By James G. Shanahan, Yan Qu, Janyce Wiebe
The chapters during this ebook deal with perspective, have an effect on, and subjective opinion. a number of conceptual versions and computational equipment are awarded, together with distinguishing attitudes from easy actual assertions; distinguishing among the author’s experiences from experiences of alternative people’s reviews; and distinguishing among explicitly and implicitly said attitudes. moreover, many purposes are defined that promise to profit from the facility to appreciate attitudes and have an effect on, comparable to indexing and retrieval of files by way of opinion; computerized query answering approximately reviews; research of sentiment within the media and in chat groups; interpreting shopper discourse in remedy and counseling; selecting family members among medical texts; producing extra acceptable texts; and growing writers’ aids. as well as English texts, the gathering comprises reviews of French, jap, and Portuguese texts. The chapters are prolonged and revised types of papers awarded on the American organization for man made Intelligence (AAAI) Spring Symposium on Exploring perspective and have an effect on in textual content, which came about in March 2004 at Stanford college. The symposium, and the publication which grew out it, characterize a primary foray into this zone and a stability between conceptual types, computational tools, and purposes.
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Additional info for Computing Attitude and Affect in Text: Theory and Applications (The Information Retrieval Series)
Utility texts such as newspaper articles expressly avoid using belief reports because they represent an evaluation by the reporter which the reader might not share. Instead, newspaper articles offer evidence reports which only give rise to beliefs through an additional interpretation step. (Gerard, 2000) presents one possible way to transform these evidence reports into first potential, and eventually held beliefs. , 1997, Rapaport, 1986)). 6. Extension to Other Attribution Reported speech is an important issue in its own right, but it can moreover serve as a model for attribution in different registers, as well.
1997) Quasi-Indexicals and Knowledge Reports, Cognitive Science 21(1). 63-107. , and Duan, L. (1997) Probabilistic Event Categorization, In Recent Advances in Natural Language Processing (RANLP-97). 163-170. Tsigov Chark. Wilks, Y. and Ballim, A. (1991) Artificial Believers. Erlbaum, Norwood. , and Bergler, S. (2003) Fuzzy Coreference Resolution for Summarization. In Proceedings of the International Symposium on Reference Resolution and Its Applications on Question Answering and Summarization (ARQAS 2003).
In (3), the experiencer, signaled by we, is the clinic and the attitude could be interpreted as knowledge shared by experiencer and addressee. In (4a), the experiencer could be interpreted as the clinic again, although it was not explicitly signaled; (4a) continues (Wiebe, 1994) the experiencer of the current POV. However, we claim that the explanatory information provided in (4b) and (4d) is the voice of the genetic counselor and the attitude for those phrases could be interpreted as knowledge that the experiencer believes the addressee does not share with the experiencer.