METHODS AND SYSTEMS FOR PREDICTING FUTURE DATA
Described herein are methods and systems for predicting data, such as values. A first interface is configured to receive an indication as to how many search queries have been submit that are related to a first item of content. A second interface is configured to receive information related to web traffic associated with the first item of content. A third interface is configured to receive news information correlated with the first item of content. An engine is configured to estimate a value for the first item content at least partly based on information received from the first, second, and/or third interface.
1 . A method for predicting advertisement content prices, the method comprising:
accessing information regarding a plurality of users' interest in a first advertising content;
accessing information regarding historical pricing trends;
accessing information indicating a correlation with respect to a first event-type and interest in the first content; and
providing a pricing estimate for the use of the first content with respect to an advertisement using at least a portion of the accessed information regarding users' interest, pricing trends, and correlations.
2 . The method as defined in claim 1 , wherein the pricing estimate is based at least in part on a quantity of page views of a Web page associated with the first advertising content.
3 . The method as defined in claim 1 , wherein the pricing estimate is based at least in part on a quantity of search queries related to the content.
4 . The method as defined in claim 1 , wherein the pricing estimate is based at least in part on website traffic.
5 . The method as defined in claim 1 , wherein the pricing estimate is based at least in part on a content of a user on a website hosting the content.
6 . The method as defined in claim 1 , wherein the pricing estimate is based at least in part on references to the content on one or more user web logs.
7 . The method as defined in claim 1 , wherein the pricing estimate is based at least in part on content of a first news feed.
8 . The method as defined in claim 1 , wherein the pricing estimate is based at least in part on IP addresses of content viewers.
9 . The method as defined in claim 1 , wherein the pricing estimate is based at least in part on one or more user purchase histories.
10 . The method as defined in claim 1 , wherein the pricing estimate is based at least in part on locations of users viewing the content.
11 . The method as defined in claim 1 , wherein the pricing estimate is based at least in part on a Really Simple Syndication feed.
12 . The method as defined in claim 1 , wherein the pricing estimate is based at least in part on an ATOM feed.
13 . The method as defined in claim 1 , the method further comprising calculating a local maxima in revenue.
14 . Programmatic code stored on a computer readable medium, that when executed is configured to:
access information regarding a plurality of users' interest in a first advertising content;
access information regarding historical pricing trends;
access information indicating a correlation with respect to a first event-type and interest in the first content; and
provide a pricing estimate for the use of the first content with respect to an advertisement.
15 . The code as defined in claim 14 , wherein the pricing estimate is based at least in part on a quantity of page views of a Web page associated with the first advertising content.
16 . The code as defined in claim 14 , wherein the pricing estimate is based at least in part on a quantity of search queries related to the content.
17 . The code as defined in claim 14 , wherein the pricing estimate is based at least in part on website traffic.
18 . The code as defined in claim 14 , wherein the pricing estimate is based at least in part on a content of a user on a website hosting the content.
19 . The code as defined in claim 14 , wherein the pricing estimate is based at least in part on references to the content on one or more user web logs.
20 . The code as defined in claim 14 , wherein the pricing estimate is based at least in part on content of a first news feed.
21 . The code as defined in claim 14 , wherein the pricing estimate is based at least in part on IP addresses of content viewers.
22 . The code as defined in claim 14 , wherein the pricing estimate is based at least in part on one or more user purchase histories.
23 . The code as defined in claim 14 , wherein the pricing estimate is based at least in part on locations of users viewing the content.
24 . The code as defined in claim 14 , wherein the pricing estimate is based at least in part on a Really Simple Syndication feed.
25 . The code as defined in claim 14 , wherein the pricing estimate is based at least in part on an ATOM feed.
26 . The code as defined in claim 14 , further configured to comprise a local maxima in revenue.
27 . A computer-based content pricing estimator system, comprising:
a first interface configured to receive an indication as to how many search queries have been submit that are related to a first item of content;
a second interface configured to receive information related to web traffic associated with the first item of content;
a third interface configured to receive news information correlated with the first item of content; and
a pricing engine configured to estimate a price for the first item content at least partly based on information received from the first, second, and/or third interface.
28 . The system as defined in claim 27 , wherein the pricing engine is further configured to generate the estimate at least partly based on blog references related to the content.
29 . The system as defined in claim 27 , wherein the pricing engine is further configured to generate the estimate at least partly based on page views of a page related to the content.
30 . The system as defined in claim 27 , wherein the pricing engine is further configured to generate the estimate at least partly based on a purchase history.
31 . The system as defined in claim 27 , wherein the pricing engine is further configured to generate the estimate based at least in part on locations of users viewing the content.
32 . The system as defined in claim 27 , wherein the pricing engine is further configured to generate the estimate based at least in part on a Really Simple Syndication feed.
33 . The system as defined in claim 27 , wherein the pricing engine is further configured to generate the estimate based at least in part on an ATOM feed.
34 . The system as defined in claim 27 , wherein the pricing engine is further configured to identify a local maxima in revenue.