SYSTEM AND METHODS THEREOF FOR PROVIDING AN ADVERTISEMENT PLACEMENT RECOMMENDATION BASED ON TRENDS
A method for bidding for an advertisement placement of an on-line advertisement. The method comprises identifying at least a trend for at least a first term appearing in at least one data source; extracting at least a second term from at least one on-line advertisement; performing a correlation analysis, responsive of a desired trend of the at least first term, between the at least first term and the at least second term; and placing a bid for placement of the at least one on-line advertisement for any one of the at least first term and the at least second term that demonstrates a predefined correlation.
1 . A method for bidding for an advertisement placement of an on-line advertisement, comprising:
identifying at least a trend for at least a first term appearing in at least one data source;
extracting at least a second term from at least one on-line advertisement;
performing a correlation analysis, responsive of a desired trend of the at least first term, between the at least first term and the at least second term; and
placing a bid for placement of the at least one on-line advertisement for any one of the at least first term and the at least second term that demonstrates a predefined correlation.
2 . The method of claim 1 , wherein the at least one or more data sources includes at least one of: a social network, a blog, a web page, a news feed.
3 . The method of claim 1 , further comprising:
tracking continuously the at least one-line advertisement to determine if its performance is per at least a bidding expectation.
4 . The method of claim 3 , wherein the performance of the at least on-line advertisement being tracked includes at least one of: a number of clicks and a number of conversions to sale from the advertisement.
5 . The method of claim 3 , further comprising:
providing a recommendation whether to increase or decrease the at least an advertisement bid based on at least one of: past results, and a profile prediction.
6 . The method of claim 4 , wherein the past results include tracked performance collected for the at least one on-line advertisement and other similar on-line advertisements, wherein the profile prediction identifies profile characteristics for the at least one on-line advertisement to predict future behavior based on similar profiles.
7 . The method of claim 1 , wherein identifying the trend for at least a first term comprises:
performing at least a statistical analysis respective of the at least one term.
8 . The method of claim 7 , wherein the at least one term is at least a term taxonomy generated by associating between at least one non-sentiment phrase and at least one sentiment phrase appearing in the at least one data source.
9 . The method of claim 7 , further comprising:
generating a notification when the trend changes.
10 . The method of claim 9 , further comprising:
generating the notification when the trend crosses a predetermined threshold.
11 . The method of claim 1 , wherein the predefined correlation is at least one of: a minimum threshold of a positive correlation and a maximum threshold for a negative correlation.
12 . A computer software product containing a plurality of instructions embedded in a non-transitory computer readable medium that when executed by a computing device causing to execute the method of claim 1 .
13 . A system for bidding for an advertisement placement of an on-line advertisement, comprising:
a network interface enabling an access to one or more data sources through a network;
a first mining unit for collection of textual content from the one or more data sources and generation of at least a first term;
an analysis unit for identifying a trend for the at least first term;
a second mining unit for extracting at least a second term from an at least one on-line advertisement;
an analysis unit for correlating between the at least first term and the at least second term performed responsive of a desired trend of the at least first term; and
an output unit for placement of a bid for at least an advertisement placement for any one of the at least first term and the at least second term that demonstrates a predefined correlation.
14 . The system of claim 13 , wherein each of the one or more data sources is at least one of: a social network, a blog, a web page, and a news feed.
15 . The system of claim 13 , wherein the analysis unit continuously tracks the at least one on-line advertisement to determine if its performance is per at least a bidding expectation.
16 . The system of claim 13 , wherein the analysis unit further provides a recommendation to increase or decrease advertisement expenditure.
17 . The system of claim 13 , wherein the analysis unit further provides a notification when the trend changes from expectation.
18 . The system of claim 17 , wherein the analysis unit further provides a notification when the trend crosses a predetermined threshold.
19 . The system of claim 13 , wherein the first mining unit and the second mining units are implemented into a single mining unit.
20 . The system of claim 13 , further comprising:
a storage unit for storing at least one of: the at least first term, the at least second term, the correlation between the at least first term and the at least second term, the trend of the at least first term, and the bid for the advertisement placement.
21 . The system of claim 13 , wherein the predefined correlation is at least one of: a minimum threshold of a positive correlation and a maximum threshold for a negative correlation.