Shifting semantic values of English phrases for classification
The researches of semantics (positive, negative, neutral) are performed for a long time and they are very important for many commercial applications, many scientific works, etc. In this paper we propose a new model to calculate the emotional values (or semantic scores) of English terms (English verb...
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Veröffentlicht in: | International journal of speech technology 2017-09, Vol.20 (3), p.509-533 |
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description | The researches of semantics (positive, negative, neutral) are performed for a long time and they are very important for many commercial applications, many scientific works, etc. In this paper we propose a new model to calculate the emotional values (or semantic scores) of English terms (English verbs, English nouns, English adjectives, English adverbs, etc.) as follows: firstly, we create our basis English emotional dictionary (called bEED) by using Sorensen measure (Sorensen coefficient, called SM) through Google search engine with AND operator and OR operator and secondly, many English adjective phrases, English adverb phrases and English verb phrases are created based on the English grammars (the English characteristics) by combining the English adverbs of degree with the English adjectives, the English adverbs and English verbs; finally, the valences of the English adverb phrases are identified by their specific contexts. The English phrases often bring the semantics which the values (or emotional scores) are not fixed and are changed when they appear in their different contexts. Therefore, the results of the sentiment classification are not high accuracy if the English phrases bring the emotions and their semantic values (or their sentiment scores) are not changed in any context. For those reasons, we propose many rules based on English language grammars to calculate the sentimental values of the English phrases bearing emotion in their specific contexts. The results of this work are widely used in applications and researches of the English semantic classification. |
doi_str_mv | 10.1007/s10772-017-9420-6 |
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The English phrases often bring the semantics which the values (or emotional scores) are not fixed and are changed when they appear in their different contexts. Therefore, the results of the sentiment classification are not high accuracy if the English phrases bring the emotions and their semantic values (or their sentiment scores) are not changed in any context. For those reasons, we propose many rules based on English language grammars to calculate the sentimental values of the English phrases bearing emotion in their specific contexts. 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The English phrases often bring the semantics which the values (or emotional scores) are not fixed and are changed when they appear in their different contexts. Therefore, the results of the sentiment classification are not high accuracy if the English phrases bring the emotions and their semantic values (or their sentiment scores) are not changed in any context. For those reasons, we propose many rules based on English language grammars to calculate the sentimental values of the English phrases bearing emotion in their specific contexts. The results of this work are widely used in applications and researches of the English semantic classification.</description><subject>Adjectives</subject><subject>Adverbs</subject><subject>Artificial Intelligence</subject><subject>Classification</subject><subject>Dictionaries</subject><subject>Emotions</subject><subject>Engineering</subject><subject>English language</subject><subject>Grammars</subject><subject>Language grammars</subject><subject>Mathematical analysis</subject><subject>Phrases</subject><subject>Predicate</subject><subject>Search engines</subject><subject>Semantics</subject><subject>Signal,Image and Speech Processing</subject><subject>Social Sciences</subject><subject>Verbs</subject><issn>1381-2416</issn><issn>1572-8110</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><recordid>eNp1kE9LAzEQxYMoWFc_gLcFz9FMZjfZXAQp9Q8UPKjnkGaTNmW7W5Ot4Lc3ZT148TTD4_3eDI-Qa2C3wJi8S8Ck5JSBpKrijIoTMoM6Kw0AO807NkB5BeKcXKS0ZYwpqfiM3L9tgh9Dvy6T25l-DLb8Mt3BpXLw5aJfdyFtyv0mmpQlP8TSdial4IM1Yxj6S3LmTZfc1e8syMfj4n3-TJevTy_zhyW1CGKkKGTbtpXCSqgK7cpXjailFUJyFMKYVSvrFhViI3wLtWk8ojPeyAYbDtxhQW6m3H0cPvN3o94Oh9jnkxoUl3WNMtMFgcll45BSdF7vY9iZ-K2B6WNNeqpJ55r0sSYtMsMnJmVvv3bxT_K_0A-tAGmG</recordid><startdate>20170901</startdate><enddate>20170901</enddate><creator>Phu, Vo