UZH-Logo

Maintenance Infos

Evaluating the usability of natural language query languages and interfaces to semantic web knowledge bases


Kaufmann, E; Bernstein, A (2010). Evaluating the usability of natural language query languages and interfaces to semantic web knowledge bases. Journal of Web Semantics, 8(4):377-393.

Abstract

The need to make the contents of the Semantic Web accessible to end-users becomes increasingly pressing as
the amount of information stored in ontology-based knowledge bases steadily increases. Natural language interfaces
(NLIs) provide a familiar and convenient means of query access to Semantic Web data for casual end-users. While
several studies have shown that NLIs can achieve high retrieval performance as well as domain independence, this
paper focuses on usability and investigates if NLIs and natural language query languages are useful from an enduser’s
point of view. To that end, we introduce four interfaces each allowing a different query language and present
a usability study benchmarking these interfaces. The results of the study reveal a clear preference for full natural
language query sentences with a limited set of sentence beginnings over keywords or formal query languages. NLIs
to ontology-based knowledge bases can, therefore, be considered to be useful for casual or occasional end-users. As
such, the overarching contribution is one step towards the theoretical vision of the Semantic Web becoming reality.

The need to make the contents of the Semantic Web accessible to end-users becomes increasingly pressing as
the amount of information stored in ontology-based knowledge bases steadily increases. Natural language interfaces
(NLIs) provide a familiar and convenient means of query access to Semantic Web data for casual end-users. While
several studies have shown that NLIs can achieve high retrieval performance as well as domain independence, this
paper focuses on usability and investigates if NLIs and natural language query languages are useful from an enduser’s
point of view. To that end, we introduce four interfaces each allowing a different query language and present
a usability study benchmarking these interfaces. The results of the study reveal a clear preference for full natural
language query sentences with a limited set of sentence beginnings over keywords or formal query languages. NLIs
to ontology-based knowledge bases can, therefore, be considered to be useful for casual or occasional end-users. As
such, the overarching contribution is one step towards the theoretical vision of the Semantic Web becoming reality.

Citations

27 citations in Web of Science®
49 citations in Scopus®
Google Scholar™

Altmetrics

Downloads

220 downloads since deposited on 19 Feb 2011
13 downloads since 12 months
Detailed statistics

Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:03 Faculty of Economics > Department of Informatics
Dewey Decimal Classification:000 Computer science, knowledge & systems
Date:2010
Deposited On:19 Feb 2011 09:58
Last Modified:05 Apr 2016 14:44
Publisher:Elsevier
ISSN:1570-8268
Publisher DOI:10.1016/j.websem.2010.06.001
Other Identification Number:1428
Permanent URL: http://doi.org/10.5167/uzh-44850

Download

[img]
Preview
Content: Accepted Version
Filetype: PDF
Size: 972kB
View at publisher

TrendTerms

TrendTerms displays relevant terms of the abstract of this publication and related documents on a map. The terms and their relations were extracted from ZORA using word statistics. Their timelines are taken from ZORA as well. The bubble size of a term is proportional to the number of documents where the term occurs. Red, orange, yellow and green colors are used for terms that occur in the current document; red indicates high interlinkedness of a term with other terms, orange, yellow and green decreasing interlinkedness. Blue is used for terms that have a relation with the terms in this document, but occur in other documents.
You can navigate and zoom the map. Mouse-hovering a term displays its timeline, clicking it yields the associated documents.

Author Collaborations