Roberto García , Rosa Gil , Eirik Bakke , David R. Karger
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引用次数: 2
Abstract
During the years, it has been possible to assess significant improvements in the computational efficiency of Semantic Web search and exploration systems. However, it has been much harder to assess how well different semantic systems’ user interfaces help their users. One of the key factors facilitating the advancement of research in a particular field is the ability to compare the performance of different approaches. Though there are many such benchmarks in Semantic Web fields that have experienced significant improvements, this is not the case for Semantic Web user interfaces for data exploration. We propose and demonstrate the use of a benchmark for evaluating such user interfaces, which includes a set of typical user tasks and a well-defined procedure for assigning a measure of performance on those tasks to a semantic system. We have applied the benchmark to four such systems. Moreover, all the required resources to apply the benchmark are openly available online. We intend to initiate a community conversation that will lead to a generally accepted framework for comparing systems and for measuring, and thus encouraging, progress towards better semantic search and exploration tools.
期刊介绍:
The Journal of Web Semantics is an interdisciplinary journal based on research and applications of various subject areas that contribute to the development of a knowledge-intensive and intelligent service Web. These areas include: knowledge technologies, ontology, agents, databases and the semantic grid, obviously disciplines like information retrieval, language technology, human-computer interaction and knowledge discovery are of major relevance as well. All aspects of the Semantic Web development are covered. The publication of large-scale experiments and their analysis is also encouraged to clearly illustrate scenarios and methods that introduce semantics into existing Web interfaces, contents and services. The journal emphasizes the publication of papers that combine theories, methods and experiments from different subject areas in order to deliver innovative semantic methods and applications.