Pub Date : 2011-06-28DOI: 10.1109/STAIR.2011.5995798
S. Rahman, N. Omar, M. J. Aziz
This paper discusses on how a head modifier of Noun Phrases (NPs) in Malay sentence can be detected from the four combination of phrases, such as a noun phrase (frasa nama) and noun phrase (frasa nama), a noun phrase and verb phrase (frasa kerja), a noun phrase and adjective phrase (frasa adjektif) and, a noun phrase and prepositional phrase (frasa sendi). Most of the sentences in Malay have compound nouns. The position of the head within a compound often depends on the order of the word, i.e. the most common order of constituents in Malay phrases, where nouns are modified by adjectives, verbs, other nouns and prepositional. We also investigated the relative contribution of the modifier and the head noun in noun compounds of different other related examples in Malay sentence.
{"title":"A fundamental study on detecting head modifier noun phrases in Malay sentence","authors":"S. Rahman, N. Omar, M. J. Aziz","doi":"10.1109/STAIR.2011.5995798","DOIUrl":"https://doi.org/10.1109/STAIR.2011.5995798","url":null,"abstract":"This paper discusses on how a head modifier of Noun Phrases (NPs) in Malay sentence can be detected from the four combination of phrases, such as a noun phrase (frasa nama) and noun phrase (frasa nama), a noun phrase and verb phrase (frasa kerja), a noun phrase and adjective phrase (frasa adjektif) and, a noun phrase and prepositional phrase (frasa sendi). Most of the sentences in Malay have compound nouns. The position of the head within a compound often depends on the order of the word, i.e. the most common order of constituents in Malay phrases, where nouns are modified by adjectives, verbs, other nouns and prepositional. We also investigated the relative contribution of the modifier and the head noun in noun compounds of different other related examples in Malay sentence.","PeriodicalId":376671,"journal":{"name":"2011 International Conference on Semantic Technology and Information Retrieval","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117012489","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-06-28DOI: 10.1109/STAIR.2011.5995763
M. Farouk, Mitsuru Ishizuka
Representing web data into a machine understandable format is a curtail task for the next generation of the web. Most of solutions are relying on ontologies. However, there are many problems of using ontologies. This paper proposes an approach to represent dynamic web page contents retrieved from underlying database, into Concept Description Language (CDL) semantic format. This format does not depend on ontologies. However, CDL describes semantic structure of web content based on a set of predefined concepts and semantic relations. A prototype of the proposed approach is implemented to show visibility of the proposed approach.
{"title":"Semantic structure content for dynamic web pages","authors":"M. Farouk, Mitsuru Ishizuka","doi":"10.1109/STAIR.2011.5995763","DOIUrl":"https://doi.org/10.1109/STAIR.2011.5995763","url":null,"abstract":"Representing web data into a machine understandable format is a curtail task for the next generation of the web. Most of solutions are relying on ontologies. However, there are many problems of using ontologies. This paper proposes an approach to represent dynamic web page contents retrieved from underlying database, into Concept Description Language (CDL) semantic format. This format does not depend on ontologies. However, CDL describes semantic structure of web content based on a set of predefined concepts and semantic relations. A prototype of the proposed approach is implemented to show visibility of the proposed approach.","PeriodicalId":376671,"journal":{"name":"2011 International Conference on Semantic Technology and Information Retrieval","volume":"161 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115432722","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-06-28DOI: 10.1109/STAIR.2011.5995800
M. Yusoff, J. Jaafar, A. Mahmood
KM is a new field especially for the community college environment. The other thing is the knowledge in community college environment has not been captured, collaborated and managed systematically. Realizing the value and importance of KM approach the researcher has identified several goals to be achieved to come out with a viable KM framework to support the current activities of knowledge transfer in community college environment. Four different techniques were used including observation, small talk, interview & field notes and survey. The transferring of knowledge activities happen within the community college and across to the local community and their alliances with different approach. Knowledge management is a practicable and relevance for the community college as they operate as a lifelong learning and training center. Furthermore community college is the agent for the Malaysians government to develop the local community socioeconomic via knowledge transfer and knowledge sharing.
