A service-oriented search framework for full text, geospatial and semantic search

Both, Andreas; Ngomo, Axel-Cyrille Ngonga; Usbeck, Ricardo; Lukovnikov, Denis; Lemke, Christiane; Speicher, Maximilian

doi:10.1145/2660517.2660528

Cited by 9 publications

(13 citation statements)

References 22 publications

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“…Following this process might result in a message-driven architecture (cf., Sec. 7) as it was introduced earlier for search-driven processes on hybrid federated data sources (cf., [4]). However, the methodology might be implemented by different architectures.…”

Section: Ideamentioning

confidence: 99%

Qanary – A Methodology for Vocabulary-Driven Open Question Answering Systems

Both¹,

Diefenbach

Singh

et al. 2016

The Semantic Web. Latest Advances and New Domains

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Abstract. It is very challenging to access the knowledge expressed within (big) data sets. Question answering (QA) aims at making sense out of data via a simpleto-use interface. However, QA systems are very complex and earlier approaches are mostly singular and monolithic implementations for QA in specific domains. Therefore, it is cumbersome and inefficient to design and implement new or improved approaches, in particular as many components are not reusable. Hence, there is a strong need for enabling best-of-breed QA systems, where the best performing components are combined, aiming at the best quality achievable in the given domain. Taking into account the high variety of functionality that might be of use within a QA system and therefore reused in new QA systems, we provide an approach driven by a core QA vocabulary that is aligned to existing, powerful ontologies provided by domain-specific communities. We achieve this by a methodology for binding existing vocabularies to our core QA vocabulary without re-creating the information provided by external components. We thus provide a practical approach for rapidly establishing new (domain-specific) QA systems, while the core QA vocabulary is re-usable across multiple domains. To the best of our knowledge, this is the first approach to open QA systems that is agnostic to implementation details and that inherently follows the linked data principles.

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Section: Ideamentioning

confidence: 99%

Qanary – A Methodology for Vocabulary-Driven Open Question Answering Systems

Both¹,

Diefenbach

Singh

et al. 2016

The Semantic Web. Latest Advances and New Domains

Self Cite

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“…Sec. 4 gives an overview of the components and services that are available in the Qanary ecosystem. Sec.…”

Section: Introductionmentioning

confidence: 99%

“…Most recently we provided a reference implementation of Qanary [17]. We call this implementation message-driven; it follows the architectural pattern that we have previously described for search engines in [4]. The processing steps might be implemented in different components with dedicated technology provided by distinguished research groups.…”

mentioning

confidence: 99%

“…The processing steps might be implemented in different components with dedicated technology provided by distinguished research groups. The message-driven implementation of Qanary [4] laid foundations for the QA ecosystem. The advantage of such an ecosystem is that it combines different approaches, functionality, and advances in the QA community under a single umbrella.…”

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confidence: 99%

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The Qanary Ecosystem: Getting New Insights by Composing Question Answering Pipelines

Diefenbach

Singh

Both

et al. 2017

Lecture Notes in Computer Science

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Abstract. The field of Question Answering (QA) is very multi-disciplinary as it requires expertise from a large number of areas such as natural language processing (NLP), artificial intelligence, machine learning, information retrieval, speech recognition and semantic technologies. In the past years a large number of QA systems were proposed using approaches from different fields and focusing on particular tasks in the QA process. Unfortunately, most of these systems cannot be easily reused, extended, and results cannot be easily reproduced since the systems are mostly implemented in a monolithic fashion, lack standardized interfaces and are often not open source or available as Web services. To address these issues we developed the knowledge-based Qanary methodology for choreographing QA pipelines distributed over the Web. Qanary employs the qa vocabulary as an exchange format for typical QA components. As a result, QA systems can be built using the Qanary methodology in a simpler, more flexible and standardized way while becoming knowledgedriven instead of being process-oriented. This paper presents the components and services that are integrated using the qa vocabulary and the Qanary methodology within the Qanary ecosystem. Moreover, we show how the Qanary ecosystem can be used to analyse QA processes to detect weaknesses and research gaps. We illustrate this by focusing on the Entity Linking (EL) task w.r.t. textual natural language input, which is a fundamental step in most QA processes. Additionally, we contribute the first EL benchmark for QA, as open source. Our main goal is to show how the research community can use Qanary to gain new insights into QA processes.

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“…Authors of [17] present a hybridization of Searchable Encryption and Attribute Based Encryption techniques in order to satisfy the ACAS property. Authors of [18] discussed the idea of connecting powerful tools like Openlink Virtuoso, ElasticSearch and PostGIS within a single framework for cloud based framework for full text, geospatial and semantic search. In paper [19] applications of the Search as a Service (SaaS) are given.…”

Section: Introductionmentioning

confidence: 99%

Service Models for Cloud Computing: Search as a Service (SaaS)

Dašić¹,

Dašić²,

Crvenković³

2016

IJET

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Abstract-Search as a Service (SaaS) is a cloud service model whose main focus is on enterprise search or site-specific web search. Modern companies require fast and accurate information from their internal databases, internal document stores, or through the content of a website. Having a reliable searching mechanism is essential for both internal company staff and for external customers. In this paper the overview of current state and technological advances of Search as a Service (SaaS) cloud service is given, as well as its security issues on current internet service platforms.

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A service-oriented search framework for full text, geospatial and semantic search

Cited by 9 publications

References 22 publications

Qanary – A Methodology for Vocabulary-Driven Open Question Answering Systems

Qanary – A Methodology for Vocabulary-Driven Open Question Answering Systems

The Qanary Ecosystem: Getting New Insights by Composing Question Answering Pipelines

Service Models for Cloud Computing: Search as a Service (SaaS)

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