knowledge-based networking involves the forwarding of messages across a network based on semantics of the data and associated metadata of the message content. However such systems typically assume a common semantic mo...
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Centralized semantic sensor network systems gradually show performance degradation as the scale of the sensor network increases. Thus systems based on distributed approaches with local, autonomous management features ...
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ISBN:
(纸本)9781424449620
Centralized semantic sensor network systems gradually show performance degradation as the scale of the sensor network increases. Thus systems based on distributed approaches with local, autonomous management features are urgently required. In order to achieve local autonomy, it is necessary to push semantics towards the edge of the sensor network, but this is hampered by the lack of availability of lightweight ontology processing and reasoning technologies that are cognizant of the limited resources available in sensor network nodes. This paper proposes an approach to dynamically and automatically compose an ontology reasoner to provide only the level of OWL reasoning required for a given application. A design and prototype implementation are presented, with initial evaluations confirming that this approach saves memory without loss of reasoning ability, which facilitates OWL reasoning on the resource constrained devices typical in sensor networks.
In this paper, we propose a novel framework called Smart-Miner for web usage mining problem which uses link information for producing accurate user sessions and frequent navigation patterns. Unlike the simple session ...
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ISBN:
(纸本)9781605584874
In this paper, we propose a novel framework called Smart-Miner for web usage mining problem which uses link information for producing accurate user sessions and frequent navigation patterns. Unlike the simple session concepts in the time and navigation based approaches, where sessions are sequences of web pages requested from the server or viewed in the browser, Smart Miner sessions are set of paths traversed in the web graph that corresponds to users' navigations among web pages. We have modeled session construction as a new graph problem and utilized a new algorithm, Smart-SRA, to solve this problem efficiently. For the pattern discovery phase, we have developed an efficient version of the Apriori-All technique which uses the structure of web graph to increase the performance. From the experiments that we have performed on both real and simulated data, we have observed that Smart-Miner produces at least 30% more accurate web usage patterns than other approaches including previous session construction methods. We have also studied the effect of having the referrer information in the web server logs to show that different versions of Smart-SRA produce similar results. Our another contribution is that we have implemented distributed version of the Smart Miner framework by employing Map/Reduce Paradigm. We conclude that we can efficiently process terabytes of web server logs belonging to multiple web sites by our scalable framework. Copyright is held by the International World Wide Web Conference Committee (IW3C2).
What-if analysis is an important type of DSS analysis processing procedure. It analyzes hypothetical scenarios based on historical data. The data cube view must be updated when the what-if condition is changed. Since ...
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What-if analysis is an important method to analyze the hypothetical scenarios based on the historical data. It provides useful information for the decision- maker. Multiple versions are critical to what-if analysis. I...
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What-if analysis can provide more meaningful information than classical OLAP. Multi-scenario hypothesis based on historical data needs efficient what-if data view support. In general, delta table for what-if analysis ...
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This paper presents an undertaken research work about the development of an Adaptive Tourism Modeling System which attempts to correctly model a tourism Web application user profile. This paper will follow the methodo...
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This paper presents an undertaken research work about the development of an Adaptive Tourism Modeling System which attempts to correctly model a tourism Web application user profile. This paper will follow the methodology used behind the concept of the application, `User Modeling as a process', which consists of three specific modules in order to achieve a clear user modeling technology. The user representation module devises a collection of knowledge representation formalisms that co-exist in order to constitute the system's view of the user; the user reasoning module is responsible for the execution of several inference tasks as well as the generation of possibly new and valuable information about the user, using the latter module. The user concept that comes out of these two modules will ultimately be used by various kinds of application-level systems, namely a recommender system, therefore instantiating a project-dependent third module.
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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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.
There exists a large and underutilized resource of archaeological literature, both formal, such as scholarly journals and less formal in the form of `grey literature'. In the archaeological domain the vast majorit...
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There exists a large and underutilized resource of archaeological literature, both formal, such as scholarly journals and less formal in the form of `grey literature'. In the archaeological domain the vast majority of this literature contains some geo-spatial element as well as the expected temporal information and therefore its ease of discovery would be greatly enhanced were it accessible via a geo-spatially enabled search mechanism. As a result of this, geo-referencing these types of material and integrating them with other resources, such as monument inventories, is seen as a desirable enhancement for digital archives serving the archaeological research community. This paper provides an overview of a number of the approaches to the integration of such legacy literature into geospatial search mechanisms in an archaeological context. In particular efforts to achieve this via the Archaeotools e-science project and its use of natural language processing and a geo-spatial cross-walk service are discussed as well as potential future enhancements to the process.
Mobility information of cell phone users is very important for wide range of applications, including context-based search and advertising, early warning systems, city-wide sensing applications such as air pollution ex...
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Mobility information of cell phone users is very important for wide range of applications, including context-based search and advertising, early warning systems, city-wide sensing applications such as air pollution exposure estimation and traffic planning. With the inclusion of new technologies in the cell phone hardware such as built-in GPS and 802.11 supports, mobility information are easily captured, managed and forwarded to a remote system via opportunistic connections over Internet. However, it is very difficult to use these low level location data for practical applications due to lack of sufficient information including high level location and temporal data. In order to solve this problem, we propose a Web based mobility analysis system which collects location data from cell phone users via opportunistic Internet connections and convert these low level location data to high level mobility information as well as adding a temporal dimension. In our experiments, we have illustrated the benefits of our systems on the reality mining data set which contains 350 K hours of real cell tower connection data.
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