The advent of Web 2.0 has led to an increase in user-generated content on the Web. This has provided an extensive collection of free-style texts with opinion expressions that could influence the decisions and actions ...The advent of Web 2.0 has led to an increase in user-generated content on the Web. This has provided an extensive collection of free-style texts with opinion expressions that could influence the decisions and actions of their readers. Providers of such content exert a certain level of influence on the receivers and this is evident from blog sites having effect on their readers＇ purchase decisions, political view points, financial planning, and others. By detecting the opinion expressed, we can identify the sentiments on the topics discussed and the influence exerted on the readers. In this paper, we introduce an automatic approach in deriving polarity pattern rules to detect sentiment polarity at the phrase level, and in addition consider the effects of the more complex relationships found between words in sentiment polarity classification. Recent sentiment analysis research has focused on the functional relations of words using typed dependency parsing, providing a refined analysis on the grammar and semantics of textual data. Heuristics are typically used to determine the typed dependency polarity patterns, which may not comprehensively identify all possible rules. We study the use of class sequential rules （CSRs） to automatically learn the typed dependency patterns, and benchmark the performance of CSR against a heuristic method. Preliminary results show CSR leads to further improvements in classification performance achieving over 80% F1 scores in the test eases. In addition, we observe more complex relationships between words that could influence phrase sentiment polarity, and further discuss on possible approaches to handle the effects of these complex relationships.展开更多
The present paper attempts to make a contrastive study on Chinese and English word order with a view of identifying the discrepancies and propose its significance to mutual translation.As to the research methodology,q...The present paper attempts to make a contrastive study on Chinese and English word order with a view of identifying the discrepancies and propose its significance to mutual translation.As to the research methodology,qualitative analysis and com parative analysis are adopted when the similarities and differences of the word order of English and Chinese are explained.It can be concluded that Chinese and English word order differs at the phrase level and sentence level:in terms of the discrepancies in phrase structure,they are mainly manifested in adverbial and attributive phrases;as to the discrepancies in sentence structure,they are reflected in simple,complex and special sentences.展开更多
文摘The advent of Web 2.0 has led to an increase in user-generated content on the Web. This has provided an extensive collection of free-style texts with opinion expressions that could influence the decisions and actions of their readers. Providers of such content exert a certain level of influence on the receivers and this is evident from blog sites having effect on their readers＇ purchase decisions, political view points, financial planning, and others. By detecting the opinion expressed, we can identify the sentiments on the topics discussed and the influence exerted on the readers. In this paper, we introduce an automatic approach in deriving polarity pattern rules to detect sentiment polarity at the phrase level, and in addition consider the effects of the more complex relationships found between words in sentiment polarity classification. Recent sentiment analysis research has focused on the functional relations of words using typed dependency parsing, providing a refined analysis on the grammar and semantics of textual data. Heuristics are typically used to determine the typed dependency polarity patterns, which may not comprehensively identify all possible rules. We study the use of class sequential rules （CSRs） to automatically learn the typed dependency patterns, and benchmark the performance of CSR against a heuristic method. Preliminary results show CSR leads to further improvements in classification performance achieving over 80% F1 scores in the test eases. In addition, we observe more complex relationships between words that could influence phrase sentiment polarity, and further discuss on possible approaches to handle the effects of these complex relationships.
文摘The present paper attempts to make a contrastive study on Chinese and English word order with a view of identifying the discrepancies and propose its significance to mutual translation.As to the research methodology,qualitative analysis and com parative analysis are adopted when the similarities and differences of the word order of English and Chinese are explained.It can be concluded that Chinese and English word order differs at the phrase level and sentence level:in terms of the discrepancies in phrase structure,they are mainly manifested in adverbial and attributive phrases;as to the discrepancies in sentence structure,they are reflected in simple,complex and special sentences.
