System and method for sentiment-based text classification and relevancy ranking
First Claim
1. A computer implemented method of assessing human sentiment from a group of documents, each document in the group of documents having a plurality of terms and being digitally represented in a computer, said method comprising:
- receiving a group of documents, each document in the group of documents comprising a context of a plurality of terms and all documents in the group of documents representative of a particular topic;
constructing a document sentiment vector space from the group of documents, wherein construction of the document sentiment vector space comprises;
assessing sentimentality of each document in the group of documents toward the topic;
identifying sentimentally significant documents in the group of documents with heightened sentimentality toward the particular topic; and
labeling sentimentally significant documents by including a unique sentiment binding term in the context of the plurality of terms;
representing each document in the group of documents in the document sentiment vector space;
defining a region of sentimental significance in the document sentiment vector space based on an occurrence of document representations for sentimentally significant documents with the unique sentiment binding term;
receiving a query string; and
assessing sentimentality of the query string by comparing a representation of the query string for semantic similarity to the region of sentimental significance in the document sentiment vector space.
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Abstract
The sentimental significance of a group of historical documents related to a topic is assessed with respect to change in an extrinsic metric for the topic. A unique sentiment binding label is included to the content of actions documents that are determined to have sentimental significance and the group of documents is inserted into a historical document sentiment vector space for the topic. Action areas in the vector space are defined from the locations of action documents and singular sentiment vector may be created that describes the cumulative action area. Newly published documents are sentiment-scored by semantically comparing them to documents in the space and/or to the singular sentiment vector. The sentiment scores for the newly published documents are supplemented by human sentiment assessment of the documents and a sentiment time decay factor is applied to the supplemented sentiment score of each newly published documents. User queries are received and a set of sentiment-ranked documents is returned with the highest age-adjusted sentiment scores.
211 Citations
34 Claims
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1. A computer implemented method of assessing human sentiment from a group of documents, each document in the group of documents having a plurality of terms and being digitally represented in a computer, said method comprising:
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receiving a group of documents, each document in the group of documents comprising a context of a plurality of terms and all documents in the group of documents representative of a particular topic; constructing a document sentiment vector space from the group of documents, wherein construction of the document sentiment vector space comprises; assessing sentimentality of each document in the group of documents toward the topic; identifying sentimentally significant documents in the group of documents with heightened sentimentality toward the particular topic; and labeling sentimentally significant documents by including a unique sentiment binding term in the context of the plurality of terms; representing each document in the group of documents in the document sentiment vector space; defining a region of sentimental significance in the document sentiment vector space based on an occurrence of document representations for sentimentally significant documents with the unique sentiment binding term; receiving a query string; and assessing sentimentality of the query string by comparing a representation of the query string for semantic similarity to the region of sentimental significance in the document sentiment vector space. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34)
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Specification