Semantic Web: A Topic Specific Search

Kishan, Dharavath; Saritha, Sri Khetwat

doi:10.1109/itng.2012.29

Cited by 3 publications

(3 citation statements)

References 8 publications

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“…This paper proposed novel approach to create Ontology using clustering. The ontology is domain specific [6][7][8][9][10]. This ontological cluster model is tested on Tourism domain [4].…”

Section: Ontology Generation Using Clusteringmentioning

confidence: 99%

“…It is not possible to understand the relationship among terms specific to domain and use these relevant terms for better results [2]. Here Ontology plays very important role which allows user to search concepts rather than keywords [3][4][5][6][7][8]. This paper contributes to design the novel information retrieval interface by developing Ontology of specific domain using clustering.…”

Section: Introductionmentioning

confidence: 99%

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Onto Semantic Tourism Information Retrieval

Laddha¹,

Jawandhiya²

2018

IJET

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Semantic Search is an area of research which focuses on meaning of terms used in user query. Ontology plays significant role to define the concept and the relationship of terms in domain. Since the understanding of concepts is domain specific, Ontology creation is also domain specific. According to this argument, query interpreted in Tourism domain can have different meaning in some other domain. This paper presents a prototype of information retrieval interface using ontology which can save users time by rendering relevant, precise and efficient search results as compared to traditional search interfaces.

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“…This paper proposed novel approach to create Ontology using clustering. The ontology is domain specific [6][7][8][9][10]. This ontological cluster model is tested on Tourism domain [4].…”

Section: Ontology Generation Using Clusteringmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Onto Semantic Tourism Information Retrieval

Laddha¹,

Jawandhiya²

2018

IJET

View full text Add to dashboard Cite

show abstract

“…Ontologies are employed in a growing number of applications, especially websites, and have become the chosen template tool. The plan with the maintenance of theory is a large procedure [18][19][20][21][22][23][24]. Ecological storage, which has lately become a significant knowledge for theorizing, engages the automatic recognition of ideas in a region as well as the interconnection of ideas [25].…”

Section: Introductionmentioning

confidence: 99%

Development of a Machine Learning model for knowledge acquisition, relationship extraction and discovery in Domain Ontology Engineering

Guruvayur*¹,

Suchithra²

2019

IJRTE

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Creating a fast domain independent ontology through knowledge acquisition is a key problem to be addressed in the domain of knowledge engineering. Updating and validation is impossible without the intervention of domain experts, which is an expensive and tedious process. Thereby, an automatic system to model the ontology has become essential. This manuscript presents a machine learning model based on heterogeneous data from multiple domains including agriculture, health care, food and banking, etc. The proposed model creates a complete domain independent process that helps in populating the ontology automatically by extracting the text from multiple sources by applying natural language processing and various techniques of data extraction. The ontology instances are classified based on the domain. A Jaccord Relationship extraction process and the Neural Network Approval for Automated Theory is used for retrieval of data, automated indexing, mapping and knowledge discovery and rule generation. The results and solutions show the proposed model can automatically and efficiently construct automated Ontology

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Novel Concept of Query-Prototype and Query-Similarity for Semantic Search

Laddha

Jawandhiya²

2018

Communications in Computer and Information Science

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Semantic Web: A Topic Specific Search

Cited by 3 publications

References 8 publications

Onto Semantic Tourism Information Retrieval

Onto Semantic Tourism Information Retrieval

Development of a Machine Learning model for knowledge acquisition, relationship extraction and discovery in Domain Ontology Engineering

Novel Concept of Query-Prototype and Query-Similarity for Semantic Search

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