Abstract: There is provided, in accordance with some embodiments, a computerized method executed by one or more hardware processors, comprising receiving interaction records, where some of the interaction records comprise a cookie value, a URL (Uniform Resource Locator), and a time stamp. The computerized method comprises computing, from the interaction records, interaction sequences each comprising user interactions. Each adjacent pair of user interactions in each interaction sequence has the same unique user identifier, and attributing at least two interaction values to respective user interactions, where the sum of attributed interaction values is equal to the total value, and where each interaction value is computed using rule(s), respective property values, and the total value. The computerized method comprises updating one or more bidding property on an advertising platform based on the attribution, where the bidding property comprises an advertisement bid value or an advertisement keyword.

Abstract: Positioning an element in a computer-based document by determining, for each of a plurality of positions of a target element displayed in a plurality of computer-based documents, a first performance value associated with the target element, and a second performance value associated with a non-target element displayed in the plurality of computer-based documents, selecting one of the positions that meets predefined selection criteria as applied to the performance values, determining, for a position factor associated with the target element, a position factor value associated with the selected position, and assigning the position factor value to the position factor.

Abstract: A method comprising using at least one hardware processor for: receiving first a set of keywords associated with a first advertising platform; receiving second a set of keywords associated with a second advertising platform; defining binary relations between the first and second sets of keywords; applying formal concept analysis (FCA) to the binary relations, to produce a concept lattice; and updating the concept lattice responsive to changes in the first or second sets of keywords.

Abstract: A method for trend detection in online advertising, the method comprising using at least one hardware processor for: receiving current performance data associated with a current online ad entity; determining a class with which the current online ad entity is associated, by applying a clustering algorithm to one or more attributes associated with the current online ad entity; fetching historical performance data associated with one or more historical online ad entities associated with the class; and comparing a behavior of the current performance data with a behavior of the historical performance data, to detect an abnormal trend in the behavior of the current online ad entity.

Abstract: Temporal budget optimization in online advertising, comprising: receiving a user selection of a time period in the future and of a joint budget for M online ad entities, wherein M?2; forecasting, based on historical data associated with the M online ad entities, a future ROI function of each of the M online ad entities, wherein the future ROI function provides revenue as a function of cost; computing individual budgets for the M online ad entities by finding M points to serve as the individual budgets, each of the M points being a certain cost in the future ROI function of a different one of the M online ad entities, such that: the M points have approximately equal derivatives, and a sum of the costs at the M points is approximately equal to the joint budget; and during the time period: tracking a spending of the individual budgets, to determine remaining individual budgets, periodically updating the future ROI functions based on newly-accumulated historical data associated with the M online ad entities, and

Abstract: A method for temporal budget optimization in online advertising, the method comprising using at least one hardware processor for: receiving a user selection of a time period in the future; forecasting, based on historical data associated with an online ad entity, a future return on investment (ROI) function of the online ad entity; receiving a user selection of a point on the ROI function, thereby setting a budget for the time period; and during the time period: (a) tracking a spending of the budget, to determine a remaining budget, (b) periodically updating the future ROI function based on newly-accumulated historical data associated with the online ad entity, and (c) periodically adjusting, in an online advertising platform, a spending pace of the remaining budget, wherein the adjusting is based on the updated future ROI function.

Abstract: Positioning an element in a computer-based document by determining, for each of a plurality of positions of a target element displayed in a plurality of computer-based documents, a first performance value associated with the target element, and a second performance value associated with a non-target element displayed in the plurality of computer-based documents, selecting one of the positions that meets predefined selection criteria as applied to the performance values, determining, for a position factor associated with the target element, a position factor value associated with the selected position, and assigning the position factor value to the position factor.

Abstract: A system operable to attribute a value associated with a series of user interactions to individual interactions in the series, the system including: (a) an interface, configured to obtain information of interactions which are included in the series of interactions; and (b) a processor on which an attribution module is implemented, the attribution module is configured to attribute an apportionment of the value to each out of a plurality of interactions of the series, based on a calibrated attribution scheme and on properties relating to at least one interaction out of the series of interactions, thereby enabling efficient utilization of communication resources.