1. A process for foaming a water-based adhesive comprising the steps:
a. providing a water-based adhesive in a pressure tight container, wherein the water-based adhesive is an aqueous polymer solution or dispersion;
b. introducing a gaseous substance into the adhesive at room temperature and at pressure greater than 0.2 atm than ambient pressure in the container, thereby dissolving the gaseous substance in the adhesive
c. releasing the adhesive at an ambient pressure, causing the adhesive to foam.
2. The process of claim 1 further comprising step (d) applying the foamed adhesive onto a substrate.
3. The process of claim 2 wherein the substrate is paper, wood, synthetic film or metal.
4. The process of claim 1 wherein the gaseous substance has a solubility increase greater than 30% when subjected to a change from 1 to 2 atm and at room temperature.
5. The process of claim 1 wherein in the step (a), the container is connected to a pressure cylinder, and wherein the cylinder has a pressure greater than the container.
6. The process of claim 1 wherein the gaseous substance is a liquid or a solid with a temperature T<0\xb0 C.
7. A process for foaming a water-based adhesive comprising the steps:
a. providing a water-based adhesive in a pressure tight container, wherein the water-based adhesive is an aqueous polymer solution or dispersion;
b. adding and mixing a first reagent into the adhesive in the pressure-tight container;
c. adding and mixing a second reagent into the adhesive in the container;
d. releasing the adhesive at an ambient pressure, causing the a first reagent and second reagent react and foam.
8. The process of claim 6 further comprising step (e) applying the foamed adhesive onto a substrate.
9. The process of claim 8 wherein the substrate is paper, wood, synthetic film or metal.
10. The process of claim 7 wherein the adhesive comprises a homo or co-polymer of vinyl acetate, a polymer or co-polymer of acrylate or acrylic acid or esters thereof.
11. The process of claim 7 wherein the adhesive comprises polyvinyl alcohol, starch or dextrin-based natural polymers.
12. The process of claim 7 wherein the adhesive contains 5-75 wt %, based on total weight, of non-volatiles.
13. The process of claim 7 wherein the first reagent is 5-30 wt %, based on to total weight of the adhesive, of a metal carbonate, ammonium carbonate or corresponding hydrogen carbonates, or a mixture of carbonates andor hydrogen carbonates.
14. The process of claim 7 wherein the second reagent is an organic or inorganic acid, or acidic salt.
15. The process of claim 7 wherein in step (a), the adhesive is at room temperature and held at pressure greater than 0.59 atm than ambient pressure.
16. The process of claim 7 wherein in step (c), the second reagent is added to the adhesive at a higher pressure than the adhesive.
17. The process of claim 7 wherein the foam exits in step (d) at a pressure lower than the pressure when in the container.
18. An article manufactured by the process of applying the foamed adhesive of claim 2.
19. An article manufactured by the process of applying the foamed adhesive of claim 8.
20. An apparatus for the process of foaming a water-based adhesive of claim 10 comprising: a pressure-tight container for the adhesive wherein an overpressure is provided through a first valve, and a drain valve placed at the outlet of said container, a motor-driven mixer in said container, a pressure-tight second vessel which comprises a second valve at its inlet, and an outlet of said vessel which is connected through a third valve to the pressure-tight container.
The claims below are in addition to those above.
All refrences to claim(s) which appear below refer to the numbering after this setence.
1. A method performed by data processing apparatus, the method comprising:
identifying a set of responsive images for a search phrase that includes two or more terms;
determining, by one or more processors, interaction rankings for images in the set of responsive images; the interaction ranking of each image being based on a number of user interactions with the image relative to a number of user interactions with other images in the set;
creating, by one or more processors, two or more sub-queries based on the search phrase, the sub-queries each being a proper subset of the two or more terms;
for each sub-query from the two or more sub-queries:
determining, by one or more processors, sub-query model rankings for images in the set of responsive images, the sub-query model ranking of each image being determined based on a sub-query model for the sub-query and features of the images, the sub-query model being an image relevance model for the sub-query; and
determining, by one or more processors, a search phrase score for the image relevance model, the search phrase score being a measure of similarity between the interaction rankings of the images and the sub-query model rankings of the images; and
selecting, based on the search phrase scores for the sub-queries, one of the sub-query models as a model for the search phrase, the selected sub-query model having a search phrase score that meets a threshold search phrase score.
2. The method of claim 1, wherein determining interaction rankings for images in the set of responsive images comprises:
ranking a first image from the set of responsive images as a highest ranked image, the first image having a highest number of user interactions among the images in the set of responsive images;
ranking a second image from the set of responsive images as a second highest ranked image, the second image having a second highest number of user interactions among the images in the set of responsive images; and
ranking each unranked image in the set of responsive images in descending order according to the number of user interactions with the image.
3. The method of claim 1, further comprising creating an interaction histogram based on the interaction rankings and the numbers of user interactions with the images.
4. The method of claim 3, further comprising creating a sub-query histogram based on the sub-query model rankings and the number of user interactions with the images.
5. The method of claim 4, wherein determining a search phrase score comprises:
determining a level of match between the interaction histogram and the sub-query histogram; and
determining the search phrase score based on the level of match between the interaction histogram and the sub-query histogram.
6. The method of claim 1, further comprising:
obtaining, for the sub-query model of the selected sub-query, an additional search phrase score specifying a measure of similarity between interaction rankings of other images responsive to another search phrase and sub-query model rankings of the other images based on the sub-query model; and
determining a global search phrase score for the sub-query model, the global search phrase score being determined based on an aggregate measure of the search phrase score and the additional search phrase score.
