ExNa: an efficient search pattern for semantic search engines

Wei, Xiao; Zeng, Daniel

doi:10.1002/cpe.3818

Cited by 5 publications

(3 citation statements)

References 24 publications

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“…Another dimension we did not focus on is scalability and using advanced techniques to speed up search at scale, such as those provided by state-of-the-art vector databases (e.g. Pinecone 20 or Weaviate 21 that provide efficient indexing and query optimisation techniques. Replacing our current exhaustive vector comparison with these would bring massive improvements in terms of scalability, but we have seen that basic approach already produces satisfactory results on nontrivial problem sizes.…”

Section: Discussionmentioning

confidence: 99%

“…The absence of methodological frameworks is also visible in many other services and platforms that can be used, inter alia, for the development of semantic search engines 18 . A notable exception to this is the work presented in [20], which characterises search patterns in search engines in terms of a combination of index structures, user profiles, and interaction mechanisms. However, the authors proceed to developing their own search pattern that relies on a hierarchical semantic structure available to the search engine (which we do not assume), rather than to flesh out a more general design methodology for semantic search engines.…”

Section: Related Workmentioning

confidence: 99%

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Building Lightweight Semantic Search Engines

Rovatsos,

Filgueira

2023

2023 IEEE 19th International Conference on E-Science (E-Science)

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Despite significant advances in methods for processing large volumes of structured and unstructured data, surprisingly little attention has been devoted to developing general practical methodologies that leverage state-of-the-art technologies to build domain-specific semantic search engines tailored to use cases where they could provide substantial benefits.This paper presents a methodology for developing these kinds of systems in a lightweight, modular, and flexible way with a particular focus on providing powerful search tools in domains where non-expert users encounter challenges in exploring the data repository at hand.Using an academic expertise finder tool as a case study, we demonstrate how this methodology allows us to leverage powerful off-the-shelf technology to enable the rapid, low-cost development of semantic search engines, while also affording developers with the necessary flexibility to embed user-centric design in their development in order to maximise uptake and application value.

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Section: Discussionmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Building Lightweight Semantic Search Engines

Rovatsos,

Filgueira

2023

2023 IEEE 19th International Conference on E-Science (E-Science)

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“…Start with classifying and comparing current search engines, particularly from the perspective of search patterns which consist of index structure, user profiles, and interaction mechanism. X. Wei then present a novel search pattern named ExNa by defining its model and basic operations in detail. Two attribute reduction methods based on minimum decision cost are proposed by Z. Bi from the algebraic view and the information theory, respectively.…”

mentioning

confidence: 99%

Big data‐related technologies and applications

Luo

Liu

2016

Concurrency and Computation

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With the advances of information communication technologies, it is critical to improve the efficiency and accuracy of modern data processing techniques. The past decade has witnessed the tremendous technical advances in sensor networks, Internet/Web of Things, cloud computing, mobile/embedded computing, spatial/temporal data processing, and big data, and these technologies have provided new opportunities and solutions to data processing techniques. Big data is an emerging paradigm applied to datasets whose size is beyond the ability of commonly used software tools to capture, manage, and process the data within a tolerable elapsed time. Such datasets are often from various sources (Variety) yet unstructured such as social media, sensors, scientific applications, surveillance, video and image archives, Internet texts and documents, Internet search indexing, medical records, business transactions, and web logs and are of large size (Volume) with fast data in/out (Velocity). More importantly, big data has to be of high value (Value) and establish trust in it for business decision-making (Veracity). Various technologies are being discussed to support the handling of big data such as massively parallel processing databases, scalable storage systems, cloud computing platforms, and MapReduce. Big data is more than simply a matter of size; it is an opportunity to find insights in new and emerging types of data and content, to make business more agile, and to answer questions that were previously considered beyond our reach. This special issue wants to demonstrate the emerging issues in the research of big data and approaches towards it. Original and research articles are solicited in all aspects including theoretical studies, practical applications, and experimental prototypes.The submitted manuscripts were reviewed by experts from both academia and industry. After two rounds of reviewing, the highest quality manuscripts were accepted for this special issue. Totally, we have received 20 manuscripts and 11 papers are accepted. Five papers are selected from SKG2015 conference with about 50% new content. This special issue will be published by Concurrency and Computation: Practice and Experience as special issues.In order to detect and describe the real-time urban emergency event, the knowledge base model is proposed by the paper by Z. Xu et al [1]. The crowdsourcing-based knowledge base model is introduced, which uses the information from social media. X. Lin et al [2]. introduced one such comprehensive schemes: it takes consideration of the DG's own characteristics and its ability to support the local loading, it adopts different protection strategy, and realizes the fault isolation and island division through the coordination between the protection and the automatic devices. J. Zheng [3] extracted the feature information and also mined the association rules to identify and mark the unknown protocol using the learning mechanism of machine. The unknown protocol in a specific environment was found and analyzed by marking t...

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Textual Keyword Optimization Using Priori Knowledge

Wei

2017

Advances in Intelligent Systems and Computing

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ExNa: an efficient search pattern for semantic search engines

Cited by 5 publications

References 24 publications

Building Lightweight Semantic Search Engines

Building Lightweight Semantic Search Engines

Big data‐related technologies and applications

Textual Keyword Optimization Using Priori Knowledge

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