Abstract: A deal program life cycle system and method is disclosed. The deal program life cycle may oversee the issuance of deals from a deal program to consumers over the life cycle of the deal program. One or more aspects of the deal program may change during different periods of the life cycle of the deal program. For example, the deal program may include deal features, a number of units for deals, and relevance features for the deal program. The deal features, number of units of deals, and/or relevance features for the deal program may change during the different periods of the life cycle.

Abstract: A sales enhancement system and method is disclosed. The sales enhancement system is configured to use one or more deal program collections, which are groupings or compilations of deal programs. The sales enhancement system manages deal programs in the deal program collections at various stages of use including: associating a deal program with multiple deal program collections; determining the number of deals to assign to the different deal programs; using triggers to select which deal program collections to access; transmitting an offer for a deal; and processing acceptances of the offers.

Abstract: Electronic correspondence that includes one or more promotions may be generated for presenting to a consumer. In order to determine whether to present the electronic correspondence to the consumer, the promotions included in the electronic correspondences may be analyzed in terms of a probability the consumer will accept the promotions, a relevance level between the promotions and attributes of the consumer, a relevance level between the promotions and the consumer, a relevance level between the promotions and a set of goals or rules, among other similar terms. After the analysis, a determination may be made whether to send the electronic correspondence to the consumer. Similarly, the analysis may compare multiple electronic correspondences, and determine, based on the comparison, which of the multiple electronic correspondences to send to the consumer.

Abstract: In a promotion offering system, a consumer is more likely to purchase a promotion offering if the consumer finds the promotion to be interesting or fits a need of the consumer. In order to provide a more intelligent selection process for selecting promotions that are desirable to the consumer, a method and a promotion offering system for implementing the method are provided that takes into consideration a number of different factors associated with a consumer, including locations and deal types that are known or predicted to be of interest to the consumer, when determining one or more promotions to present to the consumer.

Abstract: A promotion offering system and method is disclosed. The promotion offering system and method selects consumers for a test promotion that has one or more attributes, and is configured to generate test data for multiple consumer groupings. The promotion offering system and method may use the test data in analyzing whether to send a promotion to a consumer. For example, the promotion offering system and method may use one algorithm to generate a list of ranked promotions, and may use the test data in order to adjust the list of ranked promotions (such as replacing a highest ranked promotion with another promotion).

Abstract: The present invention relates to a method for extracting tabular data from a document. The method includes identifying a bordered table or a borderless table in a received document and an image of the document. The tabular data in the identified bordered table is extracted using a first and a second set of pixel coordinates from the plurality of pixel coordinates. Further, upon identifying the borderless table in the document, a first set of document coordinates of at least one row of the borderless table is determined. Furthermore, a second set of document coordinates of the at least one column corresponding to the at least one row is determined. Finally, the tabular data in the identified borderless table is extracted from the document based on the determined first and second set of document coordinates.

Abstract: A user preference hierarchy is determined from user response to images. Images may be tagged using machine learning models trained to determine values for images. Products are clustered according to product vectors. Images of products within a cluster are clustered according to composition and groups of images are selected from image clusters for soliciting feedback regarding user preference for products of a cluster. Feedback is used to train a user preference model to estimate affinity for a product vector. A user may provide feedback regarding a price point and products are weighted according to a distribution about the price point. The distribution may be asymmetrical according to direction of movement of the price point. Filters may be dynamically defined and presented to a user based on popularity and frequency of occurrence of attribute-value pairs of search results and based on feedback regarding the search results.

Abstract: A promotion system for determining a deficiency in promotion data and correcting for the deficiency is disclosed. Issuing offers from a promotion program results in promotion data being generated. The promotion data may be analyzed to determine an acceptance rate of the offers. The promotion system may compare whether the acceptance rate is above a predetermined threshold, but has a confidence level that is less than a confidence rate threshold. In that event, the promotion system may issue additional offers in order to increase the confidence level associated with the acceptance rate by a predetermined amount.

Abstract: Systems and methods are presented for managing the cadence (e.g., frequency or rate) that electronic promotion correspondence is sent to a consumer. A system may access a target cadence indicator associated with a consumer that indicates of a target rate for sending electronic promotion correspondence to the consumer. The system may also determine an actual cadence indicator for the consumer over a predetermined period of time and analyze a potential electronic promotion correspondence for sending to the consumer. The system determines whether to send the electronic correspondence to the consumer based on the target cadence indicator, the actual cadence indicator, and the analysis of the electronic promotion correspondence.

Abstract: A user preference hierarchy is determined from user response to images that are tagged. Tagged images may be generated by processing them with machine learning models trained to determine values for images. Product records including images and other data are analyzed to generate attribute vectors that are encoded to generate product vectors. Products are clustered according to their product vectors. Images of products within a cluster are clustered according to composition and groups of images are selected from image clusters for soliciting feedback regarding user preference for products of a cluster. Feedback is used to train a user preference model to estimate affinity for a product having a given product vector. A user may provide feedback regarding a price point and products are weighted according to a distribution having a highest value at the price point. The distribution may be asymmetrical according to direction of movement of the price point.

