Search engine for textual content and non-textual content
First Claim
Patent Images
1. A method performed by a search engine system (SES), the method comprising:
- receiving, at the SES, a search request transmitted by a client device, wherein said search request includes one or more query terms;
determining, by the SES, a query vector based on said one or more query terms;
determining, by the SES, a first set of tag vectors for a first set of tags associated with a first segment of a first non-textual content item;
determining, by the SES, a second set of tag vectors for a second set of tags associated with a second segment of said first non-textual content item;
determining, by the SES, a first segment vector for said first segment by summing said first set of tag vectors;
determining, by the SES, a second segment vector for said second segment by summing said second set of tag vectors;
calculating, by the SES, a first segment search score based on a result of a comparison of said first segment vector to said query vector;
calculating, by the SES, a second segment search score based on a result of a comparison of said second segment vector to said query vector; and
comparing said first segment search score and said second segment search score,whereinone or more vectors of the first and second sets of tag vectors is a weighted tag vector,the weighted tag vector is obtained by multiplying an initial tag vector with a feature score,the feature score is determined based on a feature type of a tag, andthe feature type is one of image, audio, video, and text.
1 Assignment
0 Petitions
Accused Products
Abstract
A search engine system that can match a search request to not only a specific content item (e.g., video file), but also to a single component of a content item. For instance, using a video content item as an example, the search engine system can match a specific search request to not only a specific video within a collection of videos, but also to a single moment within a video, a video segment, and a group of videos.
-
Citations
21 Claims
-
1. A method performed by a search engine system (SES), the method comprising:
-
receiving, at the SES, a search request transmitted by a client device, wherein said search request includes one or more query terms; determining, by the SES, a query vector based on said one or more query terms; determining, by the SES, a first set of tag vectors for a first set of tags associated with a first segment of a first non-textual content item; determining, by the SES, a second set of tag vectors for a second set of tags associated with a second segment of said first non-textual content item; determining, by the SES, a first segment vector for said first segment by summing said first set of tag vectors; determining, by the SES, a second segment vector for said second segment by summing said second set of tag vectors; calculating, by the SES, a first segment search score based on a result of a comparison of said first segment vector to said query vector; calculating, by the SES, a second segment search score based on a result of a comparison of said second segment vector to said query vector; and comparing said first segment search score and said second segment search score, wherein one or more vectors of the first and second sets of tag vectors is a weighted tag vector, the weighted tag vector is obtained by multiplying an initial tag vector with a feature score, the feature score is determined based on a feature type of a tag, and the feature type is one of image, audio, video, and text. - View Dependent Claims (2, 3)
-
-
4. A method performed by a search engine system (SES), the method comprising:
-
receiving, at the SES, a search request transmitted by a client device, wherein said search request includes one or more query terms; determining, by the SES, a query vector based on said one or more query terms; determining, by the SES, a first weighted tag vector based on said one or more query terms and a first tag, wherein said first tag is linked with a first feature located in a first segment of a non-textual content item; determining, by the SES, a second weighted tag vector based on said one or more query terms and a second tag, wherein said second tag is linked with a second feature located in a second segment of the non-textual content item; calculating, by the SES, a first tag search score based on a result of a comparison of said first weighted tag vector to said query vector; and calculating, by the SES, a second tag search score based on a result of a comparison of said second weighted tag vector to said query vector, wherein said first weighted tag vector is obtained by multiplying a first initial tag vector with a feature score; the feature score is determined based on a feature type of said first tag, and the feature type is one of image, audio, video, and text. - View Dependent Claims (5, 6)
-
-
7. A search engine system (SES) comprising:
-
