Abstract:
An object of the present invention is to extract only the relevant information from a document (such as an HTML web page) to facilitate the summarizing of the document. There is provided a method of extracting a portion of text from a document including at least one table and cells within the at least one table, for the purposes of generating a summary of contents of the document. The method comprises: identifying cells within the document; determining a text size of the cells; selecting some of the cells using the text size of the cells; extracting in a text only output a text content of the selected cells; whereby the text only output extracted can be used to produce a summary of a portion of text of the document excluding text from non-selected cells.

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS  
       [0001]    This application is a continuation-in-part of PCT application no. PCT/CA00/01225 filed Oct. 19, 2000 by Applicant.  
       FIELD OF THE INVENTION  
       [0002]    The invention relates to the field of extracting the contents of documents, especially the contents of web pages. 
     
    
     
       BACKGROUND OF THE INVENTION  
         [0003]    Because of the incredible quantity of documents available on the Internet, people surfing on the Internet often have the impression that they will not be able to find what they are looking for in a timely fashion. When search tools return a list of hits for particular keywords which comprises more than 15 hits, it is inefficient for a user to follow each link and read through the material available on the web site before deciding if the hit is relevant.  
           [0004]    Summarizing tools have been created which try to extract the particular meaning of the contents of documents using statistical analysis of the words to better direct the users through the documents available. These summarizing tools are very efficient with conventional documents such as papers, essays, books, etc., but yield very limited results when used with web pages because of the presence of banners, links, tables, frames and other presentation and display tools which separate and organize portions of text.  
           [0005]    Many text summarizing tools are available on the market. A few such tools are the ConText tool by Oracle, the Text Extractor by National Research Council of Canada (NRC), the Summarizer SDK by inxight and the Word AutoSummarize feature by Microsoft. Also available is the text-only save option in Internet Explorer 5.0 by Microsoft. It allows to save a document without the HTML formatting.  
           [0006]    NRC Extractor takes a text file as input and generates a list of keywords and keyphrases as output. The output keyphrases are intended to serve as a short summary of the input text file. Extractor uses a statistical approach to summarizing. Using this approach, the frequency of appearance of words and their derivatives (stems) together with their relative position with respect to the top of the page, among others, are important factors. Extractor uses 12 statistical parameters. As can be understood from this description of Extractor, when such an algorithm is faced with a web page to be summarized, the summary is polluted with many words and phrases irrelevant to the contents of the page but highly relevant to the navigation on the site.  
           [0007]    Referring to FIG. 1, a web page including a news article is shown. This web page was available on Oct. 17, 2000 at www.zdnet.com/zdnn/stories/news/0,4586,2619342,00.html. The contents of the web page are diluted by words such as Zdnet, Page one, Business, Internet, Contact Us, Breaking news, etc. These words, which are irrelevant to the contents of the news item but highly relevant to the web site, are frequent and often appear above the text of the article.  
           [0008]    [0008]FIG. 1 is a schematic representation of the web page mentioned above. The contents of the web page has been divided into tables to highlight the structure of the document. The browser  19  displays the web page. The following is a description of the contents of each table identified in the web page:  
           [0009]    [0009] 20 . ZDNet navigation hyperlinks: Cameras, Reviews, Shop, Business, Help, News, Electronics, GameSpot, Tech Life, Downloads, Developer.  
           [0010]    [0010] 21 . The ZDNet banner with their logo.  
           [0011]    [0011] 22 . ZDNet&#39;s highlighted hyperlinks: Tech Business insider, Outlet Store Savings, Free Downloads.  
           [0012]    [0012] 23 . The hierarchical position of the article: ZDNet&gt;ZDNet News Page One&gt;Business&gt;Lane gets new job, blasts Ellison.  
           [0013]    [0013] 24 . An ad banner, in this case, MasterCard™.  
           [0014]    [0014] 25 . A Search For tool.  
           [0015]    [0015] 26 . The ZDNet Business section logo together with the Wall Street Journal logo.  
           [0016]    [0016] 27 . The Sections frame.  
           [0017]    [0017] 28 . The Breaking news frame with a sample of 5 news items.  
           [0018]    [0018] 29 . The hyperlinks for the following news sections: Page One, Business, Commentary, Computing, eCrime, Law and You, International, Internet, Investor, Mac/Apple, TalkBack Central.  
           [0019]    [0019] 30 . The top stories hyperlinks with a sample of 6 news items.  
           [0020]    [0020] 31 . The hyperlinks to communicate with ZDNet: Contact Us, Corrections, Custom News.  
           [0021]    [0021] 32 . The operations section: E-mail this, Print this, Save this.  
           [0022]    [0022] 33 . A hyperlink to the Air Tech news radio.  
           [0023]    [0023] 34 . An ad frame.  
           [0024]    [0024] 35 . Related Sites hyperlinks such as AnchorDesk, Inter@ctive Week, MSNBC News, eWEEK, Sm@rt Partner, ZDNet Asia, etc.  
           [0025]    [0025] 36 . The main body and contents of the news item, a news article.  
           [0026]    [0026] 37 . The second portion of the main body and contents of the news item.  
           [0027]    [0027] 38 . A table of hyperlinks to other related sites.  
           [0028]    [0028] 39 . An hyperlink to the tool to submit comments on the news item.  
           [0029]    [0029] 40 . Hyperlinks to more articles on the same story.  
           [0030]    [0030] 41 . ORCL links: News, Profile, Chart, Estimates.  
