Sentiment prediction from textual data
First Claim
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1. A method to train data for sentiment prediction, comprising:
- at a device comprising one or more processors;
creating from a domain corpus a domain space that is a semantic representation of one or more identified areas of information;
creating from affective data an affective space that is a semantic representation of a plurality of sentiments;
generating a plurality of first affective anchors in the affective space, each first affective anchor corresponding to a respective sentiment in the affective space;
mapping the plurality of first affective anchors generated in the affective space onto respective locations in the domain space, wherein the mapping of the first affective anchors is performed by the one or more processors;
based on the respective locations to which the plurality of first affective anchors have been mapped in the domain space, generating a plurality of second affective anchors in the domain space, each second affective anchor corresponding to a respective sentiment in the domain space; and
providing the domain space and the second affective anchors for predicting sentiment of text.
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Abstract
A semantically organized domain space is created from a training corpus. Affective data are mapped onto the domain space to generate affective anchors for the domain space. A sentiment associated with an input text is determined based the affective anchors. A speech output may be generated from the input text based on the determined sentiment.
709 Citations
28 Claims
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1. A method to train data for sentiment prediction, comprising:
at a device comprising one or more processors; creating from a domain corpus a domain space that is a semantic representation of one or more identified areas of information; creating from affective data an affective space that is a semantic representation of a plurality of sentiments; generating a plurality of first affective anchors in the affective space, each first affective anchor corresponding to a respective sentiment in the affective space; mapping the plurality of first affective anchors generated in the affective space onto respective locations in the domain space, wherein the mapping of the first affective anchors is performed by the one or more processors; based on the respective locations to which the plurality of first affective anchors have been mapped in the domain space, generating a plurality of second affective anchors in the domain space, each second affective anchor corresponding to a respective sentiment in the domain space; and providing the domain space and the second affective anchors for predicting sentiment of text. - View Dependent Claims (2, 3, 4, 5, 6, 7)
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8. A non-transitory computer readable storage medium having instructions stored thereon that, when executed, cause a computer to:
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create from a domain corpus a domain space that is a semantic representation of one or more identified areas of information; create from affective data an affective space that is a semantic representation of a plurality of sentiments; generate a plurality of first affective anchors in the affective space, each first affective anchor corresponding to a respective sentiment in the affective space; map the plurality of first affective anchors generated in the affective space onto respective locations in the domain space; based on the respective locations to which the plurality of first affective anchors have been mapped in the domain space, generating a plurality of second affective anchors in the domain space, each second affective anchor corresponding to a respective sentiment in the domain space; and provide the domain space and the second affective anchors for predicting sentiment of text. - View Dependent Claims (9, 10, 11, 12, 13, 14)
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15. A system for training data for sentiment prediction, comprising:
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a memory to store a domain corpus associated with one or more identified areas of information, and affective data associated with a plurality of sentiments; a processor coupled to the memory; a latent semantic mapping (LSM) module to create from the domain corpus a domain space that is a semantic representation of the one or more identified areas of information, and to create from the affective data an affective space that is a semantic representation of the plurality of sentiments; and a mapping module to; generate a plurality of first affective anchors in the affective space, each first affective anchor corresponding to a respective sentiment in the affective space; map the plurality of first affective anchors generated in the affective space onto respective locations in the domain space; and based on the respective locations to which the plurality of first affective anchors have been mapped in the domain space, generate a plurality of second affective anchors in the domain space, each second affective anchor corresponding to a respective sentiment in the domain space. - View Dependent Claims (16, 17, 18, 19)
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20. A method to predict sentiment, comprising:
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at a device comprising one or more processors; receiving a first text; determining a representation of the first text in a domain space created from a domain corpus, wherein the domain space has one or more first affective anchors representing one or more sentiment categories, and wherein the first affective anchors are generated by;
generating a plurality of second affective anchors in an affective space, mapping the plurality of second affective anchors generated in the affective space to respective locations in the domain space, and generating the first affective anchors based on the respective locations in the domain space; anddetermining a sentiment associated with the first text based on the first affective anchors, wherein determining the sentiment associated with the first text is performed by the one or more processors. - View Dependent Claims (21, 22)
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23. A non-transitory machine readable storage medium having instructions stored thereon that, when executed, cause a computer to perform operations comprising:
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receiving a first text; determining a representation of the first text in a domain space created from a domain corpus, wherein the domain space has one or more first affective anchors representing sentiment categories, and wherein the first affective anchors are generated by generating a plurality of second affective anchors in an affective space, mapping the plurality of second affective anchors generated in the affective space to respective locations in the domain space, and generating the first affective anchors based on the respective locations in the domain space; and determining a sentiment associated with the first text based on the one or more first affective anchors in the domain space. - View Dependent Claims (24, 25)
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26. A system to predict sentiment, comprising:
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a processor; an input device to receive a first text; a memory coupled to the processor; a latent semantic mapping (LSM) module, stored in the memory, configured to determine a representation of the first text in a domain space created from a domain corpus, wherein the domain space has one or more first affective anchors representing sentiment categories and wherein the first affective anchors are generated by;
generating a plurality of second affective anchors in an affective space, mapping the plurality of second affective anchors generated in the affective space to respective locations in the domain space, and generating the first affective anchors based on the respective locations in the domain space; anda sentiment computation module configured to determine a sentiment associated with the first text based on the one or more first affective anchors. - View Dependent Claims (27, 28)
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Specification