Research on Web Query Translation based on Ontology

Wang, Xin; Wang, Ying

doi:10.4304/jsw.7.12.2849-2856

Cited by 4 publications

(2 citation statements)

References 13 publications

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“…The Jena2 provides a series of interfaces which store in the database of the content [5,6]. You can also directly have access to visit the data in the Ontology through these interfaces.…”

Section: The Main Information Storagementioning

confidence: 99%

Ontology-based English-Mongolian Machine Translation System Design and Implementation

Gong¹,

Guan²,

Zhang³

2017

dtetr

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ABSTRACT Ontology is as a detailed description of things, which is able to link the properties of things as well as clearly depicted the relationship between different things. Ambiguity often occurs in machine translation, the Ontology has a good effect in eliminating ambiguity. By constructing a domain ontology dictionary, summarizing common sentence of English and Mongolian as well as using dependency parsing sentence structure to complete the English machine translation into Mongolian, it is to verify the role of the Ontology to eliminate ambiguity in terms of machine translation. A SYSTEM DESIGNThis paper makes ontology-based English-Mongolian machine translation as experimental requirements so as to eliminating ambiguity in the process of machine translation through verifying this experiment. Experimental system design principles are as follows:(1) English -Mongolian Machine Translation uses the field of ontology to express semantic center. Building the Ontology must fully understand the field. The field of vocabulary can be covered the entire field. Ontology must include all common features of the field so as to playing an important role in the translation process.(2) Construction of field dictionary is an important part of the machine translation system, which contains all relevant terms in the field. Construction of the field can reflect whether the domain ontology meets its demand by constructing dictionary.(3) The English Mongolian Machine Translation System using the template translation. By summarizing the common English sentence and comparing with the corresponding Mongolian sentence, the translation template is got.

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“…The Jena2 provides a series of interfaces which store in the database of the content [5,6]. You can also directly have access to visit the data in the Ontology through these interfaces.…”

Section: The Main Information Storagementioning

confidence: 99%

Ontology-based English-Mongolian Machine Translation System Design and Implementation

Gong¹,

Guan²,

Zhang³

2017

dtetr

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“…Hyponymy relations play a crucial role in various natural language processing systems, such as systems for machine translation, information retrieval, and intelligent query. Especially, hyponymy relations are important in the identification of ontologies, knowledge bases, and lexicons [1] [2].…”

Section: Introductionmentioning

confidence: 99%

Spatial Structure Analysis and Identification of Candidate Hyponymy Relations

Liu¹,

Diao²

2013

JSW

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Automatic acquisition of semantic relations is an important problem in knowledge acquisition. We present a method of spatial structure analysis of candidate Chinese hyponymy based on concept space and use them to identify candidate hyponymy. Firstly a group of candidate hyponymy relations is imported into concept space. Secondly we analyze the basic spatial structure of concept space including concept nodes and relation edges. More identified features based on the spatial structure analysis are given and used to identify hyponymy relations. Experimental results show that the spatial structure is very useful to the identification of hyponymy.

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