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Recognizing Emotional Content of Emails as a byproduct of Natural Language Processing-based Metadata Extraction
Abstract
This paper describes a metadata extraction technique based on natural language processing (NLP) which extracts personalized information from email communications between financial analysts and their clients. Personalized means connecting users with content in a personally meaningful way to create, grow, and retain online relationships. Personalization often results in the creation of user profiles that store individuals preferences regarding goods or services offered by various e-commerce merchants. We developed an automatic metadata extraction system designed to process textual data such as emails, discussion group postings, or chat group transcriptions. The focus of this paper is the recognition of emotional contents such as mood and urgency, which are embedded in the business communications, as metadata.
- keywords
- Information Extraction, Metadata, Emotional Content, 메타데이터, 정보추출, 감성정보, 자연어처리, Information Extraction, Metadata, Emotional Content
Reference
N. 1992. MUC-4 Evaluation Metrics. Proceedings of the Fourth Message Understand-ing Conference. , -.
Some universals in language usage. Cambridge University Press.. , -.
(2004). A probabilistic framework for recognizing and affecting emotions. Proceedings of the AAAI 2004 Spring Symposium on Architectures for Modeling Emotions. , -.
(2005). An exploration of human emotion perception from short texts. Artificial Intelli-gence and Psychology Project Report.. , -.
(2004). Emotions: From brain to robot. Trends in Cognitive Science. 8(12), 554-561.
(2003). Perception of e-mail personality at zeroacquaintance Extraver-sion takes care of itself but neuroticism is more of a worry. Proceedings of the 25th Annual Conference of the Cognitive Science Society. , 456-461.
(2004). BDIE: a BDI like architecture with emotional capabilities. Architectures for modeling emotion: Cross-Disciplinary founda-tions. , -.
(2000). Flaming: A white paper. , -.
(2002). Combining acoustic and language informa-tion for emotion recognition. Proceedings of International Conference on Spoken Language Processing. , 873-876.
MUC-3 1991. Proceedings of the Third Message Understanding Conference. San Diego. , -.
MUC-4 1992. Proceedings of the Fourth Message Understanding Conference. McLean. , -.
MUC-5 1993. Proceedings of the Fifth Message Understanding Conference. Baltimore. , -.
(1995). Proceedings of the Sixth Message Understanding Conference. Columbia. , -.
Automated Tools for Building and Extending Clinical Methods. In Hammond. , -.
(2000). CHronological information Extraction SyStem (CHESS).. , -.
(2006.). Online Available http://www.eudora.com/email/features/moodwatch.html. , -.
(2004). Discerning emotions in texts. Proceeding of the 2004 AAAI Symposium on Exploring Attitude and Affect in Text. , -.
Computer Man-agement of Narrative Data. Reading. , -.
(usa.). J.R. 1969. Speech Acts an Essay in the Philosophy of Language. Cambridge University Press. NY. , -.
(2000). There Are Myriad Ways to Get Personal. Internet Week Online. , -.
A. 1985. Toward a consensual structure of mood. Psychological Bulle-tin. , 219-235.
(2003). Towards answering opinion questions: separating facts from opinions and identifying the polarity of opinion sentences. , -.
(2000). Do you know what personalization means? Gartner Group T-10-9346.. , -.
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