scholarly journals A Novel Adaptive Cuckoo Search for Optimal Query Plan Generation

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Ramalingam Gomathi ◽  
Dhandapani Sharmila
Keyword(s):  
Semantic Web ◽  
Query Optimization ◽  
Execution Time ◽  
Cuckoo Search ◽  
Optimization Methods ◽  
Web Data ◽  
Query Plan ◽  
Plan Generation ◽  
Description Framework ◽  
Rdf Graphs

The emergence of multiple web pages day by day leads to the development of the semantic web technology. A World Wide Web Consortium (W3C) standard for storing semantic web data is the resource description framework (RDF). To enhance the efficiency in the execution time for querying large RDF graphs, the evolving metaheuristic algorithms become an alternate to the traditional query optimization methods. This paper focuses on the problem of query optimization of semantic web data. An efficient algorithm called adaptive Cuckoo search (ACS) for querying and generating optimal query plan for large RDF graphs is designed in this research. Experiments were conducted on different datasets with varying number of predicates. The experimental results have exposed that the proposed approach has provided significant results in terms of query execution time. The extent to which the algorithm is efficient is tested and the results are documented.

scholarly journals Modified Firefly Algorithm for Optimizing Biomedical Breast Cancer Queries

2021 ◽  
Author(s):  
Gomathi Ramalingam
Keyword(s):  
Breast Cancer ◽  
Semantic Web ◽  
Execution Time ◽  
Firefly Algorithm ◽  
Optimal Solution ◽  
Query Languages ◽  
Query Execution ◽  
Web Data ◽  
Query Plan ◽  
Modified Firefly Algorithm

Abstract Querying and retrieving Semantic Web data is a challenging task due to the increment in its volume. Many query languages were designed to retrieve Semantic Web data. A popular querying method of communication in Semantic Web is SPARQL. The query languages were designed with some optimization strategies, and it was found in literature that these query languages were not able to handle large volume of data efficiently. In this research, a Modified Firefly Algorithm (MFA) is applied to optimize the SPARQL queries so that it can retrieve data from a large Semantic Web repository efficiently by reducing query execution time. Every query will have multiple query plans generated with different cost values. The challenge is to choose the best query plan which reduces the query cost and query execution time. The proposed algorithm uses the best query plan in the previous iteration to calculate the distance between two query plans using the radius parameter. The proposed algorithm generates a query plan which is a global optimal solution. MFA is evaluated using the BioPortal dataset with triples containing breast cancer. Experimental analysis is conducted to identify the significant improvement in performance of the proposed work with the existing nature inspired query optimization algorithms. The efficiency of MFA is compared with other algorithms in terms of query execution time and the performance is evaluated.

Natural Language Generation from Graphs

2014 ◽  
Vol 08 (03) ◽  
pp. 335-384 ◽  
Author(s):  
Ngan T. Dong ◽  
Lawrence B. Holder
Keyword(s):  
Semantic Web ◽  
Natural Language ◽  
Web Search ◽  
Open Data ◽  
Natural Language Generation ◽  
Language Generation ◽  
Expert User ◽  
Computer Representation ◽  
Description Framework ◽  
Rdf Graphs

The Resource Description Framework (RDF) is the primary language to describe information on the Semantic Web. The deployment of semantic web search from Google and Microsoft, the Linked Open Data Community project along with the announcement of schema.org by Yahoo, Bing and Google have significantly fostered the generation of data available in RDF format. Yet the RDF is a computer representation of data and thus is hard for the non-expert user to understand. We propose a Natural Language Generation (NLG) engine to generate English text from a small RDF graph. The Natural Language Generation from Graphs (NLGG) system uses an ontology skeleton, which contains hierarchies of concepts, relationships and attributes, along with handcrafted template information as the knowledge base. We performed two experiments to evaluate NLGG. First, NLGG is tested with RDF graphs extracted from four ontologies in different domains. A Simple Verbalizer is used to compare the results. NLGG consistently outperforms the Simple Verbalizer in all the test cases. In the second experiment, we compare the effort spent to make NLGG and NaturalOWL work with the M-PIRO ontology. Results show that NLGG generates acceptable text with much smaller effort.

scholarly journals Analysis of RDF Syntaxes for Semantic Web Development

2015 ◽  
Vol 18 (1) ◽  
pp. 33-42 ◽  
Author(s):  
Yevgeny Gryaznov ◽  
Pavel Rusakov
Keyword(s):  
Semantic Web ◽  
Directed Graph ◽  
Resource Description Framework ◽  
Formal Model ◽  
Information Representation ◽  
Web Development ◽  
Rdf Data ◽  
Description Framework ◽  
Rdf Graphs ◽  
Resource Description

Abstract In this paper authors perform a research on possibilities of RDF (Resource Description Framework) syntaxes usage for information representation in Semantic Web. It is described why pure XML cannot be effectively used for this purpose, and how RDF framework solves this problem. Information is being represented in a form of a directed graph. RDF is only an abstract formal model for information representation and side tools are required in order to write down that information. Such tools are RDF syntaxes – concrete text or binary formats, which prescribe rules for RDF data serialization. Text-based RDF syntaxes can be developed on the existing format basis (XML, JSON) or can be an RDF-specific – designed from scratch to serve the only purpose – to serialize RDF graphs. Authors briefly describe some of the RDF syntaxes (both XML and non-XML) and compare them in order to identify strengths and weaknesses of each version. Serialization and deserialization speed tests using Jena library are made. The results from both analytical and experimental parts of this research are used to develop the recommendations for RDF syntaxes usage and to design a RDF/XML syntax subset, which is intended to simplify the development and raise compatibility of information serialized with this RDF syntax.

