Patent ID: 9697196
Date: 2017-07-04
CPC Classifications: G06F

Claim:
1. A method implemented on a computer for enhancing machine-intelligence function of the computer by enabling the computer to discover hidden attributes associated with words in a raw text and producing a new type of data object with sentiment type markings, the method comprising: receiving a text content comprising multiple text units, each text unit comprising at least a portion of a phrase or a sentence consisting of multiple terms, each term comprising a word or a phrase in a language; identifying, in the text content, a text unit for assigning a derived sentiment type, wherein the text unit comprises a first term and a second term as components in the text unit, wherein the sentiment type of the text unit as a whole is unknown; discovering a first attribute as a first sentiment type associated with the first term, wherein the first attribute is not indicated in the text unit or in the text content when received, wherein the first attribute is represented by a first label or a first group membership associated with the first term, and is discovered from a data source external to the text content; discovering a second attribute as a second sentiment type associated with the second term, wherein the second attribute is not indicated in the text unit or in the text content when received, wherein the second attribute is represented by a second label or a second group membership associated with the second term, and is discovered from a data source external to the text content; wherein the first sentiment type and the second sentiment type each refers to a positive or negative sentiment but not a neutral sentiment; wherein neither the first term nor the second term includes the grammatical negator or the negation word of the language, and when the language is the English language, neither the first term nor the second term includes a syntactically or grammatically defined negator or negation word comprising the word “not” or “no”; performing one of the following to generate a derived sentiment type for the text unit as a whole, such that the derived sentiment type is different from either the first sentiment type or the second sentiment type, or both: (a) generating a negative sentiment type for the text unit as a whole if both the first sentiment type and the second sentiment type are positive, (b) generating a positive sentiment type for the text unit as a whole if both the first sentiment type and the second sentiment type are negative, (c) generating a negative sentiment type for the text unit as a whole if one of the first sentiment type and the second sentiment type is a positive sentiment type, and one of the first sentiment type and the second sentiment type is a negative sentiment type; and extracting, as a data object, the text unit from the text content with the derived sentiment attached to it, or displaying, in a user interface, the text unit as a whole with the derived sentiment indicated.