129 resultados para Many-To-One Matching Market
Resumo:
A people-to-people matching system (or a match-making system) refers to a system in which users join with the objective of meeting other users with the common need. Some real-world examples of these systems are employer-employee (in job search networks), mentor-student (in university social networks), consume-to-consumer (in marketplaces) and male-female (in an online dating network). The network underlying in these systems consists of two groups of users, and the relationships between users need to be captured for developing an efficient match-making system. Most of the existing studies utilize information either about each of the users in isolation or their interaction separately, and develop recommender systems using the one form of information only. It is imperative to understand the linkages among the users in the network and use them in developing a match-making system. This study utilizes several social network analysis methods such as graph theory, small world phenomenon, centrality analysis, density analysis to gain insight into the entities and their relationships present in this network. This paper also proposes a new type of graph called “attributed bipartite graph”. By using these analyses and the proposed type of graph, an efficient hybrid recommender system is developed which generates recommendation for new users as well as shows improvement in accuracy over the baseline methods.
Resumo:
Despite the significant recent growth in research relating to instrumental, vocal and composition tuition in higher education, little is known about the diversity of approaches that characterise one-to-one teaching in the Conservatoire, and what counts as optimal practice for educating 21st-century musicians. Through analysis of video-recorded one-to-one lessons that draws on a ‘bottom up’ methodology for characterising pedagogical practices (Taylor, 2012; Taylor et al, 2012), this paper provides empirical evidence about the nature of one-to-one pedagogy in one Australian institution. The research aims (1) to enable a better understanding of current one-to-one conservatoire teaching; and (2) to build and improve upon existing teaching practice using authentic insights gained through systematic investigation. The authors hope the research will lead to a better understanding of the diversity and efficacy of the pedagogical practice within the specific context in which the study was conducted, and beyond, to Conservatoire pedagogy generally.
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Despite significant investment in school one-to-one device programs, little is known about which aspects of program implementation work and why. Through a comparison of two implementation models, adopter-diffusion and saturation, and using existing data from the One Laptop per Child Australia laptop program, we explored how factors of implementation may affect device diffusion, learning and educational outcomes, and program sustainability in schools. In this article we argue that more focused research into implementation of one-to-one device programs, moving beyond comparisons of “devices versus without devices,” is needed to provide reliable data to inform future program funding and advance this area of research.
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The primary aim of this descriptive exploration of scientists’ life cycle award patterns is to evaluate whether awards breed further awards and identify researcher experiences after reception of the Nobel Prize. To achieve this goal, we collected data on the number of awards received each year for 50 years before and after Nobel Prize reception by all 1901–2000 Nobel laureates in physics, chemistry, and medicine or physiology. Our results indicate an increasing rate of awards before Nobel reception, reaching the summit precisely in the year of the Nobel Prize. After this pinnacle year, awards drop sharply. This result is confirmed by separate analyses of three different disciplines and by a random-effects negative binomial regression model. Such an effect, however, does not emerge for more recent Nobel laureates (1971–2000). In addition, Nobelists in medicine or physiology generate more awards shortly before and after prize reception, whereas laureates in chemistry attract more awards as time progresses.
Resumo:
This research paper reports on phase one of an investigation of video recorded intensive one-to-one teaching interactions with 6–7-year-old students who were in their second year of schooling in Australia and identified by the their teacher as low attaining in early number. The two-phased study from which this paper emerges was originally conducted in 1998 as part of my Bachelor of Teaching Honours (Research) program at Southern Cross University Lismore, New South Wales. That study identified teaching interactions particularly suited to one-to-one teaching in the Maths Recovery Program, a program designed for these students who were at risk of failure in early number. Since that time a great deal has not changed with limited literature available that comprehensively reports on teaching interactions in intensive one-to-one settings. Revisiting the original study is considered timely given the increasing number of withdrawal and intensive programs now funded and adopted by schools and yet, rarely reported on in terms of the effectiveness of the teaching interactions that occur in such settings. This paper then presents a discussion of a preliminary series of teaching interactions that either positively and or negatively influence an intensive one-to-one teaching and learning setting
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The idea of extracting knowledge in process mining is a descendant of data mining. Both mining disciplines emphasise data flow and relations among elements in the data. Unfortunately, challenges have been encountered when working with the data flow and relations. One of the challenges is that the representation of the data flow between a pair of elements or tasks is insufficiently simplified and formulated, as it considers only a one-to-one data flow relation. In this paper, we discuss how the effectiveness of knowledge representation can be extended in both disciplines. To this end, we introduce a new representation of the data flow and dependency formulation using a flow graph. The flow graph solves the issue of the insufficiency of presenting other relation types, such as many-to-one and one-to-many relations. As an experiment, a new evaluation framework is applied to the Teleclaim process in order to show how this method can provide us with more precise results when compared with other representations.