           [0031]    [0031] 42 . Short summary of the news article.  
           [0032]    Not shown are other hyperlinks to ads, related articles and related web sites located at the bottom of the web page and accessible by scrolling the page using the browser&#39;s tools.  
           [0033]    Microsoft Internet Explorer 5.0 allows a user to save a web page as text only. This text-only save option extracts all text from the page, even text in hyperlinks.  
           [0034]    Table 1 shows a text-only version of the web page of FIG. 1 obtained using the text-only save of Microsoft Internet Explorer 5.0.  
                     TABLE 1                       Text-only version of the web page of FIG. 1.                                ZDNet: News: Lane gets new job, blasts Ellison | Cameras | Reviews | Shop|       Business | Help | News | Electronics | GameSpot | Tech Life |Downloads|       Developer       IPO News And Analysis       Outlet Store Savings       Free Downloads       ZDNet &gt; ZDNet News Page One &gt; Business &gt; Lane gets new job, blasts Ellison       Search For:NewsAll ZDNetThe Web Search, Tips, Power Search       Page One, Business, Commentary       Computing, eCrime, Law &amp; You, International, Internet, Investor, Mac/Apple,       TalkBack Central       Headline Scan, News Briefs, News Archive, News Specials       Contact us, Corrections, Custom News       On the Air, Tech news, 24 hours a day, Play Radio       Related Sites , AnchorDesk, Inter@ctive       Week, MSNBC News, eWEEK, Sm@rt Partner       ZDNet Asia, ZDNet UK, ZDNet Australia, ZDNet France, ZDNet Germany, ZDNet       Japan, ZDNet China       Lane gets new job, blasts Ellison       Former top lieutenant Ray Lane and Oracle CEO Larry Ellison continue       to battle, even as Lane takes a job with Kleiner Perkins.       By Lee Gomes, WSJ Interactive Edition       August 24, 2000 7:51 AM PT       Ray Lane, former No. 2 executive at Oracle Corp., hardly has a bad thing to       say about his former employer -- except that it is a company full of yes men       who tend to be less than candid about their products.       Lane abruptly left the business-software giant in June after an eight-year       stint. One reason was that his responsibilities as president and chief       operating officer had been reduced by Lawrence Ellison, Oracle&#39;s (Nasdaq:       ORCL) chief executive. Lane, 53 years old, said following his departure that       he wanted to devote more time to his two young children by his second       marriage.       Sound off here!!, Post your comment       Ellison vs. Lane       ZDNet Smart Business Magazine       Coop&#39;s Corner: Larry Ellison and Basura-gate       Ellison changes his account of Lane departure       Behind Lane&#39;s resignation at Oracle       Oracle&#39;s Ray Lane steps down       ORCL:News, Profile, Chart, Estimates       Wednesday, Lane announced that he will become a general partner at Kleiner       Perkins Caufield &amp; Byers, the prominent Silicon Valley venture-capital firm.       And in an interview scheduled with that announcement, Lane harshly criticized       Ellison, making clear that his departure from Oracle wasn&#39;t amicable. In       response to Lane&#39;s comments, Ellison strongly defended himself and the       company.       A great admirer yet       Lane said he remains a great admirer of Oracle and Ellison. He said, for       example, that Ellison&#39;s oversight of the main Oracle database product in the       early 1990s “saved” the company, and that lately, Ellison has “reinvigorated”       Oracle to take advantage of the opportunities presented by the Internet. That       work made Lane&#39;s net worth, based largely in Oracle stock, soar to nearly a       billion dollars.       But Lane also said that Ellison is utterly dominating the company right       now, something that might prove to be harmful in the long run, since Oracle       won&#39;t be able to develop the strong management team it needs.       ‘[The Oracle executives] aren&#39;t leaders. They just do what Larry says. They       wouldn&#39;t know how to make a decision without Larry making it for them.’ --       Ray Lane, former No. 2 executive at Oracle       “It&#39;s just like with kids,” Lane said. “If you make all their decisions       for them, they will go out as adults not knowing how to make decisions       themselves.” The executives now reporting to Ellison, said Lane, “are not       decision makers. They aren&#39;t leaders. They just do what Larry says. They       wouldn&#39;t know how to make a decision without Larry making it for them.”       Lane came to Oracle, of Redwood Shores, Calif., in 1992 at a time when the       company&#39;s credibility in the market was low. He said Wednesday that       studies he commissioned at that time found that many customers “would never       do business again with a Larry Ellison company.”       The reason, Lane said, is that Oracle would sell products it didn&#39;t have.       “Larry is a visionary, and expresses the vision so well that people believe       it&#39;s a product.” When he first got to Oracle, Lane said, “managers would be       willing to take the order and make a lot of money,” even though the products       often didn&#39;t exist. “That&#39;s the discipline I put into the company,” he said.       “I told the sales force, ‘After what Larry says is the vision, tell the       customer the truth about what we can actually deliver.’ ”       ‘Needs more balance’       Lane indicated that he is worried that with him gone, Oracle might lapse back       to its old ways. “The company needs more balance,” he said.       Ellison rejected his former deputy&#39;s criticisms.       Oracle&#39;s managers, Ellison said, were in many cases chosen by Lane himself.       “He is criticizing his own team for being weak. When did they become yes men?       I am thrilled they are all here. They are delivering exceptional results.”       Ellison also said the company doesn&#39;t sell products it doesn&#39;t have.       “He is the soul, the conscience of Oracle, and the other 45,000 of us are       criminals?” Ellison asked. “It&#39;s astounding. We don&#39;t sell products that       don&#39;t exist because it&#39;s against the law.”       Even while he was at Oracle, Lane was sometimes outspoken on the subject of       Ellison. Once, for example, he described how top executives of Boeing Corp.       were no longer dealing with Oracle about an important “business-to-business”       contract because they were angry that Ellison had publicly stated,       incorrectly, that Oracle had won the deal.       Front Page, Tech Center, Money and Investing, Subscribe to wsj.com       And his latest comments about Oracle should be viewed in the context of       his new job. At Kleiner Perkins, he will be helping start-up companies in       business-to-business software and services, some of which may potentially       compete with Oracle.       Lane said he was attracted to the venture-capital job in large part because       it will mean less travel. “When you are spending 70 percent of your time on       airplanes, you have to step back and say, ‘Why am I doing this?’ ” He also       predicted a looming shakeout at many Internet companies, which will make his       sort of operational experience even more valuable, since he will be able to       provide guidance to the surviving companies.       Lane was originally slated to stay on Oracle&#39;s board following his departure.       He said Wednesday, though, that he might leave it in the fall, when his term       expires.       More stories on: Ellison vs. Lane       See also: Business section       Talkback:       Ellison claims “We don&#39;t sell p . . . - Daniel Welch       Sounds like Gates, Jobs and any . . . - de       The answer to Ellison&#39;s rhetori . . . - john major       Let me be the first to say that . . . - Les Claypool       I find that throughout life tha . . . - John Bannon       Les −&gt; Nah . . . It&#39;s all Sun&#39;s f . . . - Dave Rothgery       Les: I really didn&#39;t start . . . - Phluux       Les Claypool, you forgot about . . . - mars boni       Did you ever notice its the com . . . - Mark Haliday       Anyone who believes Larry Ellis . . . - John Simpson       Mr. Ellison is the bad guy . . . . . . - Chris Papoudaris       Always research the company beh . . . - Dollie       Mark, actually I noticed compan . . . - Zheam       Did you ever notice how similar . . . - MC       05:46a NEC sets sail with Transmeta&#39;s Crusoe       05:46a Excite@Home offers do-it-yourself cable       05:39a Madonna gives cybersquatter the boot       04:44a Investor AM: Catalyst wanted to spur tech stocks       04:28a AMD ships 1.2GHz Athlons       More . . .       AOL wireless: No training wheels?       EFF defends nameless Netizens       Open-source angst: Fear of forking       NEC sets sail with Transmeta&#39;s Crusoe       Investor AM: Desperate for a catalyst       SDMI denies broken technologies       Business       Microsoft defectors gain momentum       Stock? Net execs want the cash       Commentary       Slater: Napster rocks the music world       Coursey: Is StarOffice Sun&#39;s ‘survivor’?       Computing       Sony launches Crusoe-based laptop       Handspring adds color PDA, GameFace       Internet       Outsider vows to clean up ICANN       Pop the cork on broadband bottlenecks       eCrime and Law       Cybersecurity: Don&#39;t trust the Feds!       Mitnick hacks federal DNA database       Mac       Apple: Two routes to Mac OS X       Apple cheers on MS at Office party       Oracle Corp.       Enter a company       Sponsored Links       Looksmart: Drive users to your site with Express Submit!       Rackspace: Managed Hosting in 24 hours or less.       No Credit? Get a MasterCard with NO Credit Checks!       ORACLE Zero to Portal @ Web Speed-Click here for a free Kit       PlanBee Free download - new personal productivity Internet tool       GREAT PC ClientPro Cn - 600MHz w/ 7.5 GB hard drive, from $1425!       Intel Manufacturer ShowcaseNeed More Help?       Shop Now!Shop at Dell&#39;s Home Solution Center - Dell Small Business       Center       Shop Now!Gateway Home Computing Center       Featured Links       Best Buys Shop Smart for scanners, digital cameras, monitors &amp; more!       Get Help! Ask an expert a technical question -- LIVE!       Red Herring RISK-FREE! For insight into the business of technology.       Magazine Offers       LastChance Get Your Free Premiere Trial Copy of Expedia Travels!       Tech Jobs |ZDNet e-centives |Free E-mail |Newsletters |       Updates |MyZDNet |Alerts |Rewards |Join ZDNet |Members |       SiteBuilder       Feedback |Your Privacy |Service Terms |Advertise |About Us       Copyright © 2000 ZD Inc. All rights reserved. ZDNet and the ZDNet       logo are registered trademarks of ZD Inc.                  
 
           [0035]    When a text summarizer such as the NRC Extractor is used on a text-only version of a web page, the results are less than satisfying, as can be seen from the following keywords and keyphrases extracted by the NRC Extractor from the text-only version of Table 1.  
           [0036]    Keyphrases: Lane, Ellison, Oracle, ZDNet, business, news, Larry  
           [0037]    Highlights: 1. ZDNet&gt;ZDNet News Page One&gt;Business&gt;Lane gets new job, blasts Ellison. 2. Ray Lane, former No. 2 executive at Oracle Corp., hardly has a bad thing to say about his former employer—except that it is a company full of yes men who tend to be less than candid about their products. 3. Coop&#39;s Corner: Larry Ellison and Basura-gate  
           [0038]    From the web page of FIG. 1, it can be calculated that the useful portion of the document represents 57% of the contents of the web page (about 850 relevant words on a total of 1500). Therefore, 43% of the words of the document include links, comments, headers, footers, etc. Knowing that the success rate of Extractor is approximately 80%, only 57% * 80% of the KeyPhrases extracted directly from a website will be accurate, that is, about 45%.  
