Patent Abstract:
A user can highlight text and provide accompanying annotations. Highlighted text, accompanying annotations, and time-stamp information are stored in a user profile that is maintained locally with a web browser, at the client side. A retrieved web page is presented to a user with annotations of some form, based upon the user profile. The retrieved web page may typically be annotated through marked or highlighted portions of text, so that the user can readily locate this information in the web page, and assess the relevance of the retrieved page.

Full Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
     This application is a continuation of U.S. application Ser. No. 11/838,943 filed Aug. 15, 2007, which was abandoned on Sep. 7, 2011, which is a continuation of U.S. Pat. No. 7,299,407, Issued Nov. 20, 2007, the complete disclosure of which, in its entirety, is herein incorporated by reference. 
    
    
     FIELD OF THE INVENTION 
     The present invention relates to marking and annotating electronic documents, such as Web pages, based on a user&#39;s highlighted preferences history. 
     BACKGROUND 
     Web personalization involves tailoring Web content directly to a specific user. This can be accomplished by having the user provide information to the Web site directly, or through tracking of the user&#39;s behavior on the site. The software on the Web site then can modify the content to suit the particular user&#39;s needs. That is, all the personalization is done at the Web site. 
     Typically, a Web site maintains profiles of the users that visits the site, and analyzes the information gathered. Based on this analysis, information of interest to each user is delivered. 
     Explicit or implicit profiling techniques can be used to collect user information, either alone or in combination. Explicit profiling involves asking each user to complete a questionnaire or similar, while implicit profiling involves tracking the behavior of each user, and drawing inferences from such observed behavior. 
     One form of implicit profiling involves the use of “cookies” that are stored at the browser and updated at each visit, and record browsing patterns. 
     To present appropriate content to the user and make proper recommendation, rule-based techniques or filtering techniques can be used. Filtering techniques may involve simple filtering, content-based filtering and collaborative filtering. Collaborative-filtering software compares the information gained about one user&#39;s behavior against data about other users with similar interests. 
     None of the techniques described above are entirely satisfactory. Consequently, techniques are sought that have application in navigating electronic content. 
     SUMMARY 
     A user&#39;s interest in a recently viewed web page can be determined automatically from that user&#39;s highlighted text and annotation history profiled from the previously viewed web pages. Such annotations typically constitute marked or highlighted portions of text, accompanying comments, or other forms of annotation. This annotation information is maintained in a user profile at the client side. A retrieved web page is presented to a user with annotations of some form, based upon the viewer&#39;s user profile. The retrieved web page may typically be annotated through marked or highlighted portions of text, so that the user can readily locate this information in the web page, and assess the relevance of the retrieved page. 
     A context for the highlighted information is obtained by annotating the text, and can be presented to the user along with the text. A web page presented to the user is marked to indicate the information of interest. When a user rolls the mouse over this text, the annotation is shown at the mouse position. This is the context that applies to the text, which indicates to the user the broad topic to which the marked text relates. Ontology can be represented in any form, and can be stored as a database, and represents relationships between words. A word-net can be used to enhance this gathered information. Information concerning the user&#39;s interest can be presented to the user without the need for server-side processing. 
     Highlighted text, accompanying comments, and time-stamp information are stored in a user profile that is maintained locally with the browser, at the client side. The user profile is updated as the user visits new pages and annotates these web pages. When a user accesses a new web page, text in this page that is, for example, similar to the text stored in the user profile, is automatically marked. Other annotations can also be assigned. Since the marking occurs at the client side, profiles can be shared and used across different sites the user visits. 
    
    
     
       DESCRIPTION OF DRAWINGS 
         FIG. 1  is a schematic representation of a system architecture for annotating electronic documents. 
         FIG. 2  is a schematic representation of components of a preference-enable text marker. 
         FIG. 3  is a schematic representation of a computer interface having a dialog box for prompting a user to annotate text. 
         FIG. 4  is Javascript code that can be added to a Web page to faciliate annotation of the highlighted text on the Web page. 
         FIG. 5  is a schematic representation of a computer interface indicating information of interest to a user. 
         FIG. 6  is a schematic representation of a computer system suitable for operating the described computer interfaces. 
     
