Improving habitability of natural language interfaces for querying ontologies with feedback and clarification dialogues

Damljanović, Danica; Agatonović, Milan; Cunningham, Hamish; Bontcheva, Kalina

doi:10.1016/j.websem.2013.02.002

Cited by 27 publications

(39 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Natural query interfaces (e.g., [48,91]) go beyond the keyword search; this is due to the fact that they interpret a query as whole and take linguistic considerations into account. However, they do not achieve much in terms of accuracy and completeness due to the ambiguity of natural language; some approaches try to alleviate this issue, such as by acquiring feedback and clarification through user dialogues (e.g., [25,58]), yet this increases the user cognitive load. Finally, visual query languages and systems (cf.…”

Section: Data Access Interfacesmentioning

confidence: 99%

Experiencing OptiqueVQS: a multi-paradigm and ontology-based visual query system for end users

Soylu

Giese

Jiménez-Ruiz

et al. 2015

Univ Access Inf Soc

View full text Add to dashboard Cite

Data access in an enterprise setting is a determining factor for value creation processes, such as sense making, decision making, and intelligence analysis. Particularly, in an enterprise setting, intuitive data access tools that directly engage domain experts with data could substantially increase competitiveness and profitability. In this respect, the use of ontologies as a natural communication medium between end users and computers has emerged as a prominent approach. To this end, this article introduces a novel ontology-based visual query system, named OptiqueVQS, for end users. OptiqueVQS is built on a powerful and scalable data access platform and has a user-centric design supported by a widget-based flexible and extensible architecture allowing multiple coordinated representation and interaction paradigms to be employed. The results of a usability experiment performed with non-expert users suggest that OptiqueVQS provides a decent level of expressivity and high usability, and hence is quite promising.Keywords Visual query formulation · visual query systems · ontology-based data access · data retrieval 1 Introduction

show abstract

Section: Data Access Interfacesmentioning

confidence: 99%

Experiencing OptiqueVQS: a multi-paradigm and ontology-based visual query system for end users

Soylu

Giese

Jiménez-Ruiz

et al. 2015

Univ Access Inf Soc

View full text Add to dashboard Cite

show abstract

“…The proposed technique is superior to the previously mentioned system in [15] as it has several features including:…”

Section: Related Workmentioning

confidence: 98%

“…The authors explain different constraints and data structures used for creating this interface. Afterward, Li et al [15] proposed an interactive interface for querying relational databases that used an interactive approach for understanding the user's natural language queries. This interactive approach was inappropriate tool for understanding the natural language queries, as it was time consuming and complex.…”

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

SDRED: Smart Data Retrieval Engine for Databases

Ahmad¹,

Zahra²

2018

IJITCS

View full text Add to dashboard Cite

Abstract-Today computers are continuously betrothed in almost all domains and organizations. Thus, databases act as the heart for storing and retrieving information that contain huge digital data. However, in order to interact with such databases, it is necessary to have knowledge about the Structured Query Language (SQL), which is difficult for non-expert users to understand and manipulate. So, there is an emergent need to develop a smart and a user friendly computational technique to interact with databases. The current work proposed a smart technique that can handle such context. The proposed "Smart Data Retrieval Engine for Databases (SDRED)" provided an environment that allows a nonexpert user to write and to execute the database queries easily. Furthermore, it retrieved the data stored in databases without a prior knowledge of the SQL. SDRED, which enables the non-expert user to write database queries in natural language (such as English) and to convert them to their SQL query equivalents. The current work presented a detailed design and evaluation for the proposed system by executing different database queries in English. The results established that SDRED successfully converted the non-expert user's natural language queries into their equivalent SQL queries, thereby providing an easy and user-friendly environment to interact with databases.

show abstract

“…Damljanovic et al [5] present FREyA to tackle ambiguity problems when using natural language interfaces. Many ontologies in the Semantic Web contain hard to map relations, e.g., questions starting with 'How long.…”

Section: Question Answeringmentioning

confidence: 99%

HAWK – Hybrid Question Answering Using Linked Data

Usbeck

Ngomo

Bühmann

et al. 2015

Lecture Notes in Computer Science

View full text Add to dashboard Cite

Abstract. The decentral architecture behind the Web has led to pieces of information being distributed across data sources with varying structure. Hence, answering complex questions often required combining information from structured and unstructured data sources. We present HAWK, a novel entity search approach for Hybrid Question Answering based on combining Linked Data and textual data. The approach uses predicate-argument representations of questions to derive equivalent combinations of SPARQL query fragments and text queries. These are executed so as to integrate the results of the text queries into SPARQL and thus generate a formal interpretation of the query. We present a thorough evaluation of the framework, including an analysis of the influence of entity annotation tools on the generation process of the hybrid queries and a study of the overall accuracy of the system. Our results show that HAWK achieves 0.68 respectively 0.61 F-measure within the training respectively test phases on the Question Answering over Linked Data (QALD-4) hybrid query benchmark.

show abstract

Improving habitability of natural language interfaces for querying ontologies with feedback and clarification dialogues

Cited by 27 publications

References 13 publications

Experiencing OptiqueVQS: a multi-paradigm and ontology-based visual query system for end users

Experiencing OptiqueVQS: a multi-paradigm and ontology-based visual query system for end users

SDRED: Smart Data Retrieval Engine for Databases

HAWK – Hybrid Question Answering Using Linked Data

Contact Info

Product

Resources

About