           [0039]    Here are the keywords extracted by Extractor directly from the ZDNet article shown in FIG. 1: Lane, Ellison, ZDNet, Oracle, business, news, Larry, Tech, Shop, executives, Internet, blasts Ellison. The bolded keywords ({fraction (5/12)}=41%) were extracted because of the 43% of irrelevant words. The extracted highlights are as follows: 1. ZDNet: News: Lane gets new job, blasts Ellison. 2. Business&gt;. 3. Former top lieutenant Ray Lane and Oracle CEO Larry Ellison continue to battle, even as Lane takes a job with Kleiner Perkins. 4. Ray Lane, former No. 2 executive at Oracle Corp., hardly has a bad thing to say about his former employer—except that it is a company full of yes men who tend to be less than candid about their products.  
           [0040]    Most news-related web pages and HTML-created emails contain frames which are non-relevant to the contents of the news article. These frames contain links to related articles, to other web sites or publicity. This information can be useful for the visitor of the web site but are irrelevant to the subject discussed. Eliminating such frames is therefore useful for both extracting the contents of the page and, eventually, summarizing this content. Most of the time, these frames are placed in HTML tables. These tables help setting the display of the page and its semantics.  
           [0041]    International application WO 98/47083 to Richard Weeks describes a method for summarizing data sets in which appearances of specific keywords are counted and the keywords are ranked to extract the most used keywords and produce a summary of the initial text.  
           [0042]    The article entitled “Extracting Semistructured Information From The Web” published by Hammer J et al. on Mar. 16, 1997 presents a method for moving data from the WWW into databases to ensure that data can be searched more efficiently. It describes an extractor which can isolate HTML pages and convert that data into database objects.  
           [0043]    There is therefore a need for a text extractor which cleans superfluous content from web pages, especially when this superfluous content is placed in tables in order to extract only the most meaningful content.  
         SUMMARY OF THE INVENTION  
         [0044]    Accordingly, a first object of the present invention is to extract only the relevant information from a document to facilitate the summarizing of the document.  
           [0045]    According to a first broad aspect of the present invention, there is provided a method of extracting a portion of text from a document including a plurality of layout cells in at least one table defining a layout of the document. The method comprises identifying layout cells within the document, the layout cells defining a layout of text entities within the document; calculating statistics parameters of the layout cells, at least one of the statistics parameters being the number of words in the layout cells; attributing a point value for each of the layout cells using at least one of the statistics parameters; ranking the layout cells according to the point value; selecting at least one of the layout cells whose point value is above a predetermined threshold; extracting a text content of the selected layout cells.  
           [0046]    According to a further aspect of the present invention, there is provided a computer readable memory for storing programmable instructions for use in the execution in a computer of the process of the method of extracting a portion of text from a document.  
           [0047]    According to still another aspect of the present invention, there is provided a method of extracting a portion of text from a document including at least one table and cells within the at least one table, for the purposes of generating a summary of contents of the document. The method comprises the step of receiving a signal, the signal containing text extracted according to the method of extracting a portion of text from a document.  
           [0048]    According to a further aspect of the present invention, there is provided, in a method of extracting a portion of text from a document including at least one table and cells within the at least one table, for the purposes of generating a summary of contents of the document, a computer data signal embodied in a carrier wave comprising text extracted according to the method of extracting a portion of text from a document.  
           [0049]    According to another aspect of the present invention, there is provided a system for extracting a portion of text from a document including at least one table and cells within the at least one table, for the purposes of generating a summary of contents of the document. The system comprises: a cell identifier for identifying cells within the document; a statistics calculator for determining a text size of the cells; a cell selector for selecting some of the cells using the text size of the cells; a text extractor for extracting in a text only output a text content of the selected cells; whereby the text only output extracted can be used to produce a summary of a portion of text of the document excluding text from non-selected cells.  
       
    
    
     BRIEF DESCRIPTION OF THE DRAWINGS  
       [0050]    These and other features, aspects and advantages will become better understood with regard to the following description and accompanying drawings, wherein:  
         [0051]    [0051]FIG. 1 is a screen shot of a news web page in which formatting tables have been highlighted;  
         [0052]    [0052]FIG. 2 is an illustration of the internal structure of a document;  
         [0053]    [0053]FIG. 3 is a web page created using the source code of Table 3;  
         [0054]    [0054]FIG. 4 is resulting hierarchical tree structure of the web page document of FIG. 3 using the algorithm of Table 2;  
         [0055]    [0055]FIG. 5 is a flow chart of the method according to a preferred embodiment of the present invention; and  
         [0056]    [0056]FIG. 6 is a block diagram of a system according to a preferred embodiment of the present invention. 
     
    
     DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT  
       [0057]    [0057]FIG. 1 shows a web page of news which contains many tables. Each table has been framed to illustrate the number of tables and sub-tables used to display and organize the contents of the web page. The web page shown was available at www.zdnet.com/zdnn/stories/news/0,4586,2619342,00.HTML on Oct. 17, 2000. It contains a news article entitled “Lane gets new job, blasts Ellison”, written by Lee Gomes, published on Aug. 24, 2000. As with many news-related web sites, the page contains, in addition to the text of the article, many additional links, images, ads and comments distributed around the core content of the article.  