Abstract: The present invention relates to a method for extracting tabular data from a document. The method includes identifying a bordered table or a borderless table in a received document and an image of the document. The tabular data in the identified bordered table is extracted using a first and a second set of pixel coordinates from the plurality of pixel coordinates. Further, upon identifying the borderless table in the document, a first set of document coordinates of at least one row of the borderless table is determined. Furthermore, a second set of document coordinates of the at least one column corresponding to the at least one row is determined. Finally, the tabular data in the identified borderless table is extracted from the document based on the determined first and second set of document coordinates.

Abstract: Images are tagged with values in an image data hierarchy that is most subjective at its top level and least subjective at its bottom level, such as a hierarchy including style, type, and features for clothing. A user preference hierarchy is determined from user response to images that are tagged. Tagged images may be generated by processing them with machine learning models trained to determine values for images. Product records including images and other data are analyzed to generate attribute vectors that are encoded to generate product vectors. Products are clustered according to their product vectors. Images of products within a cluster are clustered according to composition and groups of images are selected from image clusters for soliciting feedback regarding user preference for products of a cluster. Feedback is used to train a user preference model to estimate user affinity for a product having a given product vector.

Abstract: A system and method is provided for determining a portfolio of promotions from across a diverse mix of promotion categories. The diverse promotion portfolio may represent an inventory of promotions that are available for presenting to a consumer in a particular market. Also, a system and method is provided for determining a diverse group of promotions for presenting to a consumer. The diverse group of promotions may be determined based on whether a same or similar promotion was previously presented to the consumer.

Abstract: In a promotion offering system, a consumer is more likely to purchase a promotion offering if the consumer finds the promotion to be interesting or fits a need of the consumer. In order to provide a more intelligent selection process for selecting promotions that are desirable to the consumer, a method and a promotion offering system for implementing the method are provided that takes into consideration a number of different factors associated with a consumer, including locations and deal types that are known or predicted to be of interest to the consumer, when determining one or more promotions to present to the consumer.

Abstract: A promotion offering system and method is disclosed. The promotion offering system and method selects consumers for a test promotion that has one or more attributes, and is configured to generate test data for multiple consumer groupings. The promotion offering system and method may use the test data in analyzing whether to send a promotion to a consumer. For example, the promotion offering system and method may use one algorithm to generate a list of ranked promotions, and may use the test data in order to adjust the list of ranked promotions (such as replacing a highest ranked promotion with another promotion).

Abstract: Provided herein are a method and apparatus configured to determine one or more consumer deals to present to a consumer. The method and apparatus may include receiving contextual data; accessing one or more databases containing consumer deals; determining a context under which to present a consumer deal to a consumer, the determined context selected from a plurality of contexts; selecting a set of workflow rules under which to determine the consumer deal to present to the consumer; analyzing the plurality of consumer deals based at least in part on the selected set of workflow rules; determining a selected consumer deal to present to the consumer; generating an electronic correspondence comprising the selected consumer deal; and transmitting the electronic correspondence to the consumer device for presenting the selected consumer deal to the consumer.

Abstract: Techniques for providing a distributed and fast data storage layer for large scale web data services are disclosed. In some embodiments, a distributed data storage layer for web data services includes storing web related data for a plurality of merchants in the distributed data storage layer; and copying on demand a data store and a search index for web related data for a first merchant to perform a job for updating the web related data for the first merchant.

Abstract: A deal program life cycle system and method is disclosed. The deal program life cycle may oversee the issuance of deals from a deal program to consumers over the life cycle of the deal program. One or more aspects of the deal program may change during different periods of the life cycle of the deal program. For example, the deal program may include deal features, a number of units for deals, and relevance features for the deal program. The deal features, number of units of deals, and/or relevance features for the deal program may change during the different periods of the life cycle.

Abstract: A planning system obtains an order attribute table associating media advertising orders with flexibility attribute values that indicate scheduling flexibility, and generates an inventory table having cells representing station-daypart combinations. The cells of the inventory table are assigned flexibility attribute values corresponding to the flexibility attribute values of orders booked into corresponding station-daypart combinations. The planning system makes a comparison between a first flexibility attribute associated with an un-booked order and a second flexibility attribute associated with a booked order already booked in a particular station-daypart combination, where the comparison shows that the un-booked order has less scheduling flexibility than the booked order. In response to the comparison, an association between the booked order and the particular station-daypart combination is replaced with an association between the un-booked order and the particular station-daypart combination.

Abstract: In a promotion offering system, a promotion offering may be presented to a consumer on more than one occasion. The previous presentation of the promotion to the consumer may affect a subsequent presentation of the same promotion to the same consumer. The present invention provides an apparatus and method for analyzing the effect a previous presentation of a promotion may have on a consumer when the promotion is presented to the consumer at a subsequent time.