Abstract: A method and system for adjusting ads auction using predicted user responses to an in-ad survey is provided. The method includes (1) providing a content item associated with an actionable object, which when selected, causes a computing device to present a plurality of interactive elements each corresponding to a different one of a plurality of reasons for restricting the content item; (2) receiving, from the computing device, data indicating a particular reason, of the plurality of reasons, for restricting the content item, and the particular reason corresponding to a particular interactive element, of the plurality of interactive elements, that was selected by the user; and (3) updating, using the received data, a content selection model for selecting content items, wherein the content selection model is associated with the user.

Abstract: The present disclosure selects third party content based on feedback. A selector identifies several content items including first and second content items (or more) responsive to a request. A machine learning engine determines a first feature of the first content item, a second feature of the second content item, and a third feature of the web page or a device associated with the request. The machine learning engine determines, responsive to the first feature and the third feature, a first score for the first content item based on a machine learning model generated using historical signals received from devices via a metadata channel formed from an electronic feedback interface. The machine learning engine determines a second score for the second content item responsive to the second feature and the third feature. A bidding module determines a price for the first content item based on the first and second scores.

Abstract: A hair treatment composition in a cationic system includes water and a novel association of polysaccharide, such as inulin, a wax, such as, candelilla wax, a cationic surfactant, such as, behentrimonium chloride, and a film-forming polymer, such as polysilicone-29. The composition may include one or more additional components selected from fatty compounds, cationic polymers and styling polymers, embodied to deliver one or more of smoothing, straightening and curling/curl defining style features to achieve a particular straight or curly style with frizz control, softness and manageability.

Abstract: The present disclosure selects third party content based on feedback. A selector identifies several content items including first and second content items (or more) responsive to a request. A machine learning engine determines a first feature of the first content item, a second feature of the second content item, and a third feature of the web page or a device associated with the request. The machine learning engine determines, responsive to the first feature and the third feature, a first score for the first content item based on a machine learning model generated using historical signals received from devices via a metadata channel formed from an electronic feedback interface. The machine learning engine determines a second score for the second content item responsive to the second feature and the third feature. A bidding module determines a price for the first content item based on the first and second scores.

Abstract: A hair treatment composition in a anionic, nonionic or amphoteric system includes water and a novel association of polysaccharide, such as inulin, and a film-forming polymer, such as polysilicone-29. The composition may include one or more additional components selected from polymers such as anionic polymers and nonionic polymers, amphoteric surfactants, or fatty compounds, embodied to deliver one or more of smoothing, straightening and curling/curl defining style features to achieve a particular straight or curly style with frizz control, softness and manageability.

Abstract: A hair treatment composition in a cationic system includes water and a novel association of polysaccharide, such as inulin, a wax, such as, candelilla wax, a cationic surfactant, such as, behentrimonium chloride, and a film-forming polymer, such as polysilicone-29. The composition may include one or more additional components selected from fatty compounds, cationic polymers and styling polymers, embodied to deliver one or more of smoothing, straightening and curling/curl defining style features to achieve a particular straight or curly style with frizz control, softness and manageability.

Abstract: The present disclosure selects third party content based on feedback. A selector identifies several content items including first and second content items (or more) responsive to a request. A machine learning engine determines a first feature of the first content item, a second feature of the second content item, and a third feature of the web page or a device associated with the request. The machine learning engine determines, responsive to the first feature and the third feature, a first score for the first content item based on a machine learning model generated using historical signals received from devices via a metadata channel formed from an electronic feedback interface. The machine learning engine determines a second score for the second content item responsive to the second feature and the third feature. A bidding module determines a price for the first content item based on the first and second scores.

Abstract: The present invention is directed to a cleansing composition containing: (a) at least one anionic surfactant; (b) at least one amphoteric surfactant; (c) at least one amphoteric polymer; (d) at least one acrylate copolymer; (e) at least one silicone; (f) at least one alcohol ester; and (g) an insoluble component, and wherein the composition is preferably clear in appearance, free cationic polymer, and has the insoluble component effectively suspended therein.

Abstract: The present disclosure selects third party content based on feedback. A selector identifies several content items including first and second content items (or more) responsive to a request. A machine learning engine determines a first feature of the first content item, a second feature of the second content item, and a third feature of the web page or a device associated with the request. The machine learning engine determines, responsive to the first feature and the third feature, a first score for the first content item based on a machine learning model generated using historical signals received from devices via a metadata channel formed from an electronic feedback interface. The machine learning engine determines a second score for the second content item responsive to the second feature and the third feature. A bidding module determines a price for the first content item based on the first and second scores.

Abstract: The present disclosure selects third party content based on feedback. A selector identifies several content items including first and second content items (or more) responsive to a request. A machine learning engine determines a first feature of the first content item, a second feature of the second content item, and a third feature of the web page or a device associated with the request. The machine learning engine determines, responsive to the first feature and the third feature, a first score for the first content item based on a machine learning model generated using historical signals received from devices via a metadata channel formed from an electronic feedback interface. The machine learning engine determines a second score for the second content item responsive to the second feature and the third feature. A bidding module determines a price for the first content item based on the first and second scores.

Abstract: The instant disclosure relates to hair-treatment compositions. The hair-treatment compositions typically include: one or more polyurethane latex polymers; one or more cationic emulsifiers and/or surfactants; one or more fatty compounds; and water. Additional components such as water-soluble solvents, silicones, cationic polymers, etc., can also be included. The instant disclosure also relates to kits that include the hair-treatment compositions and to methods for treating hair with the hair-treatment compositions.

Abstract: The present invention is directed to a cleansing composition containing: (a) at least one anionic surfactant; (b) at least one amphoteric surfactant; (c) at least one amphoteric polymer; (d) at least one acrylate copolymer; (e) at least one silicone; (f) at least one alcohol ester; and (g) an insoluble component, and wherein the composition is preferably clear in appearance, free of cationic polymer, and has the insoluble component effectively suspended therein.

Abstract: The present disclosure selects third party content based on feedback. A selector identifies several content items including first and second content items (or more) responsive to a request. A machine learning engine determines a first feature of the first content item, a second feature of the second content item, and a third feature of the web page or a device associated with the request. The machine learning engine determines, responsive to the first feature and the third feature, a first score for the first content item based on a machine learning model generated using historical signals received from devices via a metadata channel formed from an electronic feedback interface. The machine learning engine determines a second score for the second content item responsive to the second feature and the third feature. A bidding module determines a price for the first content item based on the first and second scores.

Abstract: The present invention is directed to a cleansing composition containing: (a) at least one anionic surfactant; (b) at least one amphoteric surfactant; (c) at least one amphoteric polymer; (d) at least one acrylate copolymer; (e) at least one water-soluble silicone; (f) at least one alcohol ester, and wherein the composition is clear in appearance and free of cationic polymer.

Abstract: The present invention is directed to a cleansing composition containing: (a) at least one anionic surfactant; (b) at least one amphoteric surfactant; (c) at least one amphoteric polymer; (d) at least one acrylate copolymer; (e) at least one silicone; (f) at least one alcohol ester; and (g) an insoluble component, and wherein the composition is preferably clear in appearance, free of cationic polymer, and has the insoluble component effectively suspended therein.