Similarity estimation can be used in many applications such as recommender system, cluster analysis, information retrieval and link prediction. SimRank is a famous algorithm to measure objects' similarities based ...
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Developing an integration management system for business continuity, records and knowledge (IMS of BRK) is beneficial to the collaboration, optimization and innovation of business continuity management system (BCMS), ...
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Given a set of lists, where items of each list are sorted by the ascending order of their values, the objective of this paper is to figure out the common items that appear in all of the lists efficiently. This problem...
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The requirements of OLAP applications increase rapidly by dramatically increased data volume, users, query volume and query complexity. The requirement for shortening update period in data warehouse is another crucial...
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Many of management systems for business continuity, records and knowledge (BRK) are standalone. Connections and networks of business continuity management systems (BCMS), records management systems (RMS) and knowledge...
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ISBN:
(纸本)9788988678251
Many of management systems for business continuity, records and knowledge (BRK) are standalone. Connections and networks of business continuity management systems (BCMS), records management systems (RMS) and knowledge management systems (KMS) are expected to study for facing challenges from evidence-based collaborations in a networked working environment, in terms of control of documented information for business efficiency;guarantee of evidentiality and quality of documented information for organizational effectiveness;and sharing, protecting and increasing values of records as business and knowledge assets for knowledge economy. Based on review of ideas of integration management thinking, best practice frameworks of business continuity management, records management and knowledge management, management models of BCMS, RMS and KMS, an architecture framework towards comprehensive integration management of BRK is proposed by vertical integration design and crosswise integration operations. Case studies demonstrate that such architecture framework has implications to enhance controls of efficiency, effectiveness, and economy of organizational resources and assets adaptable to complex global competition;to improve quality assurance of documented information for supporting evidence-based governance adaptable to dynamic changing of information and communication technologies;to consistent accumulation, sharing and exchanging evidence, memory and knowledge along e-business processes to promote collaboration, optimization and innovation of BCMS, RMS and KMS.
SimRank is a well known algorithm which conducts link analysis to measure similarity between each pair of nodes (nodepair). But it suffers from high computational cost, limiting its usage in large-scale datasets. More...
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This paper proposes a new method to cluster law texts based on referential relation of laws. We extract law entities (an entity represents a law) and their referential relation from law texts. Then SimRank algorithm i...
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This paper proposes a new method to cluster law texts based on referential relation of laws. We extract law entities (an entity represents a law) and their referential relation from law texts. Then SimRank algorithm is applied to calculate law entity's similarity through referential relation and law clustering is carried out based on the SimRank similarity. This is the first time to apply SimRank algorithm in the domain of Law and use it to carry out text clustering. Prototype and experiments show that our solution is feasible. We also publish the extracted data as Linked Law data with RDF data model, which forms the first open semantic web database in Law domain. Linked Law data enables user to access law data with rich data links and query web data by application interface of Semantic Web.
In this paper, we analyse the data access characteristics of a typical XML information retrieval system and propose a new query aware buffer replacement algorithm based on prediction of Minimum Reuse Distance (MRD for...
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In this paper, we analyse the data access characteristics of a typical XML information retrieval system and propose a new query aware buffer replacement algorithm based on prediction of Minimum Reuse Distance (MRD for short). The algorithm predicts an object's next reference distance according to the retrieval system's running status and replaces the objects that have maximum reuse distances. The factors considered in the replacement algorithm include the access frequency, creation cost, and size of objects, as well as the queries being executed. By taking into account the queries currently running or queuing in the system, MRD algorithm can predict more accurately the reuse distances of index data objects.
The requirements of OLAP applications increase rapidly by dramatically increased data volume, users, query volume and query complexity. The requirement for shortening update period in data warehouse is another crucial...
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The requirements of OLAP applications increase rapidly by dramatically increased data volume, users, query volume and query complexity. The requirement for shortening update period in data warehouse is another crucial factor for a scalable OLAP application. In this paper, we propose a scalable OLAP prototype to support the query processing with increasing data volume by distributing the whole fact tuples to multiple servers to construct a set of sibling cubes which can be merged together to obtain the whole cube. We employ a light weight distribution policy with fully duplicated dimension tables in each sibling server on the observation of very low proportion of space cost for dimension tables. OLAP query with distributed aggregate functions can be transformed into queries to be performed parallel in sibling servers. For non-distributed computing aggregate functions, such as median, the optimized median aggregate computing algorithm is proposed to reduce transmission volume between servers while computing the global median values. We also present a three-level framework in data warehouse to meet the requirement of shorter update period in "operational business intelligence". An asynchronous tunnel model is proposed to reduce update latency by pre-fetching updated tuples to OLAP processing server. Finally, we set up prototype system ParaCube to evaluate performance in SN (shared-nothing) system and multi-core platforms.
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