Web services are commonly perceived as an environment of both offering opportunities and threats. In this environment, one way to minimize threats is to use reputation evaluation, which can be computed, for example, t...
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Web services are commonly perceived as an environment of both offering opportunities and threats. In this environment, one way to minimize threats is to use reputation evaluation, which can be computed, for example, through transaction feedback. However, the current feedback-based approach is inaccurate and ineffective because of its inner limitations （e.g., feedback quality problem）. As the main source of feedback, the qualities of existing on-line reviews are often varied greatly from low to high, the main reasons include： （1） they have no standard expression formats, （2） dishonest comments may exist among these reviews due to malicious attacking. Up to present, the quality problem of review has not been well solved, which greatly degrades their importance on service reputation evaluation. Therefore, we firstly present a novel evaluation approach for review quality in terms of multiple metrics. Then, we make a further improvement in service reputation evaluation based on those filtered reviews. Experimental results show the effectiveness and efficiency of our proposed approach compared with the naive feedback-based approaches.
SimRank is a well-known algorithm for similarity calculation based on object-to-object relationship. However, it suffers from high computation cost. Inthis paper, we find that the convergence behavior of different obj...
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ISBN:
(纸本)9783642008863
SimRank is a well-known algorithm for similarity calculation based on object-to-object relationship. However, it suffers from high computation cost. Inthis paper, we find that the convergence behavior of different object pairs is different when we use SimRank to compute the similarity of objects. Many similarity scores converge fast, while others need more time before convergence. Based on this observation, we propose an adaptive method called Adaptive-SimRank to speed up similarity calculation. Using this method, we don't need to recalculate those converged pairs' similarity. The experiments conducted on web datasets and synthetic dataset show that our new method can reduce the running time by nearly 35%.
Ubiquitous computing (ubicomp), as envisaged by Weiser [22], is heavily user-centric and largely concerned with applications specifically designed to meet end-user needs. Sensor populated ubicomp environments differen...
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ISBN:
(纸本)9789639799455
Ubiquitous computing (ubicomp), as envisaged by Weiser [22], is heavily user-centric and largely concerned with applications specifically designed to meet end-user needs. Sensor populated ubicomp environments differentiate these applications from existing mobile and distributed systems through context awareness. For the system developer, the problems of heterogeneity and scalability are felt most keenly when designing this adaptive behaviour. A context-aware ubicomp system needs to operate reliably over the wide variety of situations that may be encountered. In this paper we present a technical architecture which has been implemented to support scalable, cost-effective, runtime experimentation using a framework of models to support informed decision making in an iterative design cycle.
Aiming at the problem of the "semantic gap" and the "dimensionality curse", this paper discussed the model of cross-media retrieval. The methods of feature extraction and fusion of multimedia were ...
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A common approach to mitigate the effects of ontology heterogeneity is to discover and express the specific correspondences (mappings) between different ontologies. An open research question is: how should such ontolo...
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ISBN:
(纸本)1891706241
A common approach to mitigate the effects of ontology heterogeneity is to discover and express the specific correspondences (mappings) between different ontologies. An open research question is: how should such ontology mappings be represented? In recent years several proposals for an ontology mapping representation have been published, but as yet no format is officially standardised or generally accepted in the community. In this paper we will present the results of a systematic analysis of ontology mapping representations to provide a pragmatic state of the art overview of their characteristics. In particular we are interested how current ontology mapping representations can support the management of ontology mappings (sharing, re-use, alteration) as well as how suitable they are for different mapping tasks.
Similarity calculation has many applications, such as information retrieval, and collaborative filtering, among many others. It has been shown that link-based similarity measure, such as SimRank, is very effective in ...
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ISBN:
(纸本)9781424452422
Similarity calculation has many applications, such as information retrieval, and collaborative filtering, among many others. It has been shown that link-based similarity measure, such as SimRank, is very effective in characterizing the object similarities in networks, such as the Web, by exploiting the object-to-object relationship. Unfortunately, it is prohibitively expensive to compute the link-based similarity in a relatively large graph. In this paper, based on the observation that link-based similarity scores of real world graphs follow the power-law distribution, we propose a new approximate algorithm, namely Power-SimRank, with guaranteed error bound to efficiently compute link-based similarity measure. We also prove the convergence of the proposed algorithm. Extensive experiments conducted on real world datasets and synthetic datasets show that the proposed algorithm outperforms SimRank by four-five times in terms of efficiency while the error generated by the approximation is small.
Influence between objects needs to be assessed in many applications. Lots of measures have been proposed, but a domain-independent method is still expected. In this paper, we give a probabilistic definition of influen...
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ISBN:
(纸本)9781424427659
Influence between objects needs to be assessed in many applications. Lots of measures have been proposed, but a domain-independent method is still expected. In this paper, we give a probabilistic definition of influence based on the random walker model on graphs. Two approaches, linear systems method and Basic InfRank algorithm, are shown and return equal results, but Basic InfRank is more efficient by iterative computation. Two variants on bipartite graphs and star graphs are discussed. Experiments show InfRank algorithms have good accuracy, fast convergent rate and high performance.
Along with a massive amount of information being placed online, it is a challenge to exploit the internal and external information of documents when assessing similarity between them. A variety of approaches have been...
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In many real-world domains, link graph is one of the most effective ways to model the relationships between objects. Measuring the similarity of objects in a link graph is studied by many researchers, but an effective...
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Nearly all text classification methods classify texts into predefined categories according to the terms appeared in texts. State-of-the-art of text classification prefer to simplely take a word as a term since it perf...
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