’ methodological approach has been used, resulting in the following outcomes. A thematic historical overview of landscape values and resource development in Australia post-1788, and a review of cultural landscape theory literature, contribute to the formation of a new theoretical framework: Reconnecting the Interrupted Landscape. This framework establishes a positive answer to the research question. It also suggests a method of application within the Australian open-cut coal mining landscape, a highly visible exemplar of the resource development landscape. This method is speculatively tested against the rehabilitation strategy of an operating open-cut coal mine, concluding with positive recommendations to the industry, and to government.

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Linking Karumba: Creating Sustainable Connections This exhibition showcases the work of 3rd -4th year undergraduate landscape architecture, architecture, Industrial Design, Environmental Engineering, Civil Engineering students in response to issues of sustainability in the Gulf of Carpentaria town of Karumba. It presented the work to the Karumba and Carpentaria Shire community. 16 students and four staff set off on a 2488km journey to undertake the first half of the Carpentaria Project: a fortnight-long strategic planning project entitled Linking Karumba to encourage social, economic, environmental and cultural linkages across the town. Karumba, along with the nearby town of Normanton, is one of Queensland’s most remote settlements. Its economy is based on fishing, tourism, and mining. It has two centres, 2.5km apart by river, or 9km by road. This physical disconnect was identified by Carpentaria Shire Council (CSC) and the Karumba Progress Association (KPA) as a source of socio-cultural disconnection, which formed the basis of our project brief. Student designs were highly responsive to the character of Karumba’s culture and environment, indicating remarkable levels of immersion, and attracting $830 000 in Qld. state government funding for implementation. The Exhibition Four groups of four students produced four strategic planning and design options toward this future: Make the Switch: Alice Anonuevo, Michael Marriott, Carla Priestley & Grant Harvey Realigning the Systems: Claudia Bergs, Rebecca Stephens, Anna Coulson & Lois Kerrigan Diversification of Experience: Rebecca North, Kyle Bush, Debra Sullivan & Jenna Green The River is the Main Street: Ashley Nicholson, Monica Kuiken, Dean Bowen & Bill Schild

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QUT Linking Karumba Project This exhibition showcases the work of 3rd -4th year undergraduate landscape architecture, architecture, Industrial Design, Environmental Engineering, Civil Engineering students in response to issues of sustainability in the Gulf of Carpentaria town of Karumba. It presented the final, polished set of work to the Karumba and Carpentaria Shire community, following revisions in line with feedback from the 2008 exhibition. 16 students and four staff set off on a 2488km journey to undertake the first half of the Carpentaria Project: a fortnight-long strategic planning project entitled Linking Karumba to encourage social, economic, environmental and cultural linkages across the town. Karumba, along with the nearby town of Normanton, is one of Queensland’s most remote settlements. Its economy is based on fishing, tourism, and mining. It has two centres, 2.5km apart by river, or 9km by road. This physical disconnect was identified by Carpentaria Shire Council (CSC) and the Karumba Progress Association (KPA) as a source of socio-cultural disconnection, which formed the basis of our project brief. Student designs were highly responsive to the character of Karumba’s culture and environment, indicating remarkable levels of immersion, and attracting $830 000 in Qld. state government funding for implementation. The Exhibition Four groups of four students produced four strategic planning and design options toward this future: Make the Switch: Alice Anonuevo, Michael Marriott, Carla Priestley & Grant Harvey Realigning the Systems: Claudia Bergs, Rebecca Stephens, Anna Coulson & Lois Kerrigan Diversification of Experience: Rebecca North, Kyle Bush, Debra Sullivan & Jenna Green The River is the Main Street: Ashley Nicholson, Monica Kuiken, Dean Bowen & Bill Schild