    
    
     DETAILED DESCRIPTION 
       FIG. 1  schematically represents an architecture of the described system. A Web Browser  100  is enabled to create and update a User Profile  130  based on highlighted and annotated text of previous web pages. The Web Browser  100  then marks the text in the retrieved Web Page  150  based on the User Profile  130 . The marked Web Page  150  is presented to the user by the Web Browser  100 . 
     The system architecture of  FIG. 1  has five components that supplement the Web Browser  100 , namely, User Manager  110 , Event Listener and Text Extractor  112 , Annotator  114 , Profile Manager  116  and Preference Enabled Text Marker  118  that supplement the functionality of a conventional web browser. Each of these components is described in turn below.  FIG. 2  schematically represents components of the Preference Enabled Text Marker  118 , described in further detail below. 
     User Manager: The main function of the User Manager  110  is to identify the “userid” of the “logged on” user. The User Manager  110  also creates a User Profile  130 , if a User Profile  130  does not already exist. Each user has their own User Profile  130  that stores their preferences. The User Manager  110  maintains the privacy of each user. The security and privacy of the User Profile  130  can be maintained using the file system user privileges provided by the operating system. If the operating system does not provide a way to identify the user, then the system can maintain a single User Profile  130  that is common to all the users of that particular instance of the Web Browser  100 . 
     Event Listener and Text Extractor: The Event Listener and Text Extractor  112  listens to the “mouse-dragged” event. This operating system event gets fired whenever a user highlights particular text in a web page. When the event is fired the Event Listener and Text Extractor  112  extracts the highlighted text from the web page and sends the text string to the Annotator  114 , which is described directly below. 
     Annotator: The Annotator  114  enables the user to annotate the user&#39;s highlighted text. This allows the user to associate the context with the highlighted text. When the user annotates a text, the user&#39;s annotating comments may either summarize the text or disambiguate the text. This is what meant by giving a context to the text of interest to the user. For example, a particular text about networking might be of interest to one user because the text is about wireless networking, for another user the text may be interesting since the text is about security. So when the user annotates the text with words “network security”, this is the context in which the user looking for further information. Therefore, a particular text might be relevant within different contexts, i.e., the text can have different meanings depending upon how the text is used. Thus, annotation helps the system to distinguish between different possible meanings of the text. The second use of annotation is to summarize a text. For example, the user visits page “A” and highlights the text “optimized to manage large collections of smaller objects such as statements and reports and checks” appearing on page “A”. The system does not in his case receive any information concerning what the information is about. Annotator  114 , however, allow the user to mark this information with the annotation of “content manager”. Now the system can make use of the annotation to find the information of the user interest in the pages that talk about “content manager”. Once the highlighted text is annotated, if any, then the Annotator  114  passes the highlighted text along with accompanying annotation to the Profile Manager  116 . 
     Profile Manager: Profile Manager  116  receives the annotated highlighted text from the Annotator  114 . Profile Manager  116  obtains the file system location of the User Profile  130  from the User Manager  110 . Profile Manager  116  then stores this highlighted text along with the associated annotation in the User Profile  130 . Table 1 below presents the format of the User Profile  130 . 
     
       
         
               
             
               
               
               
               
               
             
           
               
                 TABLE 1 
               
             
             
               
                   
               
               
                 Format of User Profile 130 
               
             
          
           
               
                   
                 Highlighted 
                   
                 Timestamp of 
                 Timestamp 
               
               
                   
                 Text 
                 \Annotation 
                 highlighting 
                 of Expiry 
               
               
                   
               
               
                   
                 . . . 
                 . . . 
                 . . . 
                   
               
               
                   
                 . . . 
                 . . . 
                 . . . 
                   
