Empirical Insights on a Value of Ontology Quality in Ontology-Driven Web Search

Strasunskas, Darijus; Tomassen, Stein L.

doi:10.1007/978-3-540-88873-4_28

Cited by 13 publications

(6 citation statements)

References 16 publications

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“…In this framework, different knowledge bases can be compared indirectly, bearing in mind that knowledge bases can obtain varying performances on different tasks. Strasunskas and Tomassen have proposed a scheme to evaluate the 'ontology fitness' with respect to search tasks [101].…”

Section: The Quality Of Crowdsourced Geo-knowledge Basesmentioning

confidence: 99%

“…However, several ontology quality metrics have been devised. Stransunkas and Tomassen, while presenting a framework for ontology evaluation for information retrieval, survey existing ontology metrics [101]. Beside formal quality metrics based on structure, coherence, and other aspects, an open geo-ontology can be evaluated indirectly on the basis of results obtained in real-world tasks.…”

Section: Current Limitations Of Geo-knowledge Bases and Girmentioning

confidence: 99%

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A Survey of Volunteered Open Geo-Knowledge Bases in the Semantic Web

Ballatore

Wilson²,

Bertolotto

2013

Intelligent Systems Reference Library

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Over the past decade, rapid advances in web technologies, coupled with innovative models of spatial data collection and consumption, have generated a robust growth in geo-referenced information, resulting in spatial information overload. Increasing 'geographic intelligence' in traditional text-based information retrieval has become a prominent approach to respond to this issue and to fulfill users' spatial information needs. Numerous efforts in the Semantic Geospatial Web, Volunteered Geographic Information (VGI), and the Linking Open Data initiative have converged in a constellation of open knowledge bases, freely available online. In this article, we survey these open knowledge bases, focusing on their geospatial dimension. Particular attention is devoted to the crucial issue of the quality of geoknowledge bases, as well as of crowdsourced data. A new knowledge base, the OpenStreetMap Semantic Network, is outlined as our contribution to this area. Research directions in information integration and Geographic Information Retrieval (GIR) are then reviewed, with a critical discussion of their current limitations and future prospects.

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Section: The Quality Of Crowdsourced Geo-knowledge Basesmentioning

confidence: 99%

Section: Current Limitations Of Geo-knowledge Bases and Girmentioning

confidence: 99%

A Survey of Volunteered Open Geo-Knowledge Bases in the Semantic Web

Ballatore

Wilson²,

Bertolotto

2013

Intelligent Systems Reference Library

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“…A three-level evaluation framework looking at concept tagging was used to evaluate how well an ontology performs (Porzel and Malaka, 2005). Precision and recall were used in an evaluation framework to evaluate an ontology in the Web search task (Strasunskas and Tomassen, 2008). Nevertheless, none of the evaluation approaches above test or incorporate the connection between ontology characteristics and context parameters that can provide an actionable guideline for ontology engineers.…”

Section: Background and Related Workmentioning

confidence: 99%

Lightweight Ontologies in Context - Relationship between Ontology Characteristics and Context Parameters

Waldstein¹,

Weber²,

Handly³

2013

Proceedings of the International Conference on Knowledge Engineering and Ontology Development

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Ontologies, mainly lightweight ontologies, are ubiquitous throughout the Internet and are succeeding in replacing human expertise. We conducted a study with physicians and nurses performing a search task in the medical domain that demonstrates that lightweight ontologies perform well as a substitute for expertise. The extent of success of the substitution depends upon context of use. Our study investigates lightweight ontologies with respect to the context of use in which they are applied. The better we understand the context of use, the better we can inform ontology design and evaluation. We describe ontologies through characteristics and context through parameters. By varying ontology characteristics and testing the effect on the performance of an ontology-supported task for a context parameter, such as the level of user expertise, we increase our understanding of ontology design and evaluation. Our study shows that changing ontologies by varying some of its characteristics has a direct and significant impact on the performance of the ontology-supported task for different levels of user expertise.

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“…According to these information need distinctions, Strasunskas and Tomassen [15] propose a set of evaluation measures for a search ontology:…”

Section: Search Ontologiesmentioning

confidence: 99%

Automatic Evaluation of Search Ontologies in the Entertainment Domain Using Natural Language Processing

Elhadad¹,

Gabay²,

Netzer³

2011

Applied Semantic Web Technologies

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Abstract. Information Retrieval (IR) research has recently started addressing the information need of exploratory search. where the searcher may be unfamiliar with the domain or not have decided what is the goal of his query. A popular tool to support exploratory search is the use of faceted search. The implementation of faceted search requires that documents be annotated by metadata in the form of attributes and hierarchical categories. In many applications, the metadata is maintained manually, in the form of a search ontology. Recent work has also investigated methods to automatically acquire such metadata from sample documents [1,2]. In this work, we propose a new method to automatically evaluate the quality of such a search ontology.Our method relies on mapping ontology instances to textual documents. On the basis of this mapping, we evaluate the adequacy of ontology relations by measuring their classification potential over the textual documents. This data-driven method provides concrete feedback to ontology maintainers and a quantitative estimation of the functional adequacy of the ontology relations towards search experience improvement. We specifically evaluate whether an ontology relation can help the search engine support exploratory search in the form of effective facets.We test this ontology evaluation method on an ontology in the Movies domain, that has been acquired automatically from the integration of multiple semi-structured and textual data sources (e.g., IMDb and Wikipedia). We automatically construct a domain corpus from a set of movie instances by crawling the Web for movie reviews (both professional and user reviews). The 1-1 relation between textual documents (reviews) and movie instances in the ontology enables us to translate ontology relations into text classes. We verify that the text classifiers induced by key ontology relations (genre, keywords, actors) achieve high performance and exploit the properties of the learned text classifiers to provide concrete feedback on the ontology.The proposed ontology evaluation method is general: it only relies on the possibility to automatically align textual documents to ontology instances. 2Elhadad, Gabay and Netzer

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Empirical Insights on a Value of Ontology Quality in Ontology-Driven Web Search

Cited by 13 publications

References 16 publications

A Survey of Volunteered Open Geo-Knowledge Bases in the Semantic Web

A Survey of Volunteered Open Geo-Knowledge Bases in the Semantic Web

Lightweight Ontologies in Context - Relationship between Ontology Characteristics and Context Parameters

Automatic Evaluation of Search Ontologies in the Entertainment Domain Using Natural Language Processing

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