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AssigneeInternational Business Machines Corporation
InventorsJeonghee Yi, Tetsuya Nasukawa
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A method and system for extracting opinions about a subject of interest from a text document in which each sentence is analyzed individually to identify the opinions. The most relevant feature terms related to the subject are extracted from the document based on their relevancy scores. Candidate feature terms are definite noun phrases at the beginning of the sentences. For each sentence that refers to the subject or a feature term, the invention determines whether the sentence includes an opinion polarity about the subject or the feature term. The opinion polarity is detected by identifying opinion terms in the sentence using an opinion dictionary or an opinion rule base, parsing the sentence with an English parser to identify grammatical components in the sentence and their relationships, and finding a matching entry in the dictionary or the rule base.
A method for extracting opinions about a subject of interest from a text document having a plurality of sentences, the subject associated with a plurality of features, the method comprising the steps of:
The method as recited in claim 3, wherein the opinion skeleton includes a feature term and an opinion term referring to said feature term.
A system for extracting opinions about a subject of interest from a text document having a plurality of sentences, the subject associated with a plurality of features, the system comprising:
A computer-program product for use with a computer for extracting opinions about a subject of interest from a text document having a plurality of sentences, the subject associated with a plurality of features, the computer-program product comprising:
Dependencies are inferred from the claim text.