               
               
                   
                 . . . 
                 . . . 
                 . . . 
               
               
                   
               
             
          
         
       
     
     As shown in Table 1 above, the User Profile  130  stores the time when the user highlighted and annotated the relevant text. The fourth row indicates the “life” of each entry in the User Profile  130  (that is, each highlighted text and its annotation). An “Expiry date” can be used to avoid maintaining the history beyond certain time. 
     The user can set a system parameter that controls how much past history is considered when marking a Web Page  150 . The Profile Manager  116  uses this parameter to compute the Timestamp of Expiry for the User Profile  130  entry. Suppose the user sets the parameters to indicate that the user is interested in keeping the history for 30 days. If an entry is made in the user profile, for page A on 1 st  January 12 p.m. 30 days time is added to the time when the entry is inserted. This is the time of expiry. Time of expiry is 31 st  January 12.00 pm. Now, on 10 th  January the user again changes the parameter to contain 20 days of history. The time of expiry for page A is updated by adding 20 days to timestamp of highlighting. Alternatively, after highlighting and annotating the user can be prompted to provide the time duration for which the information is to persist in the User Profile  130 . The expiry time for the information is then calculated and stored in the User Profile  130  along with the other information. Profile Manager  116  runs a maintenance algorithm that removes entries in the User Profile  130  that are expired. 
     Preference-Enabled Text Marker: The Preference Enabled Text Marker  118  receives web pages from the HTTP client  119  in the Web Browser  100 , which in turn retrieves web pages from the Web Server  120 . The Preference Enabled Text Marker  118  presents web pages to the user in such a way that the information is highlighted and annotated automatically. This highlighting and annotation is based upon the User Profile  130 , which contains the history of the highlighted text and annotations from the previously browsed pages.  FIG. 2  schematically represents different components of the Preference Enabled Text Marker  118 . 
     Various steps performed by the Preference Enabled Text Marker  118  are now described with reference to the components of the Preference Enabled Text Marker  118  depicted in  FIG. 2 . Let LA be a list of all annotations (List of Annotations) in the User Profile  130 , let Ti be the list of all highlighted text available in the user profile for annotation a i , and let S i  be the list of synonyms of annotation a i . Table 2 below presents an algorithm performed by the Preference Enabled Text Marker  118 . 
     
       
         
               
               
             
               
               
               
             
               
               
             
               
               
               
             
               
               
             
           
               
                 TABLE 2 
               
               
                   
               
             
             
               
                 1. 
                 A page W retrieved by the HTTP client 119 from the Web Server 120 
               
               
                   
                 is provided to the Profiler 216. 
               
               
                 2. 
                 The Profiler 216 then reads the User Profile 130 of that user and 
               
               
                   
                 retrieves LA 
               
               
                 3. 
                 For each annotation a i  in the list LA 
               
             
          
           
               
                   
                 a. 
                 Profiler 216 retrieves a list of all the corresponding highlighted 
               
               
                   
                   
                 text entries T i . 
               
               
                   
                 b. 
                 Profiler 216 queries an Ontology Plug-in 140 to get S i . 
               
               
                   
                 c. 
                 Profiler 216 passes S i , T i , a i  and W to the Match Finder 212. 
               
               
                   
                 d. 
                 Match Finder 212 passes T i  and W to Pattern Locator 210. 
               
               
                   
                 e. 
                 Pattern Locator 210 finds the position of each text element of T i  in 
               
               
                   
                   
                 W, and returns back a list denoted by P i  of position pairs &lt;b i , e i &gt; 
               
               
                   
                   
                 providing beginning and ending positions of the sentence in the 
               
               
                   
                   
                 retrieved web page in which the strings were approximately 
               
               
                   
                   
                 matched. 
               
               
                   
                 f. 
                 Match Finder 212 stores this list P i  and then passes S i , a i  and W to 
               
               
                   
                   
                 the Pattern Locator 210. 
               
