An Ontology Based Visual Tool for Query Formulation Support

Catarci, Tiziana; Dongilli, Paolo; Mascio, Tania Di; Franconi, Enrico; Santucci, Giuseppe; Tessaris, Sergio

doi:10.1007/978-3-540-39962-9_15

Cited by 43 publications

(53 citation statements)

References 14 publications

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“…Examples of QbN are Tabulator [25], SEWASIE project [7], ViziQuer [26], and Visor [27], and well-known examples of faceted search are Flamenco [28], mSpace [29], and Exhibit [30]. The examples of first category provide weak or no support for select and projection operations; similarly the examples on the latter do not provide sufficient support for joining concepts.…”

Section: Related Workmentioning

confidence: 99%

“…are not meant to capture a domain per se and are not truly natural for end-users. Recent approaches (e.g., [7,8]) close this gap by employing ontologies for visual query formulation, due to their closeness to reality; and the emergence of ontology-based data access (OBDA) technologies (cf. [9]) complete the overall picture by making it possible to access data residing on traditional relational databases over ontologies.…”

Section: Introductionmentioning

confidence: 99%

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A Preliminary Approach on Ontology-Based Visual Query Formulation for Big Data

Soylu

Skjæveland

Giese

et al. 2013

Communications in Computer and Information Science

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Abstract. Data access in an enterprise setting is a determining factor for the potential of value creation processes such as sense-making, decision making, and intelligence analysis. As such, providing friendly data access tools that directly engage domain experts (i.e., end-users) with data, as opposed to the situations where database/IT experts are required to extract data from databases, could substantially increase competitiveness and profitability. However, the ever increasing volume, complexity, velocity, and variety of data, known as the Big Data phenomenon, renders the end-user data access problem even more challenging. Optique, an ongoing European project with a strong industrial perspective, aims to countervail the Big Data effect, and to enable scalable end-user data access to traditional relational databases by using an ontology-based approach. In this paper, we specifically present the preliminary design and development of our ontology-based visual query system and discuss directions for addressing the Big Data effect.

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Preliminary Approach on Ontology-Based Visual Query Formulation for Big Data

Soylu

Skjæveland

Giese

et al. 2013

Communications in Computer and Information Science

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“…The application ontology then becomes the input of a DIG-enabled query tool like (Catarci, T. et al, 2004); the two main modules of this tool are the Compose module for assisting the user in effectively composing a query, and the Query module for directly specifying the data which should be retrieved from the data sources. In particular, with input the LIS ontology, Compose will propose sign components (ontology classes) which are related to the user's current selection, as specified in the ontology; e.g., if the user selects "one-hand sign" then the query tool will not show "hands relational position" as next possible choice to the user, because the ontology does not relate these concepts.…”

Section: The Ontology-driven Dictionarymentioning

confidence: 99%

“…In particular, with input the LIS ontology, Compose will propose sign components (ontology classes) which are related to the user's current selection, as specified in the ontology; e.g., if the user selects "one-hand sign" then the query tool will not show "hands relational position" as next possible choice to the user, because the ontology does not relate these concepts. We refer the reader to (Catarci, T. et al, 2004) for more on the query tool and its intergration with a database.…”

Section: The Ontology-driven Dictionarymentioning

confidence: 99%

An Ontology for a Web Dictionary of Italian Sign Language

Mascio

2007

Proceedings of the Third International Conference on Web Information Systems and Technologies

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Keywords:ontology and the semantic web; knowledge management; web-based education.Abstract: Sign languages are visual languages used in deaf communities. They are essentially tempo-spatial languages: signs are made of manual components, e.g., the hand movements, and non-manual components, e.g., facial expressions. The e-LIS project aims at the creation of the first web bidirectional dictionary for Italian sign language-verbal Italian. Whereas the lexicographic order is a standard and 'natural' way of ordering hence retrieving words in Italian dictionaries, there is nothing similar for Italian sign language dictionaries. Stokoebased notations have been successfully employed for decomposing and ordering signs in paper dictionaries for Italian sign language; but consulting the dictionaries requires knowing the adopted Stokoe-based notation, which is not as easy-to-remember and well-known as Italian alphabet is. Users of a web dictionary cannot be expected to be expert of this. There the role of ontologies comes into play. The ontology presented in this paper analyses and relates the formational components of a sign; in some sense, the ontology allows us to 'enrich' the e-LIS dictionary with expert information concerning classes of sign components and, above all, their mutual relations. We conclude this paper with several open questions at the intersection of knowledge representation and reasoning, semantic web, sign and computational linguistics.

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“…Plugins currently exist for AktiveMedia (manual and semi-automatic annotation [6]) and some information extraction tools (T-Rex, an ontology-based IE tool [15] and Saxon, a rule-based extraction system 5 ). Extracted information (ontology-based annotations) is stored in the form of RDF triples according to OWL or RDF ontologies into a triple store.…”

Section: Indexing and Annotationmentioning

confidence: 99%

Hybrid Search: Effectively Combining Keywords and Semantic Searches

Bhagdev¹,

Chapman²,

Ciravegna³

et al.

Lecture Notes in Computer Science

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Abstract. This paper describes hybrid search, a search method supporting both document and knowledge retrieval via the flexible combination of ontologybased search and keyword-based matching. Hybrid search smoothly copes with lack of semantic coverage of document content, which is one of the main limitations of current semantic search methods. In this paper we define hybrid search formally, discuss its compatibility with the current semantic trends and present a reference implementation: K-Search. We then show how the method outperforms both keyword-based search and pure semantic search in terms of precision and recall in a set of experiments performed on a collection of about 18.000 technical documents. Experiments carried out with professional users show that users understand the paradigm and consider it very powerful and reliable. K-Search has been ported to two applications released at Rolls-Royce plc for searching technical documentation about jet engines.

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An Ontology Based Visual Tool for Query Formulation Support

Cited by 43 publications

References 14 publications

A Preliminary Approach on Ontology-Based Visual Query Formulation for Big Data

A Preliminary Approach on Ontology-Based Visual Query Formulation for Big Data

An Ontology for a Web Dictionary of Italian Sign Language

Hybrid Search: Effectively Combining Keywords and Semantic Searches

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