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In this paper we tackle the problem of finding an efficient signature verification scheme when the number of signatures is signi.- cantly large and the verifier is relatively weak. In particular, we tackle the problem of message authentication in many-to-one communication networks known as concast communication. The paper presents three signature screening algorithms for a variant of ElGamal-type digital signatures. The cost for these schemes is n applications of hash functions, 2n modular multiplications, and n modular additions plus the verification of one digital signature, where n is the number of signatures. The paper also presents a solution to the open problem of finding a fast screening signature for non-RSA digital signature schemes.
Resumo:
Generally wireless sensor networks rely of many-to-one communication approach for data gathering. This approach is extremely susceptible to sinkhole attack, where an intruder attracts surrounding nodes with unfaithful routing information, and subsequently presents selective forwarding or change the data that carry through it. A sinkhole attack causes an important threat to sensor networks and it should be considered that the sensor nodes are mostly spread out in open areas and of weak computation and battery power. In order to detect the intruder in a sinkhole attack this paper suggests an algorithm which firstly finds a group of suspected nodes by analyzing the consistency of data. Then, the intruder is recognized efficiently in the group by checking the network flow information. The proposed algorithm's performance has been evaluated by using numerical analysis and simulations. Therefore, accuracy and efficiency of algorithm would be verified.
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The rank transform is a non-parametric technique which has been recently proposed for the stereo matching problem. The motivation behind its application to the matching problem is its invariance to certain types of image distortion and noise, as well as its amenability to real-time implementation. This paper derives an analytic expression for the process of matching using the rank transform, and then goes on to derive one constraint which must be satisfied for a correct match. This has been dubbed the rank order constraint or simply the rank constraint. Experimental work has shown that this constraint is capable of resolving ambiguous matches, thereby improving matching reliability. This constraint was incorporated into a new algorithm for matching using the rank transform. This modified algorithm resulted in an increased proportion of correct matches, for all test imagery used.
Resumo:
This paper examines whether innovation in market design can address persistent problems of housing choice and affordability in the ageing inner and middle suburbs of Australian cities. Despite policy consensus that urban intensification of these low density, ‘greyfield’ areas should be able to deliver positive social, economic and environmental outcomes, existing models of development have not increased housing stock or delivered adequate gains in sustainability, affordability or diversity of dwellings in greyfield localities. We argue that application of smart market and matching market principles to the supply of multi-unit housing can unlock land, reduce development costs and improve design.
Resumo:
The continuous growth of the XML data poses a great concern in the area of XML data management. The need for processing large amounts of XML data brings complications to many applications, such as information retrieval, data integration and many others. One way of simplifying this problem is to break the massive amount of data into smaller groups by application of clustering techniques. However, XML clustering is an intricate task that may involve the processing of both the structure and the content of XML data in order to identify similar XML data. This research presents four clustering methods, two methods utilizing the structure of XML documents and the other two utilizing both the structure and the content. The two structural clustering methods have different data models. One is based on a path model and other is based on a tree model. These methods employ rigid similarity measures which aim to identifying corresponding elements between documents with different or similar underlying structure. The two clustering methods that utilize both the structural and content information vary in terms of how the structure and content similarity are combined. One clustering method calculates the document similarity by using a linear weighting combination strategy of structure and content similarities. The content similarity in this clustering method is based on a semantic kernel. The other method calculates the distance between documents by a non-linear combination of the structure and content of XML documents using a semantic kernel. Empirical analysis shows that the structure-only clustering method based on the tree model is more scalable than the structure-only clustering method based on the path model as the tree similarity measure for the tree model does not need to visit the parents of an element many times. Experimental results also show that the clustering methods perform better with the inclusion of the content information on most test document collections. To further the research, the structural clustering method based on tree model is extended and employed in XML transformation. The results from the experiments show that the proposed transformation process is faster than the traditional transformation system that translates and converts the source XML documents sequentially. Also, the schema matching process of XML transformation produces a better matching result in a shorter time.
Resumo:
Non-use values (i.e. economic values assigned by individuals to ecosystem goods and services unrelated to current or future uses) provide one of the most compelling incentives for the preservation of ecosystems and biodiversity. Assessing the non-use values of non-users is relatively straightforward using stated preference methods, but the standard approaches for estimating non-use values of users (stated decomposition) have substantial shortcomings which undermine the robustness of their results. In this paper, we propose a pragmatic interpretation of non-use values to derive estimates that capture their main dimensions, based on the identification of a willingness to pay for ecosystem protection beyond one's expected life. We empirically test our approach using a choice experiment conducted on coral reef ecosystem protection in two coastal areas in New Caledonia with different institutional, cultural, environmental and socio-economic contexts. We compute individual willingness to pay estimates, and derive individual non-use value estimates using our interpretation. We find that, a minima, estimates of non-use values may comprise between 25 and 40% of the mean willingness to pay for ecosystem preservation, less than has been found in most studies.