scholarly journals Teaching Learning Based Optimization in Semantic Web of Distributed RDF

2019 ◽  
Vol 8 (2) ◽  
pp. 5381-5389
Keyword(s):  
Semantic Web ◽  
Query Optimization ◽  
Open Data ◽  
Computation Time ◽  
Population Based ◽  
Experimental Result ◽  
Distributed Data ◽  
Teaching Learning Based Optimization ◽  
Description Framework ◽  
Teaching Learning

Semantic web data use as a unified data model in various areas, such as Bioinformatics, media data, Wikipedia, social networks, and government open data. Sharing information among people using semantic web helps to understand and manipulation of information. In the semantic web, the Resource Description Framework (RDF) denotes the linked data. The logical data is represented as RDF model to manage the unformatted data and it provides an ability to machine interpretability of data. The major problem on the web is to handle the large volume of the data that also has other challenges like query processing and optimization over widely distributed RDF data. In this research, the Teacher Learning based Optimization (TLBO) algorithm is proposed for the query optimization to reduce query cost, and optimize the computation time of the query. The TLBO technique select the suitable location and size of the population based on the data that effectively provide the solution for the distributed data i.e.., triple pattern of semantic web. The experimental result showed that the TLBO in query optimization performed well in the manner of query computation time compared to existing methods like MARVEL. Additionally, the results showed that the proposed TLBO model achieved nearly 4.93 seconds for executing the multiple queries in LUBM dataset.

Distributed Query Plan Generation using Cuckoo Search Algorithm

2017 ◽  
Vol 6 (1) ◽  
pp. 86-100
Author(s):  
Monika Yadav ◽  
T. V. Vijay Kumar
Keyword(s):  
Query Processing ◽  
Search Algorithm ◽  
Distributed Databases ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Distributed Query Processing ◽  
Query Plan ◽  
Plan Generation ◽  
Distributed Query ◽  
Efficient Query Processing

Query processing in distributed databases involves data transmission amongst sites capable of providing answers to a distributed query. For this, a distributed query processing strategy, which generates efficient query processing plans for a given distributed query, needs to be devised. Since in distributed databases, the data is fragmented and replicated at multiple sites, the number of query plans increases exponentially with increase in the number of sites capable of providing answers to a distributed query. As a result, generating efficient query processing plans, from amongst all possible query plans, becomes a complex problem. This distributed query plan generation (DQPG) problem has been addressed using the Cuckoo Search Algorithm (CSA) in this paper. Accordingly, a CSA based DQPG algorithm (DQPGCSA) that aims to generate Top-K query plans having minimum cost of processing a distributed query has been proposed. Experimental based comparison of DQPGCSA with the existing GA based DQPG algorithm shows that the former is able to generate Top-K query plans that have a comparatively lower query processing cost. This, in turn, reduces the query response time resulting in efficient decision making.

Research and Development on Semantic Web Data Management

2009 ◽  
Vol 20 (11) ◽  
pp. 2950-2964 ◽  
Author(s):  
Xiao-Yong DU ◽  
Yan WANG ◽  
Bin LÜ
Keyword(s):  
Semantic Web ◽  
Research And Development ◽  
Data Management ◽  
Web Data ◽  
Web Data Management

scholarly journals Robust Query Optimization Methods With Respect to Estimation Errors

2015 ◽  
Vol 44 (3) ◽  
pp. 25-36 ◽  
Author(s):  
Shaoyi Yin ◽  
Abdelkader Hameurlain ◽  
Franck Morvan
Keyword(s):  
Query Optimization ◽  
Optimization Methods ◽  
Estimation Errors

scholarly journals Metaheuristic techniques comparison to optimize robotic end-effector behavior and its workspace

2018 ◽  
Vol 15 (5) ◽  
pp. 172988141880113
Author(s):  
Miguel Angel Funes Lora ◽  
Edgar Alfredo Portilla-Flores ◽  
Raul Rivera Blas ◽  
Emmanuel Alejandro Merchán Cruz ◽  
Manuel Faraón Carbajal Romero
Keyword(s):  
Numerical Technique ◽  
Cuckoo Search ◽  
Optimization Methods ◽  
Metaheuristic Algorithms ◽  
End Effector ◽  
Bee Colony ◽  
Ill Posed ◽  
Metaheuristic Techniques

Many robots are dedicated to replicate trajectories recorded manually; the recorded trajectories may contain singularities, which occur when positions and/or orientations are not achievable by the robot. The optimization of those trajectories is a complex issue and classical optimization methods present a deficient performance when solving them. Metaheuristics are well-known methodologies for solving hard engineering problems. In this case, they are applied to obtain alternative trajectories that pass as closely as possible to the original one, reorienting the end-effector and displacing its position to avoid the singularities caused by limitations of inverse kinematics equations, the task, and the workspace. In this article, alternative solutions for an ill-posed problem concerning the behavior of the robotic end-effector position and orientation are proposed using metaheuristic algorithms such as cuckoo search, differential evolution, and modified artificial bee colony. The case study for this work considers a three-revolute robot (3R), whose trajectories can contain or not singularities, and an optimization problem is defined to minimize the objective function that represents the error of the alternative trajectories. A tournament in combination with a constant of proportionality allows the metaheuristics to modify the gradual orientation and position of the robot when a singularity is present. Consequently, the procedure selects from all the possible elbow-configurations the best that fits the trajectory. A classical numerical technique, Newton’s method, is used to compare the results of the applied metaheuristics, to evaluate their quality. The results of this implementation indicate that metaheuristic algorithms are an efficient tool to solve the problem of optimizing the end-effector behavior, because of the quality of the alternative trajectory produced.

Sign in / Sign up

Export Citation Format

Share Document