         [0058]    [0058]FIG. 2 is the preferred internal structure used to work with the HTML document which contains tables. It shows how using tables facilitates the organization of the information and also how the body text of the page can be buried in sub-tables of sub-tables. As is apparent from FIG. 2, each cell  46  belongs to one table  45 , each table  45  has one or more cells  46 , each cell  46  has one or more cell items  47 , each cell item  47  belongs to one cell  46 . A cell item  47  can be text  48  or another table  49 . This is the structure used by the algorithm of the present invention to extract information.  
         [0059]    The preferred embodiment of the present invention, uses essentially two main steps: 1) Document Structure Extraction and Accumulation of Statistics on the Contents of the Document. 2) Tally of the Points and Generation of the Results.  
         [0060]    Document Structure Extraction and Accumulation of Statistics on the Contents of the Document.  
         [0061]    The first step consists in reading the document object model (DOM) of a document and to transform it into a representation of its internal structure (as shown in FIG. 2) which is more user friendly, at an algorithm level, at a processing level and at a programming level. The DOM is received as a COM object of type IHTMLDocument2 (MSHTML). The Document Object Model (DOM) is a standard internal representation of the document structure and is used to easily access components and delete, add or edit their content, attributes and style. In essence, the DOM makes it possible for programmers to write applications which work properly on all browsers and servers, and on all platforms. While programmers may need to use different programming languages, they do not need to change their programming model. The Document Object Model is a platform- and language-neutral interface that will allow programs and scripts to dynamically access and update the content, structure and style of documents. There are a plurality of versions called levels of DOM. The first, the DOM XML, relies on an internal tree-like representation of the document, and enables to traverse the hierarchy accordingly. The standard model of viewing a document is as a hierarchy of tags, with the computer building up an internal model of the document based on a tree structure. Meanwhile the HTML DOM provides a set of convenient easy-to-use ways to manipulate HTML documents. The initial HTML DOM merely describes methods (for example), for accessing an identifier by name, or a particular link. The HTML DOM is sometimes referred to as DOM Level 0 but has been imported into DOM Level 1. The HTML and XML DOMs form part of DOM level 1. DOM level 2 includes DOM level 1 but adds a number of new features. IHTMLDocument2 is the implementation done by Microsoft of the HTML DOM Level 2.  
         [0062]    Once the structure of the DOM is represented in a user friendly format, it is then possible to extract data useful for compiling statistics on the contents by traveling through this hierarchical structure. Table 2 below is a simplified version of the pseudo-code of the preferred embodiment of the present invention which allows such an extraction.  
                                                                                                                                                                                                                                                                       TABLE 2                       Document Structure Extraction and Accumulation of Statistics       on the Content                                ExtractDocumentStructure(p_Document : IHTMLDocument2) : KTable       Begin                Ktable parsedDocument           // Extract Document Title           //           KcellItem pCellItem.Text(p_Document.get_title( ));           Kcell pCell.AddCellItem(pCellItem);           parsedDocument.AddCell(pCell);           // Get a pointer to the body element.           //           IHTMLDOMNode pBodyNode = p_Document.get_body( );           // And parse the document.           //           Kcell pBodyCell;           RecursiveParse( pBodyNode, pBodyCell, false );           parsedDocument.AddCell(pBodyCell);           return parsedDocument;            End       RecursiveParse(p_Node:IHTMLDOMNode, p_Cell:KCell, p_bInHref:bool)       Begin                // Iterate through all children.           //           IHTMLDOMNode pNodeCurrent = p_Node;           while( pNodeCurrent )           Begin                if( pNodeCurrent == IHTMLDOMTextNode )           Begin                // It is a text only node.           // Extract text and add it to current cell           KcellItem pCellItem(pNodeCurrent.get_data( ));           // Compute word stats.           //           integer nWords = CountWords(pCellItem);           p_Cell−&gt;AddWords( nWords, p_bInHref );                end           else if( pNodeCurrent == IHTMLAnchorElement )           Begin                // If it is a &lt;A HREF&gt;, proceed with the children.           If( pNodeCurrent.hasChildNodes( ) )           begin                // We now are inside a Href.           if( !p_bInHref )                p_Cell.AddLinks( 1 );           IHTMLDOMNode pChild = pNodeCurrent.get_firstChild( );                RecursiveParse( pChild, p_Cell, true );                end                End           else if( pNodeCurrent == IHTMLImageElement )           Begin                p_Cell.AddImages( 1 );           KcellItem pCellItem(pNodeCurrent.get_alternateText( ));           // Compute word stats.           //           integer nWords = CountWords(pCellItem);           p—Cell−&gt;AddWords( nWords, true );                End           else if( pNodeCurrent == IHTMLTable )           Begin                p_Cell.AddTables( 1 );           // If it is a table, proceed with all table cells           //           Ktable  pSubTable;           KcellItem pNewCellItem.Table(pSubTable);           p_Cell.AddCellItem( pNewCellItem );           // Retrieve column and row information.           //           pSubTable.Dimensions=GetTableDimensions(pNodeCurrent);           // Retrieve table caption.           //           IHTMLDOMNode pCaption = pNodeCurrent.get_caption();           RecursiveParse( pCaption, subTable.Caption, false );           // Retrieve table summary.           //           IHTMLDOMNode pSummary = pNodeCurrent.get_summary( );           RecursiveParse( pSummary, subTable.Summary, false );           // Extract content cell by cell           //           for(integer iRow=0; iRow&lt;pSubTable.RowCount; iRow++ )           begin                for(integer iCell=0; iCell&lt;pSubTable.CellCount; iCell++)                Begin                IHTMLTableCell pCell = pNodeCurrent.get_cell(iRow,iCell);           KCell newCell;           // Extract content           RecursiveParse( pCell, newCell, false );           subTable.TableCell(iRow, iCell) = newCell;                End                end                End           Else           Begin                // Proceed with the children.           //           If( pNodeCurrent.hasChildNodes( ) )           begin           IHTMLDOMNode pChild = pNodeCurrent.get_firstChild( );           RecursiveParse( pChild, p_Cell, p_bInHref );           end                End           pNodeCurrent = pNodeCurrent.get_nextSibling( );                End            End                  
 
         [0063]    Although the previous algorithm only supports the DOM2 implementation of Microsoft (the library MSHTML which contains the objects IHTMLDocument 2, IHTMLOMNode, IHTMLDOMTextNode, IHTMLTableElement, . . . ). It is to be understood that it would be apparent to one skilled in the art to introduce code for customers who do not have the DOM2 implementation of Microsoft.  
