A Requirements Driven Framework for Benchmarking Semantic Web Knowledge Base Systems
| Autor: | Jeff Heflin, Yuanbo Guo, Abir Qasem, Zhengxiang Pan |
|---|---|
| Rok vydání: | 2007 |
| Předmět: |
Database
business.industry Computer science Benchmarking computer.software_genre Knowledge acquisition Computer Science Applications Domain (software engineering) Knowledge-based systems Computational Theory and Mathematics Knowledge base Scalability Benchmark (computing) business Software engineering computer Formal verification Semantic Web Information Systems |
| Zdroj: | IEEE Transactions on Knowledge and Data Engineering. 19:297-309 |
| ISSN: | 1041-4347 |
| DOI: | 10.1109/tkde.2007.19 |
| Popis: | A key challenge for the semantic Web is to acquire the capability to effectively query large knowledge bases. As there will be several competing systems, we need benchmarks that will objectively evaluate these systems. Development of effective benchmarks in an emerging domain is a challenging endeavor. In this paper, we propose a requirements driven framework for developing benchmarks for semantic Web knowledge base systems (SW KBSs). In this paper, we make two major contributions. First, we provide a list of requirements for SW KBS benchmarks. This can serve as an unbiased guide to both the benchmark developers and personnel responsible for systems acquisition and benchmarking. Second, we provide an organized collection of techniques and tools needed to develop such benchmarks. In particular, the collection contains a detailed guide for generating benchmark workload, defining performance metrics, and interpreting experimental results |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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