{"title":"KM practice in community college — KM framework towards KMS","authors":"M. Yusoff, J. Jaafar, A. Mahmood","doi":"10.1109/STAIR.2011.5995800","DOIUrl":"https://doi.org/10.1109/STAIR.2011.5995800","url":null,"abstract":"KM is a new field especially for the community college environment. The other thing is the knowledge in community college environment has not been captured, collaborated and managed systematically. Realizing the value and importance of KM approach the researcher has identified several goals to be achieved to come out with a viable KM framework to support the current activities of knowledge transfer in community college environment. Four different techniques were used including observation, small talk, interview & field notes and survey. The transferring of knowledge activities happen within the community college and across to the local community and their alliances with different approach. Knowledge management is a practicable and relevance for the community college as they operate as a lifelong learning and training center. Furthermore community college is the agent for the Malaysians government to develop the local community socioeconomic via knowledge transfer and knowledge sharing.","PeriodicalId":376671,"journal":{"name":"2011 International Conference on Semantic Technology and Information Retrieval","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126139443","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-06-28DOI: 10.1109/STAIR.2011.5995762
S. A. Fadzli, R. Setchi
The study presented in this paper focuses on the preprocessing stage of image retrieval by proposing an ontology-based indexing approach which captures the meaning of image annotations by extracting the semantic importance of the words in them. The indexing algorithm is based on the classic vector-space model that is adapted by employing index weighting and a word sense disambiguation. It uses sets of Semantic DNA, extracted from a lexical ontology, to represent the images in a vector space. As discussed in the paper, the use of Semantic DNA in text-based image retrieval aims to overcome some of the major drawbacks of well known traditional approaches such as ‘bags of words’ and term frequency-(TF) based indexing. The proposed approach is evaluated by comparing the indexing achieved using the proposed semantic algorithm with results obtained using a traditional TF-based indexing in vector space model (VSM) with singular value decomposition (SVD) technique. The experimental results show that the proposed ontology-based approach generates a better-quality index which captures the conceptual meaning of the image annotations.
{"title":"Ontology-based indexing of annotated images using semantic DNA and vector space model","authors":"S. A. Fadzli, R. Setchi","doi":"10.1109/STAIR.2011.5995762","DOIUrl":"https://doi.org/10.1109/STAIR.2011.5995762","url":null,"abstract":"The study presented in this paper focuses on the preprocessing stage of image retrieval by proposing an ontology-based indexing approach which captures the meaning of image annotations by extracting the semantic importance of the words in them. The indexing algorithm is based on the classic vector-space model that is adapted by employing index weighting and a word sense disambiguation. It uses sets of Semantic DNA, extracted from a lexical ontology, to represent the images in a vector space. As discussed in the paper, the use of Semantic DNA in text-based image retrieval aims to overcome some of the major drawbacks of well known traditional approaches such as ‘bags of words’ and term frequency-(TF) based indexing. The proposed approach is evaluated by comparing the indexing achieved using the proposed semantic algorithm with results obtained using a traditional TF-based indexing in vector space model (VSM) with singular value decomposition (SVD) technique. The experimental results show that the proposed ontology-based approach generates a better-quality index which captures the conceptual meaning of the image annotations.","PeriodicalId":376671,"journal":{"name":"2011 International Conference on Semantic Technology and Information Retrieval","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128589393","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-06-28DOI: 10.1109/STAIR.2011.5995799
A. Hatem, N. Omar, Khalid Shaker
The Arabic language is a Semitic language and it exhibits systematic but complex morphological structure based on root-pattern design. The aim of the present paper is to propose a transfer-based approach using morphological analysis which induces a syntactic symmetry and morphology to improve machine translation system between Arabic and English. Both languages are highly asymmetrical in terms of morphological structures. Our system supposes segmentation the word in the morphologically rich language into the sequence of prefix (es)-stem-suffix (es). The system identifies morphemes to be merged or deleted in the morphologically rich language to make the desired morphological and syntactic symmetry. The technique applied aims to improve Arabic-to-English translation quality.