         [0064]    Table 3 is an example of HTML source code used to display the web page of FIG. 3. FIG. 3 is a web page created using the source code of Table 3. It comprises introductory text  55 , a hyperlink  56  in line 1, col. 1 of table 1, a text entry in line 2, col. 1 of table 1, an image  59  and a test entry  58  at line 1, col. 2 of table 1 together with alternate text  60  and a table  62  within a cell  61  of a table at line 2, col. 2 of table 1.  
                                                                                                                                                                                             TABLE 3                       Source code used to create the web page of FIG. 3                                &lt;HTML&gt;       &lt;HEAD&gt;                &lt;TITLE&gt;Document Sample.&lt;/TITLE&gt;            &lt;/HEAD&gt;       &lt;BODY&gt;       First Text.       &lt;TABLE border&gt;                &lt;TR&gt;                &lt;TD&gt;                &lt;A Href=“www.copernic.com”&gt;Table 1, line 1, column 1&lt;/A&gt;                &lt;/TD&gt;                &lt;TD&gt;Table 1, line 1, column 2,                &lt;IMG SRC=“http://www.copernic.com/images/left-navbar/more-            button.gif” ALT=“Alternate Text”&gt;                &lt;/TD&gt;                &lt;/TR&gt;           &lt;TR&gt;                &lt;TD&gt;Table 1, line 2, column 1&lt;/TD&gt;           &lt;TD&gt;Table 1, line 2, column 2                &lt;TABLE border&gt;                &lt;TR&gt; &lt;TD&gt;Table 2, line 1, column 1&lt;/TD&gt; &lt;/TR&gt;                &lt;/TABLE&gt;                &lt;/TD&gt;                &lt;/TR&gt;            &lt;/TABLE&gt;       &lt;/BODY&gt;       &lt;/HTML&gt;                  
 
         [0065]    [0065]FIG. 4 is an example of the hierarchical structure of the document obtained using the pseudo-code of Table 2 on the web page of FIG. 3. The whole web page is considered to form Table0 70. It has two rows and one column, it doesn&#39;t have a caption or a summary and has a number KCell of cells. Its title  70  is in a text string  72  equal to “Document Sample”. The body of the table  73  comprises cell items. The first cell item is a string of text  74  comprising “First Text.” The second cell item is a table  75 . Table  75  has 2 rows and 2 columns  76 . Table  75  has four items as follows: a text string  78  in cell  77 , a text string  80  and some alternate text  81  in cell  79 , a text string  83  in cell  82  and a text string  85  together with another table  86  in cell  84 . The table  86  comprises 1 row and 1 column and the only cell  88  comprises a text string  89 .  
         [0066]    Tally of the Points and Generation of the Results.  
         [0067]    The generation of the results is preferably the following:  
         [0068]    1. Extract statistics (such as number of words, depth, etc.) from the whole document;  
         [0069]    2. Travel through all tables of the document and tally their points (RankTable);  
         [0070]    2.1. If the number of points of a table is too low, (LowThreshold), remove the table;  
         [0071]    3. Sort the tables in order of number of points;  
         [0072]    4. Identify the tables with the highest numbers of points (HiThreshold) and save them in the GoodTables list;  
         [0073]    5. Travel through the GoodTables list. For each sub-table of a table of the GoodTables list;  
         [0074]    5.1. If its number of points is high enough (WinnerLowThreshold), the table is added to the GoodTables list;  
         [0075]    6. Generate the results by travelling through all tables of the document;  
         [0076]    6.1. If the current table is in the GoodTables list, travel through all of its cells;  
         [0077]    6.1.1. Calculate the number of points of each cell (RankCell)  
         [0078]    6.1.2. If the number of points of each cell is sufficient (CellLowThreshold), extract the text from the cell.  
         [0079]    Following is a table of the thresholds used during the tally of points:  
                                 TABLE 4                           Preferred Thresholds used.            Low-                   Threshold   HiThreshold   WinnerLowThreshold   CellLowThreshold               0.20   0.05   0.30   0.50                  
 
         [0080]    Extracting Statistics from a Table(GetTableStatistics)  
         [0081]    GetTableStatistics(p_Table: KTable): KStatistics  
         [0082]    For all cells of the table  
         [0083]    1 NumberOfWords=Calculate the total number of words in the table.  
         [0084]    2 NumberOfWordsInLinksOrInImages=Calculate the number of words in the links or the images.  