a data storage system and a data processing system, said data storage system comprising instructions executable by the data processing system whereby the SES is operative to; determine a query vector based on query terms included in a search request; determine a first set of tag vectors for a first set of tags associated with a first segment of a first non-textual content item; determine a second set of tag vectors for a second set of tags associated with a second segment of said first non-textual content item; determine a first segment vector for said first segment by summing said first set of tag vectors; determine a second segment vector for said second segment by summing said second set of tag vectors; calculate a first segment search score based on a result of a comparison of said first segment vector to said query vector; calculate a second segment search score based on a result of a comparison of said second segment vector to said query vector; and compare said first segment search score and said second segment search score, wherein the SES is operative to; calculate said first segment search score by, at least, calculating;
(VQ·
VS1)/(∥
VQ∥
∥
VS1∥
), where VQ is said query vector, and VS1 is said first segment vector, andcalculate said second segment search score by, at least, calculating;
(VQ·
VS2)/(∥
VQ∥
∥
VS2∥
), where VS2 is said second segment vector. - View Dependent Claims (8, 9, 10, 11, 12, 13)
-
-
14. A search engine system (SES) comprising:
-
a data storage system and a data processing system, said data storage system comprising instructions executable by the data processing system whereby the SES is operative to; determine a query vector based on one or more query terms included in a search request; determine a first weighted tag vector based on said one or more query terms and a first tag, wherein said first tag is linked with a first feature located in a first segment of a first non-textual content item; determine a second weighted tag vector based on said one or more query terms and a second tag, wherein said second tag is linked with a second feature located in a second segment of said first non-textual content item; calculate a first tag search score based on a result of a comparison of said first weighted tag vector to said query vector; and calculate a second tag search score based on a result of a comparison of said second weighted tag vector to said query vector, wherein said first weighted tag vector is obtained by multiplying a first initial tag vector with a feature score, the feature score is determined based on a feature type of said first tag, and the feature type is one of image, audio, video, and text, wherein the SES is operative to; calculate said first tag search score by, at least, calculating;
(VQ·
VT1)/(∥
VQ∥
∥
VT1∥
), where VQ is said query vector, and VT1 is said first weighted tag vector, anddetermine said second tag search score by, at least, calculating;
(VQ·
VT2)/(∥
VQ∥
∥
VT2∥
), where VT2 is said second weighted tag vector. - View Dependent Claims (15, 16, 17, 18, 19)
-
-
20. A computer program product comprising a non-transitory computer readable medium storing computer instructions for searching content, the computer instructions comprising:
-
instructions for determining a query vector based on query terms included in a search request; instructions for determining a first set of tag vectors for a first set of tags associated with a first segment of a non-textual content item; instructions for determining a second set of tag vectors for a second set of tags associated with a second segment of said non-textual content item; instructions for determining a first segment vector for said first segment by summing said first set of tag vectors; instructions for determining a second segment vector for said second segment by summing said second set of tag vectors; instructions for calculating a first segment search score based on a result of a comparison of said first segment vector to said query vector; instructions for calculating a second segment search score based on a result of a comparison of said second segment vector to said query vector; and instructions for comparing said first segment search score and said second segment search score, wherein one or more vectors of the first and second sets of tag vectors is a weighted tag vector, the weighted tag vector is obtained by multiplying an initial tag vector with a feature score, the feature score is determined based on a feature type of a tag, and the feature type is one of image, audio, video, and text.
-
-
21. A computer program product comprising a non-transitory computer readable medium storing computer instructions for searching content, the computer instructions comprising:
-
instructions for determining a query vector based on one or more query terms included in a search request; instructions for determining a first weighted tag vector based on said one or more query terms and a first tag, wherein said first tag is linked with a first feature located in a first segment of a non-textual content item; instructions for determining a second weighted tag vector based on said one or more query terms and a second tag, wherein said second tag is linked with a second feature located in a second segment of the non-textual content item; instructions for calculating a first tag search score based on a result of a comparison of said first weighted tag vector to said query vector; and instructions for calculating a second tag search score based on a result of a comparison of said second weighted tag vector to said query vector, wherein said first weighted tag vector is obtained by multiplying a first initial tag vector with a feature score, the feature score is determined based on a feature type of said first tag, and the feature type is one of image, audio, video, and text.
-
Specification