System and method using text features for click prediction of sponsored search advertisements

A computer-implemented method for click prediction of online advertising, comprising:

• inputting at least one word feature of a search query into a click prediction model to obtain a plurality of click probabilities for a plurality of pairs of the search query and an advertisement;
• obtaining the plurality of click probabilities for the plurality of pairs of the search query and the advertisement;
• determining a list of advertisements ranked by an expected value representing a product of a bid and one of the plurality of click probabilities for the plurality of pairs of the search query and the advertisement;
• serving the list of advertisements ranked by the expected value for display with results of the search query;
• and
• pricing the list of advertisements in an online search keyword auction.

A computer system for click prediction of online advertising, comprising:

• means for receiving a plurality of click feedback features and a plurality of word pair features of a search query and a plurality of advertisements;
• means for generating, from the plurality of click feedback features and from the plurality of word pair features of the search query and the plurality of advertisements, a click prediction model that predicts a click probability for each of a plurality of pairs of the search query and an advertisement of the plurality of advertisements;
• and
• means for outputting the click prediction model that predicts the click probability for each of the plurality of pairs of the search query and the advertisement of the plurality of advertisements.