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Atmospheric ultrafine particles play an important role in affecting human health, altering climate and degrading visibility. Numerous studies have been conducted to better understand the formation process of these particles, including field measurements, laboratory chamber studies and mathematical modeling approaches. Field studies on new particle formation found that formation processes were significantly affected by atmospheric conditions, such as the availability of particle precursors and meteorological conditions. However, those studies were mainly carried out in rural areas of the northern hemisphere and information on new particle formation in urban areas, especially those in subtropical regions, is limited. In general, subtropical regions display a higher level of solar radiation, along with stronger photochemical reactivity, than those regions investigated in previous studies. However, based on the results of these studies, the mechanisms involved in the new particle formation process remain unclear, particularly in the Southern Hemisphere. Therefore, in order to fill this gap in knowledge, a new particle formation study was conducted in a subtropical urban area in the Southern Hemisphere during 2009, which measured particle size distribution in different locations in Brisbane, Australia. Characterisation of nucleation events was conducted at the campus building of the Queensland University of Technology (QUT), located in an urban area of Brisbane. Overall, the annual average number concentrations of ultrafine, Aitken and nucleation mode particles were found to be 9.3 x 103, 3.7 x 103 and 5.6 x 103 cm-3, respectively. This was comparable to levels measured in urban areas of northern Europe, but lower than those from polluted urban areas such as the Yangtze River Delta, China and Huelva and Santa Cruz de Tenerife, Spain. Average particle number concentration (PNC) in the Brisbane region did not show significant seasonal variation, however a relatively large variation was observed during the warmer season. Diurnal variation of Aitken and nucleation mode particles displayed different patterns, which suggested that direct vehicle exhaust emissions were a major contributor of Aitken mode particles, while nucleation mode particles originated from vehicle exhaust emissions in the morning and photochemical production at around noon. A total of 65 nucleation events were observed during 2009, in which 40 events were classified as nucleation growth events and the remainder were nucleation burst events. An interesting observation in this study was that all nucleation growth events were associated with vehicle exhaust emission plumes, while the nucleation burst events were associated with industrial emission plumes from an industrial area. The average particle growth rate for nucleation events was found to be 4.6 nm hr-1 (ranging from 1.79-7.78 nm hr-1), which is comparable to other urban studies conducted in the United States, while monthly particle growth rates were found to be positively related to monthly solar radiation (r = 0.76, p <0.05). The particle growth rate values reported in this work are the first of their kind to be reported for the subtropical urban area of Australia. Furthermore, the influence of nucleation events on PNC within the urban airshed was also investigated. PNC was simultaneously measured at urban (QUT), roadside (Woolloongabba) and semi-urban (Rocklea) sites in Brisbane during 2009. Total PNC at these sites was found to be significantly affected by regional nucleation events. The relative fractions of PNC to total daily PNC observed at QUT, Woolloongabba and Rocklea were found to be 12%, 9% and 14%, respectively, during regional nucleation events. These values were higher than those observed as a result of vehicle exhaust emissions during weekday mornings, which ranged from 5.1-5.5% at QUT and Woolloongabba. In addition, PNC in the semi-urban area of Rocklea increased by a factor of 15.4 when it was upwind from urban pollution sources under the influence of nucleation burst events. Finally, we investigated the influence of sulfuric acid on new particle formation in the study region. A H2SO4 proxy was calculated by using [SO2], solar radiation and particle condensation sink data to represent the new particle production strength for the urban, roadside and semi-urban areas of Brisbane during the period June-July of 2009. The temporal variations of the H2SO4 proxies and the nucleation mode particle concentration were found to be in phase during nucleation events in the urban and roadside areas. In contrast, the peak of proxy concentration occurred 1-2 hr prior to the observed peak in nucleation mode particle concentration at the downwind semi-urban area of Brisbane. A moderate to strong linear relationship was found between the proxy and the freshly formed particles, with r2 values of 0.26-0.77 during the nucleation events. In addition, the log[H2SO4 proxy] required to produce new particles was found to be ~1.0 ppb Wm-2 s and below 0.5 ppb Wm-2 s for the urban and semi-urban areas, respectively. The particle growth rates were similar during nucleation events at the three study locations, with an average value of 2.7 ± 0.5 nm hr-1. This result suggested that a similar nucleation mechanism dominated in the study region, which was strongly related to sulphuric acid concentration, however the relationship between the proxy and PNC was poor in the semi-urban area of Rocklea. This can be explained by the fact that the nucleation process was initiated upwind of the site and the resultant particles were transported via the wind to Rocklea. This explanation is also supported by the higher geometric mean diameter value observed for particles during the nucleation event and the time lag relationship between the H2SO4 proxy and PNC observed at Rocklea. In summary, particle size distribution was continuously measured in a subtropical urban area of southern hemisphere during 2009, the findings from which formed the first particle size distribution dataset in the study region. The characteristics of nucleation events in the Brisbane region were quantified and the properties of the nucleation growth and burst events are discussed in detail using a case studies approach. To further investigate the influence of nucleation events on PNC in the study region, PNC was simultaneously measured at three locations to examine the spatial variation of PNC during the regional nucleation events. In addition, the impact of upwind urban pollution on the downwind semi-urban area was quantified during these nucleation events. Sulphuric acid was found to be an important factor influencing new particle formation in the urban and roadside areas of the study region, however, a direct relationship with nucleation events at the semi-urban site was not observed. This study provided an overview of new particle formation in the Brisbane region, and its influence on PNC in the surrounding area. The findings of this work are the first of their kind for an urban area in the southern hemisphere.

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Understanding network traffic behaviour is crucial for managing and securing computer networks. One important technique is to mine frequent patterns or association rules from analysed traffic data. On the one hand, association rule mining usually generates a huge number of patterns and rules, many of them meaningless or user-unwanted; on the other hand, association rule mining can miss some necessary knowledge if it does not consider the hierarchy relationships in the network traffic data. Aiming to address such issues, this paper proposes a hybrid association rule mining method for characterizing network traffic behaviour. Rather than frequent patterns, the proposed method generates non-similar closed frequent patterns from network traffic data, which can significantly reduce the number of patterns. This method also proposes to derive new attributes from the original data to discover novel knowledge according to hierarchy relationships in network traffic data and user interests. Experiments performed on real network traffic data show that the proposed method is promising and can be used in real applications. Copyright2013 John Wiley & Sons, Ltd.