Ngoc</creator><creator>Chau, Vo Thi Ngoc</creator><creator>Tran, Vo Thi Ngoc</creator><general>Springer US</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7T9</scope><orcidid>https://orcid.org/0000-0001-6047-9066</orcidid></search><sort><creationdate>20170901</creationdate><title>Shifting semantic values of English phrases for classification</title><author>Phu, Vo Ngoc ; Chau, Vo Thi Ngoc ; Tran, Vo Thi Ngoc</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c316t-367ddd49346943cbf48657c6672366aabd75d393386fd15a8f33eafa7838212e3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Adjectives</topic><topic>Adverbs</topic><topic>Artificial Intelligence</topic><topic>Classification</topic><topic>Dictionaries</topic><topic>Emotions</topic><topic>Engineering</topic><topic>English language</topic><topic>Grammars</topic><topic>Language grammars</topic><topic>Mathematical analysis</topic><topic>Phrases</topic><topic>Predicate</topic><topic>Search engines</topic><topic>Semantics</topic><topic>Signal,Image and Speech Processing</topic><topic>Social Sciences</topic><topic>Verbs</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Phu, Vo Ngoc</creatorcontrib><creatorcontrib>Chau, Vo Thi Ngoc</creatorcontrib><creatorcontrib>Tran, Vo Thi Ngoc</creatorcontrib><collection>CrossRef</collection><collection>Linguistics and Language Behavior Abstracts (LLBA)</collection><jtitle>International journal of speech technology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Phu, Vo Ngoc</au><au>Chau, Vo Thi Ngoc</au><au>Tran, Vo Thi Ngoc</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Shifting semantic values of English phrases for classification</atitle><jtitle>International journal of speech technology</jtitle><stitle>Int J Speech Technol</stitle><date>2017-09-01</date><risdate>2017</risdate><volume>20</volume><issue>3</issue><spage>509</spage><epage>533</epage><pages>509-533</pages><issn>1381-2416</issn><eissn>1572-8110</eissn><abstract>The researches of semantics (positive, negative, neutral) are performed for a long time and they are very important for many commercial applications, many scientific works, etc. In this paper we propose a new model to calculate the emotional values (or semantic scores) of English terms (English verbs, English nouns, English adjectives, English adverbs, etc.) as follows: firstly, we create our basis English emotional dictionary (called bEED) by using Sorensen measure (Sorensen coefficient, called SM) through Google search engine with AND operator and OR operator and secondly, many English adjective phrases, English adverb phrases and English verb phrases are created based on the English grammars (the English characteristics) by combining the English adverbs of degree with the English adjectives, the English adverbs and English verbs; finally, the valences of the English adverb phrases are identified by their specific contexts. The English phrases often bring the semantics which the values (or emotional scores) are not fixed and are changed when they appear in their different contexts. Therefore, the results of the sentiment classification are not high accuracy if the English phrases bring the emotions and their semantic values (or their sentiment scores) are not changed in any context. For those reasons, we propose many rules based on English language grammars to calculate the sentimental values of the English phrases bearing emotion in their specific contexts. The results of this work are widely used in applications and researches of the English semantic classification.</abstract><cop>New York</cop><pub>Springer US</pub><doi>10.1007/s10772-017-9420-6</doi><tpages>25</tpages><orcidid>https://orcid.org/0000-0001-6047-9066</orcidid></addata></record> |
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subjects | Adjectives Adverbs Artificial Intelligence Classification Dictionaries Emotions Engineering English language Grammars Language grammars Mathematical analysis Phrases Predicate Search engines Semantics Signal,Image and Speech Processing Social Sciences Verbs |
title | Shifting semantic values of English phrases for classification |
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