{"title":"Morphological analysis for rule based machine translation","authors":"A. Hatem, N. Omar, Khalid Shaker","doi":"10.1109/STAIR.2011.5995799","DOIUrl":"https://doi.org/10.1109/STAIR.2011.5995799","url":null,"abstract":"The Arabic language is a Semitic language and it exhibits systematic but complex morphological structure based on root-pattern design. The aim of the present paper is to propose a transfer-based approach using morphological analysis which induces a syntactic symmetry and morphology to improve machine translation system between Arabic and English. Both languages are highly asymmetrical in terms of morphological structures. Our system supposes segmentation the word in the morphologically rich language into the sequence of prefix (es)-stem-suffix (es). The system identifies morphemes to be merged or deleted in the morphologically rich language to make the desired morphological and syntactic symmetry. The technique applied aims to improve Arabic-to-English translation quality.","PeriodicalId":376671,"journal":{"name":"2011 International Conference on Semantic Technology and Information Retrieval","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114313623","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Conceptual summarization aims to provide a database which comprises an abstraction of the entire document content. To effectively provide conceptual summarization, we have presented an approach that is used for conceptual querying. The approach is based on utilizing an ontology for similarity measure between concepts and the nearest neighborhood clustering algorithm for concepts clustering. The results show an improvement in the runtime and tolerant as regards noise.
{"title":"Conceptual summarization using ontologies and nearest neighborhood clustering","authors":"Elaheh Gavagsaz, Mahmoud Naghibzadeh, Mehrdad Jalali","doi":"10.1109/STAIR.2011.5995756","DOIUrl":"https://doi.org/10.1109/STAIR.2011.5995756","url":null,"abstract":"Conceptual summarization aims to provide a database which comprises an abstraction of the entire document content. To effectively provide conceptual summarization, we have presented an approach that is used for conceptual querying. The approach is based on utilizing an ontology for similarity measure between concepts and the nearest neighborhood clustering algorithm for concepts clustering. The results show an improvement in the runtime and tolerant as regards noise.","PeriodicalId":376671,"journal":{"name":"2011 International Conference on Semantic Technology and Information Retrieval","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129003757","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-06-28DOI: 10.1109/STAIR.2011.5995794
H. Mohamed, N. Omar, M. J. Aziz
Assigning part of speech to running words in a sentence is one of the pipeline processes in Natural Language Processing (NLP) tasks. In this paper, a statistical POS tagger using trigram Hidden Markov Model for tagging Malay language sentences is examined. The problem of the tagger approach is to predict the POS for unseen words in the training corpus that can guess word's POS based on their surrounding information. The predictor has been built based on information of word's prefixes, suffixes or combination of them. Linear successive abstraction has been used for smoothing the probability distribution of part of speech for unknown Malay words given their prefixes or suffixes information. However, for the combination of prefixes and suffixes information, the joint probability distribution has been used. The best performance to predict POS of unknown words are obtained through prefixes information by seeing the first three characters of the words. The accuracy of the tagging is 67.9%. This shows that a statistical tagger for Malay language using Hidden Markov Model is able to predict any unknown word's POS at some promising accuracy.
