PowerMap: Mapping the Real Semantic Web on the Fly

López, Vanessa; Sabou, Marta; Motta, Enrico

doi:10.1007/11926078_30

Cited by 44 publications

(33 citation statements)

References 16 publications

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“…In this category, we distinguish keyword-based approaches, such as [13,33,34,40,51,52,55], where queries consist of lists of keywords, and natural-language-based approaches, such as [16,23,29,32,42,43], where users can express queries in natural language. Finally, we also discuss related work on ranking techniques for the Semantic Web.…”

Section: Related Workmentioning

confidence: 99%

Semantic Web Search Based on Ontological Conjunctive Queries

Fazzinga

Gianforme

Gottlob

et al. 2010

Lecture Notes in Computer Science

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Abstract. Many experts predict that the next huge step forward in Web information technology will be achieved by adding semantics to Web data, and will possibly consist of (some form of) the Semantic Web. In this paper, we present a novel approach to Semantic Web search, called Serene, which allows for a semantic processing of Web search queries, and for evaluating complex Web search queries that involve reasoning over the Web. More specifically, we first add ontological structure and semantics to Web pages, which then allows for both attaching a meaning to Web search queries and Web pages, and for formulating and processing ontology-based complex Web search queries (i.e., conjunctive queries) that involve reasoning over the Web. Here, we assume the existence of an underlying ontology (in a lightweight ontology language) relative to which Web pages are annotated and Web search queries are formulated. Depending on whether we use a general or a specialized ontology, we thus obtain a general or a vertical Semantic Web search interface, respectively. That is, we are actually mapping the Web into an ontological knowledge base, which then allows for Semantic Web search relative to the underlying ontology. The latter is then realized by reduction to standard Web search on standard Web pages and logically completed ontological annotations. That is, standard Web search engines are used as the main inference motor for ontologybased Semantic Web search. We develop the formal model behind this approach and also provide an implementation in desktop search. Furthermore, we report on extensive experiments, including an implemented Semantic Web search on the Internet Movie Database.

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Section: Related Workmentioning

confidence: 99%

Semantic Web Search Based on Ontological Conjunctive Queries

Fazzinga

Gianforme

Gottlob

et al. 2010

Lecture Notes in Computer Science

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“…The user's NL query is processed by the ontologybased QA component, PowerAqua [14]. This component operates in a multi-ontology scenario where it translates the user terminology into the terminology of the available ontologies and retrieves a list of ontological entities as a response.…”

Section: System Architecturementioning

confidence: 99%

“…Secondly, they do not provide a semantic document ranking model: Semantic Portals [4,17] and QA systems [14,19] typically provide search functionalities that may be better characterised as semantic data retrieval, rather than semantic information retrieval. Searches return ontology instances rather than documents, and generally, no ranking method is provided.…”

Section: Introductionmentioning

confidence: 99%

“…Specifically, we report experiments with a new system which builds upon two pre-existing semantic search approaches with complementary affordances. The first, drawn from the PowerAqua system [14], can search heterogeneous knowledge bases and generates answers to natural language queries. The second system, (reported in [3]), supports semantic search, based on formal domain knowledge, over non-semantic World Wide Web documents.…”

Section: Introductionmentioning

confidence: 99%

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Semantic Search Meets the Web

Fernández

López

Sabou

et al. 2008

2008 IEEE International Conference on Semantic Computing

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“…In heterogeneous environments, the problem of identifying the right entity is an order of magnitude more difficult than in single domains. There are two main approaches: formal ontology mapping (Euzenat & Shvaiko, 2007) and light weight mapping, as is used, for example, in PowerMap (Lopez, Sabou et al, 2006). It may even be possible to exploit linguistic and domain knowledge from matching to help users to understand the intersections between different sources of semantic mark-up.…”

Section: Single Mode-heterogeneousmentioning

confidence: 99%

The usability of semantic search tools: a review

Uren¹,

Lei²,

López³

et al. 2007

The Knowledge Engineering Review

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The goal of semantic search is to improve on traditional search methods by exploiting the semantic metadata. In this paper, we argue that supporting iterative and exploratory search modes is important to the usability of all search systems. We also identify the types of semantic queries the users need to make, the issues concerning the search environment and the problems that are intrinsic to semantic search in particular. We then review the four modes of user interaction in existing semantic search systems, namely keyword-based, form-based, view-based and natural language-based systems. Future development should focus on multimodal search systems, which exploit the advantages of more than one mode of interaction, and on developing the search systems that can search heterogeneous semantic metadata on the open semantic Web.

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PowerMap: Mapping the Real Semantic Web on the Fly

Cited by 44 publications

References 16 publications

Semantic Web Search Based on Ontological Conjunctive Queries

Semantic Web Search Based on Ontological Conjunctive Queries

Semantic Search Meets the Web

The usability of semantic search tools: a review

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