One of the major limitations of current search engines is that users could not quickly locate what they want if the input query is too general. Some existing techniques try to cluster web search results into groups so...
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One of the major limitations of current search engines is that users could not quickly locate what they want if the input query is too general. Some existing techniques try to cluster web search results into groups so as to user's quick browsing. In this paper, we present a new approach to categorize the web search results by using YAGO ontology. It utilizes the YAGO ontology to automatically generate categories for the user's specific query and classify the search results into appropriate categories. Our experimental results indicate that our method is feasible and effectiveness.
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.
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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Ajax is an important approach for improving rich interactivity between web server and end users during Web 2.0 eras. At the same time, AJAX web pages can not be indexed by search engines due to its asynchronous loadin...
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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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Reliable telecommunication applications in future need the supports from replication real-time main memory databases. In order to improve recovery performance and provide predictable recovery, this paper proposes a ne...
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The paper studies the management problem of data provenance. Firstly, two data models, which enhance the traditional relational model and tree model, are proposed to reveal the basic nature of data provenance. To answ...
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A Top-k aggregate query ranks groups of tuples by their aggregate values, sum or average for example, and returns k groups with the highest aggregate values. We propose a dynamic programming based method to process un...
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Broadcasting/Multicasting problems have been well studied in wireless ad hoc networks. However, only a few approaches take into account the low interference and energy efficiency as the optimization objective simultan...
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ISBN:
(纸本)9781424451142
Broadcasting/Multicasting problems have been well studied in wireless ad hoc networks. However, only a few approaches take into account the low interference and energy efficiency as the optimization objective simultaneously. In this paper, we study the interference and power constrained broadcast/multicast and the delay-bounded interference and power constrained broadcast/multicast routing problems in wireless ad hoc networks using directional antennas. We propose an approximation and a heuristic algorithm for the two problems, respectively. Importantly, motivated by the study of above optimization problems, we propose approximation schemes for two multi-constrained directed Steiner tree problems, respectively. Broadcast/Multicast message by using the trees found by our algorithms tend to have less channel collisions and higher network throughput. The theoretical results are corroborated by simulation studies.
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