{"title":"Statistical malay part-of-speech (POS) tagger using Hidden Markov approach","authors":"H. Mohamed, N. Omar, M. J. Aziz","doi":"10.1109/STAIR.2011.5995794","DOIUrl":"https://doi.org/10.1109/STAIR.2011.5995794","url":null,"abstract":"Assigning part of speech to running words in a sentence is one of the pipeline processes in Natural Language Processing (NLP) tasks. In this paper, a statistical POS tagger using trigram Hidden Markov Model for tagging Malay language sentences is examined. The problem of the tagger approach is to predict the POS for unseen words in the training corpus that can guess word's POS based on their surrounding information. The predictor has been built based on information of word's prefixes, suffixes or combination of them. Linear successive abstraction has been used for smoothing the probability distribution of part of speech for unknown Malay words given their prefixes or suffixes information. However, for the combination of prefixes and suffixes information, the joint probability distribution has been used. The best performance to predict POS of unknown words are obtained through prefixes information by seeing the first three characters of the words. The accuracy of the tagging is 67.9%. This shows that a statistical tagger for Malay language using Hidden Markov Model is able to predict any unknown word's POS at some promising accuracy.","PeriodicalId":376671,"journal":{"name":"2011 International Conference on Semantic Technology and Information Retrieval","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131809478","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-06-28DOI: 10.1109/STAIR.2011.5995759
Siraya Sitthisarn, L. Lau, P. Dew
In the last few years, there has been an increase in the amount of information stored in semantically enriched knowledge bases, represented in RDF format. These improve the accuracy of search results when the queries are semantically formal. However framing such queries is inappropriate for inexperience users because they require specialist knowledge of ontology and syntax. In this paper, we explore an approach that automates the process of converting a conventional keyword search into a semantically formal query in order to find an expert on a semantically enriched knowledge base. A case study on expert witness discovery for the resolution of a legal dispute is chosen as the domain of interest and a system named SKengine is implemented to illustrate the approach. As well as providing an easy user interface, our experiment shows that SKengine can retrieve expert witness information with higher precision and higher recall, compared with the other system, with the same interface, implemented by a vector model approach.
{"title":"Semantic keyword search for expert witness discovery","authors":"Siraya Sitthisarn, L. Lau, P. Dew","doi":"10.1109/STAIR.2011.5995759","DOIUrl":"https://doi.org/10.1109/STAIR.2011.5995759","url":null,"abstract":"In the last few years, there has been an increase in the amount of information stored in semantically enriched knowledge bases, represented in RDF format. These improve the accuracy of search results when the queries are semantically formal. However framing such queries is inappropriate for inexperience users because they require specialist knowledge of ontology and syntax. In this paper, we explore an approach that automates the process of converting a conventional keyword search into a semantically formal query in order to find an expert on a semantically enriched knowledge base. A case study on expert witness discovery for the resolution of a legal dispute is chosen as the domain of interest and a system named SKengine is implemented to illustrate the approach. As well as providing an easy user interface, our experiment shows that SKengine can retrieve expert witness information with higher precision and higher recall, compared with the other system, with the same interface, implemented by a vector model approach.","PeriodicalId":376671,"journal":{"name":"2011 International Conference on Semantic Technology and Information Retrieval","volume":"12 4-5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132915076","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-06-28DOI: 10.1109/STAIR.2011.5995760
M. Amirhosseini, J. Salim
Ontology researchers struggle to propose various methods and methodology in ontology evaluation as reference sources for ontology engineering and evaluating process. In this paper, we intend to explain a new ontology evaluation methodology (i.e., OntoAbsolute) which it is proposed to evaluate structural domains in semantic relations and concepts in upper, middle and lower ontologies. In 2007, a modern method was proposed in quantitative evaluation of the structural domains in knowledge organizations based on Kant's Epistemology. OntoAbsolute relies on the modern quantitative evaluation method to evaluate simplicity and unity concepts (i.e., meta-properties) in the structural domains in concepts and their relations via proposed criteria and related measures. OntoAbsolute has a capacity to develop new criteria and measures to access cognitive results in ontology as a whole. OntoAbsolute is similar to OntoClean in terms of domain-independent feature and meta-properties usage and also OntoAbsolute consists of the same structure to classify the characteristics (i.e., multi-level framework) with OntoMetric.