         [0085]    3 NumberOfCells=Calculate the total number of cells.  
         [0086]    4 WordsPerCell=(NumberOfWords−NumberOfWordsInLinksOrInImages)/NumberOfCells  
         [0087]    It will be understood that the number of words calculation can be modified to be a count of the number of characters, the number of bits or can be transformed to be a count of the number of sentences (by identifying an uppercase letter followed by a plurality of characters and, eventually, a period), a number of meaningful words (by removing occurrences of “the”, “a”, “an”, “but”, “and”, etc.). One could also choose to count cells if they contain at least one verb or at least a period.  
         [0088]    Calculating the Number of Points of a Table (RankTable):  
         [0089]    RankTable(p_Table: KTable, p_MainStats: KStatistics): float  
         [0090]    Score=0, Depth=0  
         [0091]    For all sub-tables of p_Table of depth Depth (0 . . . n):  
         [0092]    1. TableStats=Extract table statistics (GetTableStatistics)  
         [0093]    2. DepthFactor=½*Depth  
         [0094]    3. LocalScore+=DepthFactor*LinkDensityFactor*(1−TableStats.NumberOfWordsInLinksOrInImages/TableStats.NumberOfWords)  
         [0095]    4 LocalScore+=DepthFactor*WordsPerCellFactor*TableStats.WordsPerCell/p_MainStats.MaximumWordsPerCell  
         [0096]    5 LocalScore+=DepthFactor*WordCountFactor*(TableStats.NumberOfWords−TableStats.NumberOfWordsInLinksOrInImages)/(p_MainStats.NumberOfWords−p_MainStats.NumberOfWordsInLinksOrInimages)  
         [0097]    6 Score=Score+LocalScore/(Number of tables of depth Depth)  
         [0098]    The tally of points function uses a two-dimensional scale. The points are calculated by the characteristics of the table and by all of the characteristics of the items dependent from the table. The deeper a sub-table is in the hierarchical tree of structure of the page, the less it contributes to the final number of points. All tables of a specified depth (Depth) contribute to the final amount of points equally. Following is a table of the scale used for the tally of points.  
                                 TABLE 5                           Scale Preferably Used to Tally the Points.                LinkDensityFactor   WordsPerCellFactor   WordCountFactor       Depth   0.33   0.33   0.33               1   (½ 1 ) * 0.33 = 0.165   (½ 1 ) * 0.33 = 0.165   (½ 1 ) * 0.33 = 0.165       2   (½ 2 ) * 0.33 = 0.0825   (½ 2 ) * 0.33 = 0.0825   (½ 2 ) * 0.33 = 0.0825       3   (½ 3 ) * 0.33 = 0.04125   (½ 3 ) * 0.33 = 0.04125   (½ 3 ) * 0.33 = 0.04125       . . .       n   (½ n )        *   (½ n )        *   (½ n )        *           LinkDensityFactor   WordsPerCellFactor   WordCountFactor                  
 
         [0099]    The values of the parameters HiThreshold, WinnerLowThreshold, CellLowThreshold, LinkDensityFactor, WordsPerCellFactor and WordCountFactor are preferred values which have been obtained through experimentation. These values are independent of the properties of the documents such as their size, their origin, etc. It would be possible to use other values to obtain a suitable set of parameters for the extraction.  
         [0100]    It should be understood that all counts done on contents of cells can be weighted by parameters to emphasize the importance of characteristics of the cells. It should therefore be understood that all additions, subtractions and multiplication can be weighted by appropriate parameters.  
         [0101]    Calculating the Number of Points of a Cell (RankCell):  
         [0102]    During the final pass for the generation of results, a last tally of points is done at the cell&#39;s level (RankCell). This tally of points is used to eliminate the cells which contain too many links with respect to body text.  
         [0103]    RankCell(p_Cell: KCell): float  
         [0104]    Return (1−p_Cell.NumberOfWordsInLinksOrInImages/NumberOfWords)  
         [0105]    [0105]FIG. 5 is a flow chart of the general methodology used in the previous algorithms. The cells in the document are identified  100 , then, a text size for these cells is determined  101 . Some cells are then selected using the text size information  102 . For the cells selected, the text content is extracted from the cells  103 . An optional step of summarizing the document using the content extracted from the cells is then possible  104 .  
         [0106]    [0106]FIG. 6 is a block diagram of a system according to a preferred embodiment of the present invention. A document  110  with cells is provided. A cell identifier  111  identifies the cells within the document  110 . A statistics calculator  112  uses the document  110  to calculate statistics on at least some of the cells of the document. A cell selector  113  uses the list of cells identifies and the statistics together with the document to select the cells relevant to the contents of the document. A text extractor  114  uses the list of cells selected and the document  110  to extract the text output  115 .  
