Nowadays mainstream RDF Repository Systems are based on RDBMS. The SPARQL query engine translates a SPARQL query into a SQL one, and then the RDBMS executes the SQL query. However the RDBMS optimizers, which usually a...
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Nowadays mainstream RDF Repository Systems are based on RDBMS. The SPARQL query engine translates a SPARQL query into a SQL one, and then the RDBMS executes the SQL query. However the RDBMS optimizers, which usually assume that columns are statistically independent, often underestimate the selectivity of conjunctive predicates and choose a bad query execution plan. It is important for query optimizers to detect correlations among properties. We propose a way of computing property correlations based on ontology itself in order to improve the execution performance of the SQL translated from SPARQL statement queries.
Due to the lack of theoretical knowledge and practical experience, the university students have many deficiencies in contribution. We conducted semi-structured interviews with 28 undergraduate and postgraduate student...
Due to the lack of theoretical knowledge and practical experience, the university students have many deficiencies in contribution. We conducted semi-structured interviews with 28 undergraduate and postgraduate students of Nanjing Agricultural University. At the same time, we used descriptive statistics and cross-analysis methods to analyse the motivations of college students' initial contribution and the influencing factor of their choice. Based on this, this paper puts forward some suggestions for the initial submission of college students, and the journals are also provided for reference in the selection of manuscripts.
Integrating multimodal data from diverse sources is crucial for enhancing various applications. Multimodal entity alignment (MMEA), which discovers equivalent entities across different sources and modalities, aims to ...
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ISBN:
(数字)9798350390155
ISBN:
(纸本)9798350390162
Integrating multimodal data from diverse sources is crucial for enhancing various applications. Multimodal entity alignment (MMEA), which discovers equivalent entities across different sources and modalities, aims to eliminate data silos for comprehensive integration. A key challenge in MMEA is effectively fusing vector representations from different modalities of the same entity for optimal entity matching. Existing fusion methods involve individual fusion operators (e.g., concatenation and summation) or the manual design of complex network structures, incurring significant human resource costs. In this paper, for the first time, we introduce the research question of automatic fusion for MMEA and propose an efficient approach from the perspective of automated architecture search. Experimental comparisons with state-of-the-art methods on real-world datasets demonstrate the effectiveness of the proposed approach.
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.
We present a non-volatile optical switch based on a directional coupler comprising a silicon-Ge2Sb2Te5 (GST) hybrid waveguide. The non-volatility of GST makes it attractive for reducing static power consumption in opt...
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We study the problem of constructing a reverse nearest neighbor (RNN) heat map by finding the RNN set of every point in a two-dimensional space. Based on the RNN set of a point, we obtain a quantitative influence (i.e...
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ISBN:
(纸本)9781509020218
We study the problem of constructing a reverse nearest neighbor (RNN) heat map by finding the RNN set of every point in a two-dimensional space. Based on the RNN set of a point, we obtain a quantitative influence (i.e., heat) for the point. The heat map provides a global view on the influence distribution in the space, and hence supports exploratory analyses in many applications such as marketing and resource management. To construct such a heat map, we first reduce it to a problem called Region Coloring (RC), which divides the space into disjoint regions within which all the points have the same RNN set. We then propose a novel algorithm named CREST that efficiently solves the RC problem by labeling each region with the heat value of its containing points. In CREST, we propose innovative techniques to avoid processing expensive RNN queries and greatly reduce the number of region labeling operations. We perform detailed analyses on the complexity of CREST and lower bounds of the RC problem, and prove that CREST is asymptotically optimal in the worst case. Extensive experiments with both real and synthetic data sets demonstrate that CREST outperforms alternative algorithms by several orders of magnitude.
Recommender systems have been accepted as a vital application on the web by offering product advice or information that users might be interested in. Despite its success, similarity-based collaborative filtering suffe...
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This paper analysis of how OLTP workloads interact with modern processors and caches behavior. First, we extend TPC-C, the OLTP-oriented benchmark, to ETPC-C benchmark, for measuring the performance of main-memory dat...
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This paper analysis of how OLTP workloads interact with modern processors and caches behavior. First, we extend TPC-C, the OLTP-oriented benchmark, to ETPC-C benchmark, for measuring the performance of main-memory database (MMDBMS) more precisely. As the performance of MMDBMS is not affected by disk I/O, it is more sensitive to cache usage. Then using ETPC-C benchmark, we investigated the behavior of caches and processors extensively. We find that the miss stall time is mostly spent on on-CPU-chip caches, that is, the first and second level cache misses are dominant. Furthermore, we find instruction cache (I-cache) stall time of on-CPU-chip is a major component to the memory stall time. The smaller the emulated users, the more proportion the I-cache stall time of on-CPU-chip contributes to the memory stall time. However, if employing index, the system under test (SUT) has more total I-cache stall time than the SUT without index at the same number of emulated users and data population. Another observation is that the SUT with index has a little more branch misprediction rate than the SUT without index in average. Finally, we find only the third level (L3) D-cache stall time rate increases with the number of users. This is because L3 D-cache miss incremental rate is the largest. Under TPC-and ETPC-evaluation, we find that for optimized database performance on modern computers, reducing instruction miss penalty is equally important to reducing data miss penalty;since they are conflict efforts, the best way is to have them balanced.
The field of Information Systems (ISs) has long been recognized, so has Enterprise Information Systems (EISs), a field close to it. Long existing also in organizations or enterprises is the field of records management...
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Synthetic lethality describes an interaction whereby the co-occurrence of two mutations leads to cell death but one mutation alone does not,which can be exploited for cancer therapeutics.1 Due to lacking effective non...
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Synthetic lethality describes an interaction whereby the co-occurrence of two mutations leads to cell death but one mutation alone does not,which can be exploited for cancer therapeutics.1 Due to lacking effective nonsurgical treatment and early clinical diagnosis markers,patients have high mortality and low overall survival rates in cholangiocarcinoma(CCA).
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