{"title":"OntoAbsolute as a ontology evaluation methodology in analysis of the structural domains in upper, middle and lower level ontologies","authors":"M. Amirhosseini, J. Salim","doi":"10.1109/STAIR.2011.5995760","DOIUrl":"https://doi.org/10.1109/STAIR.2011.5995760","url":null,"abstract":"Ontology researchers struggle to propose various methods and methodology in ontology evaluation as reference sources for ontology engineering and evaluating process. In this paper, we intend to explain a new ontology evaluation methodology (i.e., OntoAbsolute) which it is proposed to evaluate structural domains in semantic relations and concepts in upper, middle and lower ontologies. In 2007, a modern method was proposed in quantitative evaluation of the structural domains in knowledge organizations based on Kant's Epistemology. OntoAbsolute relies on the modern quantitative evaluation method to evaluate simplicity and unity concepts (i.e., meta-properties) in the structural domains in concepts and their relations via proposed criteria and related measures. OntoAbsolute has a capacity to develop new criteria and measures to access cognitive results in ontology as a whole. OntoAbsolute is similar to OntoClean in terms of domain-independent feature and meta-properties usage and also OntoAbsolute consists of the same structure to classify the characteristics (i.e., multi-level framework) with OntoMetric.","PeriodicalId":376671,"journal":{"name":"2011 International Conference on Semantic Technology and Information Retrieval","volume":"25 9","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120968759","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-06-28DOI: 10.1109/STAIR.2011.5995765
Norfaradilla Wahid, E. Pardede
XML databases are commonly used for representing data with more complex structures than traditional relational data. Like in any data model, it is very important to ensure that the contents of the database always valid even after any attempt of updates. XML Updates validation is a process of checking the correctness of XML documents, in terms of satisfying their constraints, after updates operations. The validation can be generally categorized into structural and semantic validation. The first validation is to ensure that all XML nodes in the documents conform to structural information in its associated schema. Meanwhile, the second validation checks the integrity constraints of the documents, and it involve various factors such as the functional dependencies, domain constraint, inheritance, etc. In this paper, we provide a preliminary survey of semantic validation w.r.t XML Updates. The work of validation usually applied either upon any attempt of updates or in a scheduled period. We compare the output gain by works in terms of operation of update, the composition, types of constraint, etc. It shows that even though there are abundant of studies in this area, not much work has investigated a complete semantic validation of different semantic constraints. The constraints are still strongly dependent on structural information of documents and lied only on the data access tier of application architecture.
{"title":"XML semantic constraint validation for XML updates: A survey","authors":"Norfaradilla Wahid, E. Pardede","doi":"10.1109/STAIR.2011.5995765","DOIUrl":"https://doi.org/10.1109/STAIR.2011.5995765","url":null,"abstract":"XML databases are commonly used for representing data with more complex structures than traditional relational data. Like in any data model, it is very important to ensure that the contents of the database always valid even after any attempt of updates. XML Updates validation is a process of checking the correctness of XML documents, in terms of satisfying their constraints, after updates operations. The validation can be generally categorized into structural and semantic validation. The first validation is to ensure that all XML nodes in the documents conform to structural information in its associated schema. Meanwhile, the second validation checks the integrity constraints of the documents, and it involve various factors such as the functional dependencies, domain constraint, inheritance, etc. In this paper, we provide a preliminary survey of semantic validation w.r.t XML Updates. The work of validation usually applied either upon any attempt of updates or in a scheduled period. We compare the output gain by works in terms of operation of update, the composition, types of constraint, etc. It shows that even though there are abundant of studies in this area, not much work has investigated a complete semantic validation of different semantic constraints. The constraints are still strongly dependent on structural information of documents and lied only on the data access tier of application architecture.","PeriodicalId":376671,"journal":{"name":"2011 International Conference on Semantic Technology and Information Retrieval","volume":"32 5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121008757","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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