Advertising campaigns utilizing streaming analytics

Abstract

The present invention provides methods and systems for use in advertising campaigns and advertisement targeting. Techniques are provided in which streams of data, including communications data, are sampled, such as during transmission to intended recipients. Sampled data may be analyzed and used to determine topics of interest. Sampled data may be analyzed or filtered to determine data suspected of being of particular significance or relevance in determining topics of interest. Determined topics of interest may be used in advertisement targeting as part of an advertising campaign.

1 - 20 . (canceled) 
     
     
         21 . A computerized method comprising:
 sampling one or more streams of electronic data, the electronic data comprising user communications data, to obtain sample data, wherein the sampling comprises sensing and detecting user communications data comprising user-generated content data streams that are in transmission to, but not yet received by, intended recipients;   analyzing the user-generated content data streams in the sample data, wherein the analyzing includes identifying suspect data;   based on the analyzing of the user-generated content data streams in the sample data, modifying the sampling during at least one period based on a determination that the suspect data is more likely to be concentrated during the at least one period than during other periods, wherein the modifying of the sampling is determined by utilizing one or more analytic correlation applications in detecting patterns, and wherein the patterns include one or more time-based or frequency-based patterns associated with the user-generated content data streams;   based on the suspect data obtained, selecting electronic advertisements for serving to targeted electronic device users; and   serving the selected electronic advertisements to the targeted electronic device users.   
     
     
         22 . The method of  claim 21 , wherein multiple sampling techniques are applied to one or more data streams. 
     
     
         23 . The method of  claim 22 , wherein the multiple sampling techniques are performed serially. 
     
     
         24 . The method of  claim 22 , wherein the multiple sampling techniques are performed in a compound manner. 
     
     
         25 . The method of  claim 22 , wherein the multiple sampling techniques are performed concurrently. 
     
     
         26 . The method of  claim 21 , wherein the modifying is based on one or more feedback mechanism predictive models or machine learning models. 
     
     
         27 . The method of  claim 21 , wherein the modifying includes increasing one or more sampling frequencies or rates. 
     
     
         28 . The method of  claim 21 , wherein the one or more streams of electronic data are from one geographic location or from multiple geographically distributed locations. 
     
     
         29 . The method of  claim 21 , wherein the sampling comprises monitoring, at one or more locations, the one or more streams of electronic data during transmission. 
     
     
         30 . The method of  claim 29 , wherein the sample data comprises one or more streams of electronic data at one or more cell phone transmission or reception nodes. 
     
     
         31 . The method of  claim 29 , wherein the sample data is obtained from one or more repeaters, computing systems, satellites, transmission systems, or receiving systems, and wherein the sample data may include one or more of video data, audio data, voice data, gaming data, social networking data, or blog data. 
     
     
         32 . The method of  claim 29 , wherein the sample data comprises one or more streams of electronic data from a cloud computing database or cloud computing data center. 
     
     
         33 . The method of  claim 21 , further comprising:
 sampling a plurality of streams of electronic data; and   integrating data from the plurality of streams.   
     
     
         34 . The method of  claim 21 , wherein the sampling comprises intercepting sample data related to a plurality of data modes, wherein the data modes may comprise any of voice, audio, video, gaming, social network or blogging. 
     
     
         35 . The method of  claim 34 , further comprising sampling the one or more streams of electronic data at one or more intervals, wherein the one or more intervals may be determined based on one or more parameters or one or more algorithms, and wherein the one or more parameters or one or more algorithms may include or incorporate any of sampling time, sampling frequency, or sampling data analytics. 
     
     
         36 . The method of  claim 21 , wherein the identifying of the suspect data includes determining the suspect data to be of significance or relevance in determining topics of interest to electronic device users. 
     
     
         37 . The method of  claim 21 , wherein the sampling takes place at a same location as a data source or on a same data source system as a data source. 
     
     
         38 . A system comprising:
 one or more server computers coupled to a network; and   one or more databases coupled to the one or more server computers;   wherein the one or more server computers are configured to:
 sample one or more streams of electronic data, the electronic data comprising user communications data, to obtain sample data, wherein the sampling comprises sensing and detecting user communications data comprising user-generated content data streams that are in transmission to, but not yet received by, intended recipients; 
 analyze the user-generated content data streams in the sample data, wherein the analyzing includes identifying suspect data; 
 based on the analyzing of the user-generated content data streams in the sample data, modify the sampling during at least one period based on a determination that the suspect data is more likely to be concentrated during the at least one period than during other periods, wherein the modifying of the sampling is determined by utilizing one or more analytic correlation applications in detecting patterns, and wherein the patterns include one or more time-based or frequency-based patterns associated with the user-generated content data streams; 
 based on the suspect data obtained, select electronic advertisements for serving to targeted electronic device users; and 
 serve the selected electronic advertisements to the targeted electronic device users. 
   
     
     
         39 . The system of  claim 38 , further comprising sampling the one or more streams of electronic data via one or more devices installed at one or more cell phone transmission or reception systems. 
     
     
         40 . The system of  claim 38 , further comprising sampling the one or more streams of electronic data from a cloud computing system or cloud, and wherein the streams of data can include any of voice data, video data, voice data, audio data, gaming data, social network data, or blog data. 
     
     
         41 . A non-transitory computer readable storage medium or media having stored instructions thereon for causing a computer to execute a method, the method comprising:
 sampling one or more streams of electronic data, the electronic data comprising user communications data, to obtain sample data, wherein the sampling comprises sensing and detecting user communications data comprising user-generated content data streams that are in transmission to, but not yet received by, intended recipients;   analyzing the user-generated content data streams in the sample data, wherein the analyzing includes identifying suspect data;   based on the analyzing of the user-generated content data streams in the sample data, modifying the sampling during at least one period based on a determination that the suspect data is more likely to be concentrated during the at least one period than during other periods, wherein the modifying of the sampling is determined by utilizing one or more analytic correlation applications in detecting patterns, and wherein the patterns include one or more time-based or frequency-based patterns associated with the user-generated content data streams;   based on the suspect data obtained, selecting electronic advertisements for serving to targeted electronic device users; and   serving the selected electronic advertisements to the targeted electronic device users, the serving including causing an advertisement serving system to initiate or modify an automated advertising campaign that includes the selected electronic advertisements.