2013
DOI: 10.1007/s10115-013-0678-y
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Bridging structured and unstructured data via hybrid semantic search and interactive ontology-enhanced query formulation

Abstract: In this paper, we identify the problems of current semantic and hybrid search systems, which seek to bridge structure and unstructured data, and propose solutions. We introduce a novel input mechanism for hybrid semantic search that combines the clean and concise input mechanisms of keyword-based search engines with the expressiveness of the input mechanisms provided by semantic search engines. This interactive input mechanism can be used to formulate ontology-aware search queries without prior knowledge of th… Show more

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Cited by 20 publications
(7 citation statements)
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“…Structured data is searchable in a straightforward manner, making it easy to pinpoint information and access it in a fast and fixed way [11]. In contrast, for unstructured data, time-consuming tasks are typically needed to capture specific information and make effective use of it [12].…”
Section: Related Work and Research Hypothesis 21 Text As Unstructurmentioning
confidence: 99%
“…Structured data is searchable in a straightforward manner, making it easy to pinpoint information and access it in a fast and fixed way [11]. In contrast, for unstructured data, time-consuming tasks are typically needed to capture specific information and make effective use of it [12].…”
Section: Related Work and Research Hypothesis 21 Text As Unstructurmentioning
confidence: 99%
“…Several researches have studied on various issues to map and fuse data on multiple sources as a means to translate the user query. The efforts include user interface design [20][21], usability [5], data management model [22][23][24][25][26], query language format (i.e., SPARQL) [27][28], query expressivity [4], [29][30], mapping [9], [26], [31][32], fusing [33][34][35] and ranking [3], [36][37][38]. Most of these approaches rely on linguistic triple (Subject-Predicate-Object) identification [38] which may be grammar and language dependent.…”
Section: Fig 1 Semantic Analysis Querying On Big Datamentioning
confidence: 99%
“…A severe flood associated with data is termed as Big Data, which yields to the challenging situation on the present infrastructure of Data Storage management and the Statistical estimation of data, Analogous situations arises when an organization wants to explore its data from its personal websites for analyzing the customer's feedbacks, customized services towards a product [5]. As a result, the decisions makers would convey their conclusions grounded on the analysis of extracted data or those data which carry some value or weight age [6]. Data analytics is also mapped between unrelated attributes of datasets which can be obtained from machine learning, database systems and statistics.…”
Section: Data Analysingmentioning
confidence: 99%