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This report describes the available functionality and use of the ClusterEval evaluation software. It implements novel and standard measures for the evaluation of cluster quality. This software has been used at the INEX XML Mining track and in the MediaEval Social Event Detection task.

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The rapid growth of visual information on Web has led to immense interest in multimedia information retrieval (MIR). While advancement in MIR systems has achieved some success in specific domains, particularly the content-based approaches, general Web users still struggle to find the images they want. Despite the success in content-based object recognition or concept extraction, the major problem in current Web image searching remains in the querying process. Since most online users only express their needs in semantic terms or objects, systems that utilize visual features (e.g., color or texture) to search images create a semantic gap which hinders general users from fully expressing their needs. In addition, query-by-example (QBE) retrieval imposes extra obstacles for exploratory search because users may not always have the representative image at hand or in mind when starting a search (i.e. the page zero problem). As a result, the majority of current online image search engines (e.g., Google, Yahoo, and Flickr) still primarily use textual queries to search. The problem with query-based retrieval systems is that they only capture users’ information need in terms of formal queries;; the implicit and abstract parts of users’ information needs are inevitably overlooked. Hence, users often struggle to formulate queries that best represent their needs, and some compromises have to be made. Studies of Web search logs suggest that multimedia searches are more difficult than textual Web searches, and Web image searching is the most difficult compared to video or audio searches. Hence, online users need to put in more effort when searching multimedia contents, especially for image searches. Most interactions in Web image searching occur during query reformulation. While log analysis provides intriguing views on how the majority of users search, their search needs or motivations are ultimately neglected. User studies on image searching have attempted to understand users’ search contexts in terms of users’ background (e.g., knowledge, profession, motivation for search and task types) and the search outcomes (e.g., use of retrieved images, search performance). However, these studies typically focused on particular domains with a selective group of professional users. General users’ Web image searching contexts and behaviors are little understood although they represent the majority of online image searching activities nowadays. We argue that only by understanding Web image users’ contexts can the current Web search engines further improve their usefulness and provide more efficient searches. In order to understand users’ search contexts, a user study was conducted based on university students’ Web image searching in News, Travel, and commercial Product domains. The three search domains were deliberately chosen to reflect image users’ interests in people, time, event, location, and objects. We investigated participants’ Web image searching behavior, with the focus on query reformulation and search strategies. Participants’ search contexts such as their search background, motivation for search, and search outcomes were gathered by questionnaires. The searching activity was recorded with participants’ think aloud data for analyzing significant search patterns. The relationships between participants’ search contexts and corresponding search strategies were discovered by Grounded Theory approach. Our key findings include the following aspects: - Effects of users' interactive intents on query reformulation patterns and search strategies - Effects of task domain on task specificity and task difficulty, as well as on some specific searching behaviors - Effects of searching experience on result expansion strategies A contextual image searching model was constructed based on these findings. The model helped us understand Web image searching from user perspective, and introduced a context-aware searching paradigm for current retrieval systems. A query recommendation tool was also developed to demonstrate how users’ query reformulation contexts can potentially contribute to more efficient searching.

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Crude petroleum remains the single most imported commodity into Australia and is sourced from a number of countries around the world (Department of Foreign Affairs and Trade (DFAT), 2011a). While interest in crude petroleum is widespread, in recent years Australia's focus has been drawn to the continent of Africa, where increased political stability, economic recovery and an improved investment climate has made one of the largest oil reserves in the world increasingly more attractive. Despite improvement across the continent, there remain a number of risks which have the potential to significantly damage Australia's economic interests in the petroleum sector,including government policies and legislation, corruption and conflict. The longest exporters of crude petroleum products to Australia – Nigeria and Libya – have been subject to these factors in recent years and, accordingly, are the focus of this paper. Once identified, the impact of political instability, conflict, government corruption and other risk factors to Australia's mining interests within these countries is examined, and efforts to manage such risks are discussed.

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Process-aware information systems (PAISs) can be configured using a reference process model, which is typically obtained via expert interviews. Over time, however, contextual factors and system requirements may cause the operational process to start deviating from this reference model. While a reference model should ideally be updated to remain aligned with such changes, this is a costly and often neglected activity. We present a new process mining technique that automatically improves the reference model on the basis of the observed behavior as recorded in the event logs of a PAIS. We discuss how to balance the four basic quality dimensions for process mining (fitness, precision, simplicity and generalization) and a new dimension, namely the structural similarity between the reference model and the discovered model. We demonstrate the applicability of this technique using a real-life scenario from a Dutch municipality.

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This thesis improves the process of recommending people to people in social networks using new clustering algorithms and ranking methods. The proposed system and methods are evaluated on the data collected from a real life social network. The empirical analysis of this research confirms that the proposed system and methods achieved improvements in the accuracy and efficiency of matching and recommending people, and overcome some of the problems that social matching systems usually suffer.