               
                   
                 g. 
                 Pattern Locator 210 performs exact string matching for each of 
               
               
                   
                   
                 the string in S i  and a i  in W. Pattern Locator 210 returns back a 
               
               
                   
                   
                 list denoted P j  of position pairs &lt;b i , e i &gt; of the beginning and 
               
               
                   
                   
                 ending positions of the sentence in the retrieved web page in 
               
               
                   
                   
                 which the strings were exactly matched. 
               
               
                   
                 h. 
                 Match Finder 212 now merges P i  and P j  and removes duplicates, 
               
               
                   
                   
                 if there are any. For each entry &lt;b i , e i &gt; in this merged list, Match 
               
               
                   
                   
                 Finder 212 augments the annotation a i  and stores the resulting 
               
               
                   
                   
                 triplet &lt;b i , e i , a i &gt; in pattern list LP. 
               
               
                   
                 i. 
                 Match Finder 212 sends a signal to Profiler 216 that Match 
               
               
                   
                   
                 Finder 212 has updated the pattern list for annotation a i . 
               
             
          
           
               
                 4. 
                 Profiler 216 sends a signal to Match Finder 212 that all the annotations 
               
               
                   
                 have been processed and sends it W and LA. 
               
               
                 5. 
                 Match Finder 212 then sends W, LA and pattern list LP to the Page 
               
               
                   
                 Composer 214. 
               
               
                 6. 
                 Page Composer 214 performs the following steps 
               
             
          
           
               
                   
                 a. 
                 For each a i  in LA. Page Composer 214 assigns a unique 
               
               
                   
                   
                 combination of foreground and background colors. 
               
               
                   
                 b. 
                 For each triplet &lt;b i , e i , a i &gt; in LP, the Page Composer 214 obtains 
               
               
                   
                   
                 the starting position b i  and ending position e i  of the sentence in the  
               
               
                   
                   
                 Web page and then inserts Hypertext Markup Language (HTML)  
               
               
                   
                   
                 tags at the starting and ending position so that the text of the 
               
               
                   
                   
                 sentence appears in bold with the foreground and background 
               
               
                   
                   
                 colors corresponding to a i . This operation performs the marking 
               
               
                   
                   
                 for the text matching with the user&#39;s preferences. 
               
               
                   
                   
                 Also Page Composer 214 inserts a special tag so that the  
               
               
                   
                   
                 annotation a i  is shown as a “tip” when user rolls the mouse over 
               
               
                   
                   
                 the sentence text. 
               
             
          
           
               
                 7. 
                 The Page Composer 214 then presents this modified page to the user. 
               
               
                   
               
             
          
         
       
     
