METHODS AND SYSTEMS FOR SEARCH ENGINES SELECTION & OPTIMIZATION

1 . A method for conducting a search, the method comprising:

receiving, at a computing device, a search profile having one or more search parameters, wherein the computing device contains a database of search engines;

selecting a subset of search engines from the database of search engines based on the one or more search parameters;

requesting the selected subset of search engines to conduct a search based on the one or more search parameters; and

receiving a search result from the selected subset of search engines.

2 . The method of claim 1 , wherein requesting the selected subset of search engines further comprises:

receiving real-time searching progress data from the selected subset of search engines in response to the request; and

selecting at least one search engine, from the selected subset of search engines, as a primary search engine based on the real-time searching progress data.

3 . The method of claim 2 , wherein real-time search progress data include one or more selected from the group consisting of a confidence rating, a searching progress indicator, a third-party verified indicator, a human-verified indicator, a quality indicator, a trending indicator, and a total viewing indicator.

4 . The method of claim 1 , wherein requesting the selected subset of search engines further comprises:

receiving a partial search result from the selected subset of search engines;

determining a trust rating for each of the selected subset of search engines based on the received partial results; and

selecting at least one search engine, from the selected subset of search engines, as a primary search engine based on the determined trust rating, wherein the trust rating is based on one or more of a confidence rating, a searching progress indicator, a third-party verified indicator, a human-verified indicator, a quality indicator, a trending indicator, and a total viewing indicator.

5 . The method of claim 4 , wherein the partial search result comprises substantially all of the result.

6 . The method of claim 1 , wherein each of the one or more search parameters comprises a search string and a search type indicator, wherein the subset of search engines is selected based on the search type indicator.

7 . The method of claim 6 , wherein the search type indicator includes one or more selected from the group consisting of a transcription search, a facial recognition search, a voice recognition search, an audio search, an object search, a sentiment search, and a keyword search.

8 . The method of claim 1 , further comprises:

matching attributes of the search profile with attributes of a training data set based on similarity between the attributes of the training data set and attributes of the one or more search parameters of the search profile; and

selecting the subset of search engines based on the matched training data.

9 . The method of claim 1 , wherein the selected subset of search engines comprises at least one search engine.

10 . The method of claim 9 , further comprises running at least one primary search engine and at least one secondary search engine simultaneously.

11 . The method of claim 1 , wherein the database of search engines comprises one or more transcription engines, facial recognition engines, object recognition engines, voice recognition engines, sentiment analysis engines, and keywords search engines.

12 . The method of claim 1 , further comprises sending a search termination request to search engines not selected as either the primary search engine or secondary processing engine.

13 . A non-transitory processor-readable medium having one or more instructions operational on a computing device, which when executed by a processor causes the processor to:

receive, at a computing device, a search profile having one or more search parameters, wherein the computing device contains a database of search engines;

select a subset of search engines from the database of search engines based on the one or more search parameters;

request the selected subset of search engines to conduct a search based on the one or more search parameters; and

receive a search result from the selected subset of search engines.

14 . The non-transitory processor-readable medium of claim 13 , further comprises instructions which when executed by a processor causes the processor to:

receive real-time searching progress data from the selected subset of search engines in response to the request; and

select at least one search engine, from the selected subset of search engines, as a primary search engine based on the real-time searching progress data.

15 . The non-transitory processor-readable medium of claim 14 , wherein real-time search progress data include one or more selected from the group consisting of a confidence rating, a searching progress indicator, a third-party verified indicator, a human-verified indicator, a quality indicator, a trending indicator, and a total viewing indicator.

16 . The non-transitory processor-readable medium of claim 13 , further comprises instructions which when executed by a processor causes the processor to:

receive a partial search result from the selected subset of search engines;

determine a trust rating for each of the selected subset of search engines based on the received partial results; and

select at least one search engine, from the selected subset of search engines, as a primary search engine based on the determined trust rating, wherein the trust rating is based on one or more of a confidence rating, a searching progress indicator, a third-party verified indicator, a human-verified indicator, a quality indicator, a trending indicator, and a total viewing indicator.

17 . (canceled)

18 . The non-transitory processor-readable medium of claim 13 , wherein each of the one or more search parameters comprises a search string and a search type indicator, wherein the subset of search engines is selected based on the search type indicator.

19 . The non-transitory processor-readable medium of claim 18 , wherein the search type indicator includes one or more selected from the group consisting of a transcription search, a facial recognition search, a voice recognition search, an audio search, an object search, a sentiment search, and a keyword search.

20 . The non-transitory processor-readable medium of claim 13 , further comprises instructions which when executed by a processor causes the processor to:

match attributes of the search profile with attributes of a training data set based on similarity between the attributes of the training data set and attributes of the one or more search parameters of the search profile; and

select the subset of search engines based on the matched training data.

21 . (canceled)

22 . The non-transitory processor-readable medium of claim 13 , wherein the database of search engines comprises one or more transcription engines, facial recognition engines, object recognition engines, voice recognition engines, sentiment analysis engines, and keywords search engines.

23 . (canceled)