A Study on Semantic Searching, Semantic Search Engines and Technologies Used for Semantic Search Engines

Rashid, Junaid; Nisar, Muhammad Wasif

doi:10.5815/ijitcs.2016.10.10

Cited by 9 publications

(4 citation statements)

References 16 publications

(13 reference statements)

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“…Feature optimization gave the highest accuracy of 99.65%, which is a remarkable achievement ( 56 ). Software quality ( 57 – 59 ) and semantic methods ( 60 , 61 ) are also used in algorithm evaluations. A hybrid approach combines different AI techniques and evaluates them as a single algorithm.…”

Section: Literature Reviewmentioning

confidence: 99%

An Augmented Artificial Intelligence Approach for Chronic Diseases Prediction

Rashid

Batool

Kim

et al. 2022

Front. Public Health

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Chronic diseases are increasing in prevalence and mortality worldwide. Early diagnosis has therefore become an important research area to enhance patient survival rates. Several research studies have reported classification approaches for specific disease prediction. In this paper, we propose a novel augmented artificial intelligence approach using an artificial neural network (ANN) with particle swarm optimization (PSO) to predict five prevalent chronic diseases including breast cancer, diabetes, heart attack, hepatitis, and kidney disease. Seven classification algorithms are compared to evaluate the proposed model's prediction performance. The ANN prediction model constructed with a PSO based feature extraction approach outperforms other state-of-the-art classification approaches when evaluated with accuracy. Our proposed approach gave the highest accuracy of 99.67%, with the PSO. However, the classification model's performance is found to depend on the attributes of data used for classification. Our results are compared with various chronic disease datasets and shown to outperform other benchmark approaches. In addition, our optimized ANN processing is shown to require less time compared to random forest (RF), deep learning and support vector machine (SVM) based methods. Our study could play a role for early diagnosis of chronic diseases in hospitals, including through development of online diagnosis systems.

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Section: Literature Reviewmentioning

confidence: 99%

An Augmented Artificial Intelligence Approach for Chronic Diseases Prediction

Rashid

Batool

Kim

et al. 2022

Front. Public Health

Self Cite

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“…We included articles based on the following inclusion criteria: (1) peer-reviewed, full-length articles written in English, and (2) articles published in the selected databases between 2014 and 2021. We excluded studies related to EHR interoperability, core ontology-based semantic searching or search engines, and artificial intelligence-based text processing for the latent semantic analysis [ 23 , 24 , 25 ]. Therefore, the search resulted in peer-reviewed, full-length articles on PHR architectures, models, and systems/implementations with or without semantic standards.…”

Section: Related Workmentioning

confidence: 99%

HL7 FHIR with SNOMED-CT to Achieve Semantic and Structural Interoperability in Personal Health Data: A Proof-of-Concept Study

Chatterjee

Pahari

Prinz

2022

Sensors

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Heterogeneity is a problem in storing and exchanging data in a digital health information system (HIS) following semantic and structural integrity. The existing literature shows different methods to overcome this problem. Fast healthcare interoperable resources (FHIR) as a structural standard may explain other information models, (e.g., personal, physiological, and behavioral data from heterogeneous sources, such as activity sensors, questionnaires, and interviews) with semantic vocabularies, (e.g., Systematized Nomenclature of Medicine—Clinical Terms (SNOMED-CT)) to connect personal health data to an electronic health record (EHR). We design and develop an intuitive health coaching (eCoach) smartphone application to prove the concept. We combine HL7 FHIR and SNOMED-CT vocabularies to exchange personal health data in JavaScript object notion (JSON). This study explores and analyzes our attempt to design and implement a structurally and logically compatible tethered personal health record (PHR) that allows bidirectional communication with an EHR. Our eCoach prototype implements most PHR-S FM functions as an interoperability quality standard. Its end-to-end (E2E) data are protected with a TSD (Services for Sensitive Data) security mechanism. We achieve 0% data loss and 0% unreliable performances during data transfer between PHR and EHR. Furthermore, this experimental study shows the effectiveness of FHIR modular resources toward flexible management of data components in the PHR (eCoach) prototype.

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“…1, 106-111 (2020) www.astesj.com Special Issue on Multidisciplinary Sciences and Engineering retrieve relevant information. To do so, a new layer could be added to the so called syntactic search engines [12] This paper presents the Web and SW technologies along with the Keyword and Semantic search engines. Keyword Search Engines (KSE)s are presented in section 2, section 3 reveals SSEs.…”

Section: Introductionmentioning

confidence: 99%

Comparative Study of Semantic and Keyword Based Search Engines

Hussan¹

2020

Adv. sci. technol. eng. syst. j.

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Day by day, the data on the web becomes very huge which makes it difficult to find relevant information. Search engines are one of the successful factors that can retrieve information from the Web. The process of seeking information by search engines helps users find information on the internet, however it is not an easy task to find the exact information from this massive data available on the Web. Semantic Web technology has an ability to focus on metadata rather than syntax, which made the semantic search engines to search for the meaning of keywords instead of the keyword syntax. Consequently, an effective role of performance in conventional search engines can be achieved by rising the accuracy of information returned by a search query. In this paper, a survey for syntactic-based search engines and semantic-based search engines are studied, a comprehensive comparison between the two is presented, finally, their technologies are compared and discussed.

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A Study on Semantic Searching, Semantic Search Engines and Technologies Used for Semantic Search Engines

Cited by 9 publications

References 16 publications

An Augmented Artificial Intelligence Approach for Chronic Diseases Prediction

An Augmented Artificial Intelligence Approach for Chronic Diseases Prediction

HL7 FHIR with SNOMED-CT to Achieve Semantic and Structural Interoperability in Personal Health Data: A Proof-of-Concept Study

Comparative Study of Semantic and Keyword Based Search Engines

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