     The Pattern Locator  210  used by the Preference Enabled Text Marker  118  uses a module to perform approximate string matching in step  3   e  of Table 2, using any suitable approximate string matching algorithm. A suitable algorithm is described in Cole, R., Hariharan, R., “Approximate String Matching: A simpler faster algorithm”,  SIAM Journal on Computing , Volume 31, Number 6, pages 1761-1782, 2002, the content of which is hereby incorporated by reference. 
       FIG. 3  schematically represents a typical user experience while using the system. A user interface window  310  displays text  340 . When a user highlights a portion of text  350 , Event Listener and Text Extractor  112  is activated and extracts the highlighted text, which is passed to the Annotator  114 . Annotator  114  then prompts the user to provide an accompanying comment  330  for the highlighted text  350  using a dialog box  320 . 
     Web Browser Implementations 
     A web browser having the functionality described herein can be constructed by adding appropriate components to a conventional browser. The browser needs to read the User Profile  130 , which is created by the user. The user appropriately creates the User Profile  130  in the right (system) directory structure with the right schema so that the browser can read the User Profile  130 , and take appropriate action in marking and annotating documents automatically. 
     Alternatively, an implementation can be achieved without adding components to a Web browser, but by achieving equivalent functionality using code embedded in the actual Web pages.  FIG. 4  presents Javascript code, which is interpreted by compatible browsers, and which can be used for this purpose. 
     The web page is downloaded, and the User Manager  110  is invoked to identify the user and the appropriate user profile location. Javascript code can be added to the web page to provide the simulation for the Event Listener and Text Extractor  112 , Annotator  114  and Profile Manager  116 . The “Preference Enabled Text Marker” algorithm described above is then applied to the page, and the page is presented to the user through a web browser. 
     A maintenance algorithm, which removes entries in the User Profile  130 , is activated by the Profile Manager  116  and runs as a daemon in the background. To understand the working of the simulator, assume that the user “xyz” starts using the simulated system for the first time. The User Manager  110  identifies the user and creates the User Profile  130 . Initially, the User Profile  130  is empty. If the user wants to browse the page www.abc.com the browser downloads the relevant page. The Javascript code of  FIG. 4  is added to the downloaded page, either by including appropriate Javascript to the downloaded webpage, or by using a suitable browser plugin for the browser. 
     Since the user is using the system for the first time, the code for the “Preference Enabled Text Marker” presents the page to the user without alteration. When the user highlights and annotates information in this presented page, these annotations are stored in the User Profile  130 . When the user sends a request to the simulator to browse another page, the same steps as mentioned above are carried out for this requested page. When the page is passed to Preference Enabled Text Marker  118 , this page is passed to its various components and the simulator presents the final composed page to the user. 
     Annotations to Browsed Documents 
       FIG. 5  represents a page in which annotations are made based upon a user profile. In this example, when the user brings the mouse on top of the first line of text, a entry “Data Warehouse” is displayed as the highlighted line is annotated by “Data Warehouse” in  FIG. 3 , as recorded in the User Profile  130 . In  FIG. 3 , the user annotates this same text, which is associated with this annotation in the User Profile  130 . When a new page is fetched, the User Profile  130  is automatically applied on the fetched page and the text is automatically highlighted and annotated. 
     Computer Hardware 
       FIG. 6  is a schematic representation of a computer system  600  of a type that is suitable for executing computer software for annotating electronic documents in the manner described herein. Computer software executes under a suitable operating system installed on the computer system  600 , and may be thought of as comprising various software code means for achieving particular steps. 
     The components of the computer system  600  include a computer  620 , a keyboard  610  and mouse  615 , and a video display  690 . The computer  620  includes a processor  640 , a memory  650 , input/output (I/O) interfaces  660 ,  665 , a video interface  645 , and a storage device  655 . 
     The processor  640  is a central processing unit (CPU) that executes the operating system and the computer software executing under the operating system. The memory  650  includes random access memory (RAM) and read-only memory (ROM), and is used under direction of the processor  640 . 
     The video interface  645  is connected to video display  690  and provides video signals for display on the video display  690 . User input to operate the computer  620  is provided from the keyboard  610  and mouse  615 . The storage device  655  can include a disk drive or any other suitable storage medium. 
     Each of the components of the computer  620  is connected to an internal bus  630  that includes data, address, and control buses, to allow components of the computer  620  to communicate with each other via the bus  630 . 
     The computer system  600  can be connected to one or more other similar computers via a input/output (I/O) interface  665  using a communication channel  685  to a network, represented as the Internet  680 . 
     The computer software may be recorded on a portable storage medium, in which case, the computer software program is accessed by the computer system  600  from the storage device  655 . Alternatively, the computer software can be accessed directly from the Internet  680  by the computer  620 . In either case, a user can interact with the computer system  600  using the keyboard  610  and mouse  615  to operate the programmed computer software executing on the computer  620 . 
     Other configurations or types of computer systems can be equally well used to execute computer software that assists in implementing the techniques described herein. 
     Various alterations and modifications can be made to the techniques and arrangements described herein, as would be apparent to one skilled in the relevant art.

Technology Classification (CPC): 6