7. The method of claim 6, further comprising:
determining that the global search phrase score for the sub-query model meets a global search phrase score threshold;
identifying the sub-query as a global sub-query based on the determination that the global search phrase score meets the global search phrase threshold; and
ranking images for at least one additional search phrase that includes the sub-query and at least one other term.
8. A non-transitory computer storage medium encoded with a computer program, the program comprising instructions that when executed by data processing apparatus cause the data processing apparatus to perform operations comprising:
identifying a set of responsive images for a search phrase that includes two or more terms;
determining interaction rankings for images in the set of responsive images; the interaction ranking of each image being based on a number of user interactions with the image relative to a number of user interactions with other images in the set;
creating two or more sub-queries based on the search phrase, the sub-queries each being a proper subset of the two or more terms;
for each sub-query from the two or more sub-queries:
determining sub-query model rankings for images in the set of responsive images, the sub-query model ranking of each image being determined based on a sub-query model for the sub-query and features of the images, the sub-query model being an image relevance model for the sub-query; and
determining a search phrase score for the image relevance model, the search phrase score being a measure of similarity between the interaction rankings of the images and the sub-query model rankings of the images; and
selecting, based on the search phrase scores for the sub-queries, one of the sub-query models as a model for the search phrase, the selected sub-query model having a search phrase score that meets a threshold search phrase score.
9. The computer storage medium of claim 8, wherein determining interaction rankings for images in the set of responsive images comprises:
ranking a first image from the set of responsive images as a highest ranked image, the first image having a highest number of user interactions among the images in the set of responsive images;
ranking a second image from the set of responsive images as a second highest ranked image, the second image having a second highest number of user interactions among the images in the set of responsive images; and
ranking each unranked image in the set of responsive images in descending order according to the number of user interactions with the image.
10. The computer storage medium of claim 8, wherein the instructions cause the data processing apparatus to perform operations comprising creating an interaction histogram based on the interaction rankings and the numbers of user interactions with the images.
11. The computer storage medium of claim 10, wherein the instructions cause the data processing apparatus to perform operations comprising creating a sub-query histogram based on the sub-query model rankings and the number of user interactions with the images.
12. The computer storage medium of claim 11, wherein determining a search phrase score comprises:
determining a level of match between the interaction histogram and the sub-query histogram; and
determining the search phrase score based on the level of match between the interaction histogram and the sub-query histogram.
13. The computer storage medium of claim 8, wherein the instructions cause the data processing apparatus to perform operations comprising:
obtaining, for the sub-query model of the selected sub-query, an additional search phrase score specifying a measure of similarity between interaction rankings of other images responsive to another search phrase and sub-query model rankings of the other images based on the sub-query model; and
determining a global search phrase score for the sub-query model, the global search phrase score being determined based on an aggregate measure of the search phrase score and the additional search phrase score.
14. A system comprising:
a data store; and
one or more computers that interact with the data store and execute instructions that cause the one or more computers to perform operations comprising:
identifying a set of responsive images for a search phrase that includes two or more terms;
determining interaction rankings for images in the set of responsive images; the interaction ranking of each image being based on a number of user interactions with the image relative to a number of user interactions with other images in the set;
creating two or more sub-queries based on the search phrase, the sub-queries each being a proper subset of the two or more terms;
for each sub-query from the two or more sub-queries:
determining sub-query model rankings for images in the set of responsive images, the sub-query model ranking of each image being determined based on a sub-query model for the sub-query and features of the images, the sub-query model being an image relevance model for the sub-query; and
determining a search phrase score for the image relevance model, the search phrase score being a measure of similarity between the interaction rankings of the images and the sub-query model rankings of the images; and
selecting, based on the search phrase scores for the sub-queries, one of the sub-query models as a model for the search phrase, the selected sub-query model having a search phrase score that meets a threshold search phrase score.
15. The system of claim 14, wherein determining interaction rankings for images in the set of responsive images comprises:
ranking a first image from the set of responsive images as a highest ranked image, the first image having a highest number of user interactions among the images in the set of responsive images;
ranking a second image from the set of responsive images as a second highest ranked image, the second image having a second highest number of user interactions among the images in the set of responsive images; and
ranking each unranked image in the set of responsive images in descending order according to the number of user interactions with the image.
16. The system of claim 14, wherein the instructions cause the data processing apparatus to perform operations comprising creating an interaction histogram based on the interaction rankings and the numbers of user interactions with the images.
17. The system of claim 16, wherein the instructions cause the data processing apparatus to perform operations comprising creating a sub-query histogram based on the sub-query model rankings and the number of user interactions with the images.
18. The system of claim 17, wherein determining a search phrase score comprises:
determining a level of match between the interaction histogram and the sub-query histogram; and
determining the search phrase score based on the level of match between the interaction histogram and the sub-query histogram.
19. The system of claim 14, wherein the instructions cause the data processing apparatus to perform operations comprising:
obtaining, for the sub-query model of the selected sub-query, an additional search phrase score specifying a measure of similarity between interaction rankings of other images responsive to another search phrase and sub-query model rankings of the other images based on the sub-query model; and
determining a global search phrase score for the sub-query model, the global search phrase score being determined based on an aggregate measure of the search phrase score and the additional search phrase score.
20. The system of claim 19, wherein the instructions cause the data processing apparatus to perform operations comprising:
determining that the global search phrase score for the sub-query model meets a global search phrase score threshold;
identifying the sub-query as a global sub-query based on the determination that the global search phrase score meets the global search phrase threshold; and
ranking images for at least one additional search phrase that includes the sub-query and at least one other term.