         [0107]    When the previous algorithms are used on the web page of FIG. 1, the text extracted contains 860 words of which 100% (850 words) of the relevant words contained in the news article portion of the web page document. The extracted text is as follows in Table 6:  
                     TABLE 6                       Extracted text                                Lane gets new job, blasts Ellison-       Former top lieutenant Ray Lane and Oracle CEO Larry Ellison continue to       battle, even as Lane takes a job with Kleiner Perkins.       By Lee Gomes , WSJ Interactive Edition-       August 24, 2000 7:51 AM PT-       Ray Lane, former No. 2 executive at Oracle Corp., hardly has a bad thing to       say about his former employer -- except that it is a company full of yes men       who tend to be less than candid about their products.       Lane abruptly left the business-software giant in June after an eight-year       stint. One reason was that his responsibilities as president and chief       operating officer had been reduced by Lawrence Ellison, Oracle&#39;s (Nasdaq:       ORCL ) chief executive. Lane, 53 years old, said following his departure that       he wanted to devote more time to his two young children by his second       marriage.       More stories on: Ellison vs. Lane       Wednesday, Lane announced that he will become a general partner at Kleiner       Perkins Caufield &amp; Byers, the prominent Silicon Valley venture-capital firm.       And in an interview scheduled with that announcement, Lane harshly criticized       Ellison, making clear that his departure from Oracle wasn&#39;t amicable. In       response to Lane&#39;s comments, Ellison strongly defended himself and the       company.       A great admirer yet-       Lane said he remains a great admirer of Oracle and Ellison. He said, for       example, that Ellison&#39;s oversight of the main Oracle database product in the       early 1990s “saved” the company, and that lately, Ellison has “reinvigorated”       Oracle to take advantage of the opportunities presented by the Internet. That       work made Lane&#39;s net worth, based largely in Oracle stock, soar to nearly a       billion dollars.       But Lane also said that Ellison is utterly dominating the company right now,       something that might prove to be harmful in the long run, since Oracle won&#39;t       be able to develop the strong management team it needs.       ‘[The Oracle executives] aren&#39;t leaders. They just do what Larry says. They       wouldn&#39;t know how to make a decision without Larry making it for them.’-       -- Ray Lane, former No. 2 executive at Oracle-       “It&#39;s just like with kids,” Lane said. “If you make all their decisions for       them, they will go out as adults not knowing how to make decisions       themselves.” The executives now reporting to Ellison, said Lane, “are not       decision makers. They aren&#39;t leaders. They just do what Larry says. They       wouldn&#39;t know how to make a decision without Larry making it for them.”       Lane came to Oracle, of Redwood Shores, Calif., in 1992 at a time when the       company&#39;s credibility in the market was low. He said Wednesday that studies       he commissioned at that time found that many customers “would never do       business again with a Larry Ellison company.”       The reason, Lane said, is that Oracle would sell products it didn&#39;t have.       “Larry is a visionary, and expresses the vision so well that people believe       it&#39;s a product.” When he first got to Oracle, Lane said, “managers would be       willing to take the order and make a lot of money,” even though the products       often didn&#39;t exist. “That&#39;s the discipline I put into the company,” he said.       “I told the sales force, ‘After what Larry says is the vision, tell the       customer the truth about what we can actually deliver.’ ”       ‘Needs more balance’-       Lane indicated that he is worried that with him gone, Oracle might lapse back       to its old ways. “The company needs more balance,” he said.       Ellison rejected his former deputy&#39;s criticisms.       Oracle&#39;s managers, Ellison said, were in many cases chosen by Lane himself.       “He is criticizing his own team for being weak. When did they become yes men?       I am thrilled they are all here. They are delivering exceptional results.”       Ellison also said the company doesn&#39;t sell products it doesn&#39;t have.       “He is the soul, the conscience of Oracle, and the other 45,000 of us are       criminals?” Ellison asked. “It&#39;s astounding. We don&#39;t sell products that       don&#39;t exist because it&#39;s against the law.”       Even while he was at Oracle, Lane was sometimes outspoken on the subject of       Ellison. Once, for example, he described how top executives of Boeing Corp.       were no longer dealing with Oracle about an important “business-to-business”       contract because they were angry that Ellison had publicly stated,       incorrectly, that Oracle had won the deal.       And his latest comments about Oracle should be viewed in the context of his       new job. At Kleiner Perkins, he will be helping start-up companies in       business-to-business software and services, some of which may potentially       compete with Oracle.       Lane said he was attracted to the venture-capital job in large part because       it will mean less travel. “When you are spending 70 percent of your time on       airplanes, you have to step back and say, ‘Why am I doing this?’ ” He also       predicted a looming shakeout at many Internet companies, which will make his       sort of operational experience even more valuable, since he will be able to       provide guidance to the surviving companies.       Lane was originally slated to stay on Oracle&#39;s board following his departure.       He said Wednesday, though, that he might leave it in the fall, when his term       expires.       See also: Business section-       Enter a company-                  
 
         [0108]    This extracted text can then be put through a summarizer of the prior art to obtain a relevant summary. For example, if the previous extracted text is put through the summarizer of CNRC, the following summary is obtained (which is fully relevant):  
         [0109]    Keyphrases: Lane, Oracle, Ellison, Larry, Executives, Business, Kleiner Perkins, Ray Lane, Vision, sell products, Managers, chief operating officer.  
         [0110]    Highlights: 1. Lane gets new job, blasts Ellison-Former top lieutenant Ray Lane and Oracle CEO Larry Ellison continue to battle, even as Lane takes a job with Kleiner Perkins. 2. The executives now reporting to Ellison, said Lane, “are not decision makers. 3. He said Wednesday that studies he commissioned at that time found that many customers “would never do business again with a Larry Ellison company.” 
         [0111]    While the invention has been described in connection with specific embodiments thereof, it will be understood that it is capable of further modifications and this application is intended to cover any variations, uses, or adaptations of the invention following, in general, the principles of the invention and including such departures from the present disclosure as come within known or customary practice within the art to which the invention pertains and as may be applied to the essential features hereinbefore set forth, and as follows in the scope of the appended claims.