Abstract:
A method determines a usability measure for a web page. A representation of the web page is processed in view of a usability model. The usability indication is determined based on the processing step. The representation of the web page may include an indication of at least one of structural and visual elements. For example, the indication of structural elements may include a document object model of the web page. The usability model may be a statistical model, such as a linear regression model, that provides an estimate of a statistical relationship between the usability measure and a plurality of characteristics discernible from the representation of the web page.

Description:
BACKGROUND 
       [0001]    This invention relates to web page clutter and, more particular, to methods to determine a measure of clutter on a web page. 
         [0002]    It can be important to make web pages easy and pleasing to use, which can be particularly important for web pages it is desired to monetize. This may include, for example, advertisement-containing web pages (of a so-called “web portal,” for example), for which an advertiser pays money when a user views the web page and activates a link of the advertisement. If such web pages are not easy and pleasing to use, the money-making potential of those web pages can be jeopardized. One conventional indication of whether a web page is easy and pleasing to use is called “clutter.” 
         [0003]    The inventors have realized that, since a large influence to the indication of “clutter” is subjective, it would be desirable to include subjective evaluations of a web page to determine its clutter. However, it is often impractical to survey actual people to determine clutter for a particular web page. 
       SUMMARY 
       [0004]    A method determines a usability measure for a web page. A representation of the web page is processed in view of a usability model. The usability indication is determined based on the processing step. The representation of the web page may include an indication of at least one of structural and visual elements. For example, the indication of structural elements may include a document object model of the web page. The usability model may be a statistical model, such as a linear regression model, that provides an estimate of a statistical relationship between the usability measure and a plurality of characteristics discernible from the representation of the web page. 
     
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         [0005]      FIG. 1  broadly illustrates example processing to determine the usability model in accordance with one example. 
           [0006]      FIG. 2  illustrates example processing to determine values for the characteristics of the web pages, for one particular web page. 
           [0007]      FIG. 3  illustrates an example of processing to determine a usability measure for a web page, using the statistical model for usability and the determined values for characteristics of the web page. 
       
    
    
     DETAILED DESCRIPTION 
       [0008]    In accordance with an aspect, a usability model is determined by, for example, surveying users about the usability of a sampling of web pages. The usability model is then applied to another web page to determine a usability indication for that web page. 
         [0009]      FIG. 1  broadly illustrates example processing to determine a usability model in accordance with one example. As shown in  FIG. 1 , a web page sample includes a plurality of web pages  102 . The web pages  102  are provided to users in a survey  104 . The output of the survey  104  is an indication of reactions  106  of the users to the web pages  102  of the web page sample. 
         [0010]    In addition, representations of the web pages  102  of the web page sample are processed  108  to determine, quantitatively, characteristics of the web pages. The indication of user reactions  106  and values for the determined characteristics of the web pages  102  of the web page sample are processed to determine a statistical usability model  114 , in view of the determined web page characteristics. The statistical usability model  114  is saved for use in determining a usability measure for another web page that is not one of the web pages  102  of the web page sample. 
         [0011]    In one example, the statistical usability model  114  is a regression model. For example, the regression model may be a linear regression model characterized by linear coefficients. 
         [0012]      FIG. 2  illustrates a flowchart of example processing to determine values for the characteristics of the web pages, for one particular web page  202 . The  FIG. 2  processing may be used, for example, for step  108  of the  FIG. 1  processing. In the  FIG. 2  example, the characteristics are considered in two groups—structural characteristics and visual characteristics. For structural characteristics, in the  FIG. 2  example, a source HTML representation  204  is used. Processing  206  is performed to obtain a Document Object Model (DOM) tree representation  208  of the web page  202 . The DOM representation is a nominally platform- and language-neutral representation that allows programs to access information about the structure and style of documents. Processing  210  is performed (including traversing the DOM tree representation  208 ) to determine values for structural characteristics  212 , and the determined values are added to an attributes values list  214 . 
         [0013]    In one example, the following structural characteristics are considered:
   1. Total number of links   2. Total number of words   3. Total number of images (non-ad images)   4. Image area above the fold (non-ad images)   5. Dimensions of page   6. Page area (total)   7. Page length   8. Total number of tables   9. Maximum table columns (per table)   10. Maximum table rows (per table)   11. Total rows   12. Total columns   13. Total cells   14. Average cell padding (per table)   15. Average cell spacing (per table)   16. Dimensions of fold   17. Fold area   18. Location of center of fold relative to center of page   19. Total number of font sizes used for links   20. Total number of font sizes used for headings   21. Total number of font sizes used for body text   22. Total number of font sizes   23. Presence of “tiny” text   24. Total number of colors (excluding ads)   25. Alignment of page elements   26. Average page luminosity   27. Fixed vs. relative page width   28. Page weight (proxy for load time)   29. Total number of ads   30. Total ad area   31. Area of individual ads   32. Area of largest ad above the fold   33. Largest ad area   34. Total area of ads above the fold   35. Page space allocated to ads   36. Total number of external ads above the fold   37. Total number of external ads below the fold   38. Total number of external ads   39. Total number of internal ads above the fold   40. Total number of internal ads below the fold   41. Total number of internal ads   42. Number of sponsored link ads above the fold   43. Number of sponsored link ads below the fold   44. Total number of sponsored link ads   45. Number of image ads above the fold   46. Number of image ads below the fold   47. Total number of image ads   48. Number of text ads above the fold   49. Number of text ads below the fold   50. Total number of text ads   51. Position of ads on page   
 
       This is an example, and fewer, more or other structural characteristics  212  may be utilized. 
       [0065]    For visual characteristics, in the  FIG. 2  example, processing  216  converts the web page  202  to an image representation  218  of the web page  202 . The image representation  218  is processed  220  to determine values for visual characteristics  222 , and the values are added to the attributes values list  214 . 
         [0066]    In one example, the following visual characteristics are considered (numbered sequentially from the last number of the structural characteristics):
   52. Presence of animated/flashing ads   53. Average ad luminosity   54. Maximum ad luminosity
 
Again, this is an example. Fewer, more or other visual attributes may be utilized.
   
 
         [0070]    We have described how a statistical model for usability may be determined ( FIG. 1 ) and, further, how a web page may be processed to determine values for the characteristics of the web pages ( FIG. 2 ). We now describe, with reference to  FIG. 3 , an example of processing to determine a usability measure for a web page, using the statistical model for usability and the determined values for characteristics of the web page. 
         [0071]    At step  302 , a representation of the web page  304  is processed to determine characteristics  306  of the web page  304 . The step  302  processing may be, for example, processing similar to that described with reference to  FIG. 2 . At step  308 , the determined characteristics  306  of the web page  304  are processed in view of the usability model  310 , to determine the usability measure  312 . The usability model  310  may have been determined, for example, using processing similar to that described with reference to  FIG. 1 . 
         [0072]    As for step  308 , the processing may be, for example, processing to use a regression model, whether a linear or non-linear regression model. Other models may be utilized as well, as appropriate. 
         [0073]    Furthermore, in some examples, various models and/or various web pages may be provided to the  FIG. 3  processing. For example, the  FIG. 3  processing may be a result of a program being executed on a general purpose computer. The program may include, or have accessible to it, user interface processing via which a user may interact with the program to indicate a particular web page and/or a particular model to be processed by the  FIG. 3  processing. 
         [0074]    In  FIG. 3 , a choice of web pages is indicated by the schematic switch  314 , via which one of a plurality of web page representations (shown in  FIG. 3  as web pages  316 ) may be provided as the web page representation  304  input to the step  302  processing. Furthermore, a choice of statistical usability models is indicated by the schematic switch  318 , via which one of the plurality of statistical usability models (shown in  FIG. 3  as models  320 ) may be provided as usability model  310  to the step  308  processing. In practice, the switch  314  and switch  318  would typically (but are not required to) be implemented via choices on a user interface of a software application on a general purpose local computer, server or distribution of computing power. 
         [0075]    In one example, the usability indicator is utilized as a tool to improve the usability of a web page. For example, the usability indicator for a web page is characterized by sub-components that each correspond to the contribution of a separate attribute of the web page. For example, going back to the linear regression example, each subcomponent may be a product of a value associated with a particular attribute and a coefficient of the statistical usability model, also associated with that particular attribute. An examination of the sub-components, then, contributes to an evaluation of how the usability of the web page may be improved. 
         [0076]    For example, if, the higher the usability indicator, the more “cluttered” a web page is deemed to be, then a particular attribute for which an associated coefficient of the statistical usability model is larger has a relatively larger contribution to the clutter. Put another way, if the value for the particular attribute can be lowered, then this will have a relatively larger effect on reducing the clutter. 
         [0077]    It has been shown, then that a generally-applicable usability model may be determined. The usability model is then applied to another web page to determine a usability indication for that web page. Furthermore, if the usability model is determined based on subjective interpretations of usability with respect to particular web pages, then those subjective interpretations can be practically applied to web pages other than those particular web pages. This results in a measure of usability that, while determined in view of subjective criteria, is repeatable and is practically determined.