Case 1:13-cv-00919-LPS Document 307-7 Filed 03/10/21 Page 1 of 28 PageID #: 26824
`
`EXHIBIT 26 - Part 2
`
`

`

`Case 1:13-cv-00919-LPS Document 307-7 Filed 03/10/21 Page 2 of 28 PageID #: 26825
`
`'843 Patent Claims
`
`Claim 19
`A method according to claim 1,
`wherein performing the action
`includes causing insertion of at
`least part of the second information
`into the document by the first
`computer program.
`
`Exhibit C-7
`
`Disclosure
`an artifact of Apple Data Detectors' ability to find more than one
`structure in a selection and the need to offer more than one action for the
`same structure (such as 'open URL' and 'place URL in hot list'). But
`multiple structures and actions are of benefit to users in terms of their
`being able to choose the structure to be manipulated and to choose the
`action to be employed. Users therefore remain in control of their work
`with the computer at all times."
`
`See also Nardi at 102: "We also see evidence that end users with
`varying degrees of programming skill are extending actions much as we
`had expected. One user—a skilled programmer—used the basic
`detectors and actions that ship with the product as the basis for a new
`detector/action pair for a personally relevant task. He wanted to look
`up software bug reports in a database based on the ID numbers of the
`reports commonly found in other bug reports, email messages, and other
`program management documents. He distributed this detector/action
`throughout his work group, and a colleague—a marketing manager with
`much less programming experience than the original programmer—was
`able to adapt the action so the detector could run on his laptop computer
`(where his email and other documents reside) and display the bug reports
`on his desktop machine (where is program management tools reside).
`This extension required changes to only a few lines of code in the action,
`something well within his technical ability."
`
`If the Judge or Jury finds that IAD or the IAD System does not disclose
`this element, the element and the claim are still rendered obvious for the
`reasons stated in Exhibit F, Table 5.
`
`When IAD detects an email address and a user selects "Send mail with
`Claris Emailer," Claris Emailer will search its information source for a
`company name associated with the domain of the email address and will
`insert this into the Outgoing Message panel for a new email. For
`example:
`
`31
`
`

`

`Case 1:13-cv-00919-LPS Document 307-7 Filed 03/10/21 Page 3 of 28 PageID #: 26826
`
`Exhibit C-7
`
`'843 Patent Claims
`
`Disclosure
`
`1
`
`"^i
`
`ffi
`
`Out Bo
`
`ij • g
`Subject |f
`S jmillei
`0 1 Tgp»
`I
`0 To ®
`
`N ^
`
`*
`
`^.CD a^nr
`
`Outgoinq Message;
`
`•BfBiWTfW
`
`SWOYU |
`
`R»Ctp>»fit
`
`Ad-jrpc?
`
`jmilWr
`
`AppW Computer
`
`22!!
`
`dP
`
`-
`
`When a user selects text and right-clicks in Simple Text, IAD can detect
`occurrences of a city name followed by a state name or US Postal
`abbreviation and occurrences of the name of a state, territory, or
`protectorate of the United States and provide options. The user could
`then obtain a map of the selected US city, for which the system would
`search the Yahoo map website for a map of the city, or the user could
`obtain a zip code for the selected US city, for which the system would
`search the US Postal Serv ice website for a list of zip codes for the city.
`See US Geographic Detectors 1.0 Read Me file. For example;
`
`s'Vle Sound Help
`
`[t^Vsjo^Poio Alto. CA and se^hoT^herT
`
`Help
`
`Get Map for US City
`luukup Ziptode for lis City |
`
`This feature was available in a Claris Emailer email as well, and starting
`with Claris Emailer version 2.0v3, a user needed to only right-click (and
`not select text) to obtain a list of actions for geographic information.
`
`See also Nardi at 98: "Our first step was to find a user problem that
`needed solving in which intelligent agents would add value.
`In an
`investigation of how people file information on their computer desktops
`[1], we discovered that a common user complaint is that they cannot
`easily take action on the structured information found in everyday
`documents (structured information being data-recognizable by a
`grammar). Ordinary documents are full of such structured information:
`phone numbers, fax numbers, street addresses, email addresses, email
`signatures, abstracts, tables of contents, lists of references, tables,
`figures, captions, meeting announcements, Web addresses, and more.
`In addition, there are countless domain-specific structures .... These
`
`32
`
`

`

`Case 1:13-cv-00919-LPS Document 307-7 Filed 03/10/21 Page 4 of 28 PageID #: 26827
`
`'843 Patent Claims
`
`Exhibit C-7
`
`Disclosure
`structures are not only relevant to users, but because of their structure,
`are also recognizable by parsing technologies. Once identified, the
`structure's type can be used to identify appropriate actions that might be
`carried out, like placing a meeting on a calendar, adding an address to an
`address book, dialing a phone number, opening a URL, finding the
`current price of a stock, filing an ISBN number, and compiling a list of
`abstracts.
`
`Apple Data Detectors supports a wide range of uses. Think of all the
`structured information in the documents you work with; in addition to
`those mentioned already, add bibliography items, forms (such as travel
`expensive reports and non-disclosure agreements), executive summaries,
`and most important, such domain-specific kinds of data as legal
`boilerplate, customer orders, and library search requests. Specific
`detectors can be created for each of these types of information."
`
`See also Nardi at fig. 4: "This script can be activated when the system
`detects a telephone number.
`It then generates word processor letterhead
`addressed to the person possessing that number, with appropriate date
`and salutation information. This script uses two applications: First, a
`'personal information manager' (Now Contact 3.5) is opened and used as
`a database. Then the script opens an empty word processor document
`(via Corel WordPerfect) and writes the date, name, address and
`salutation into it, leaving the user ready to write the letter."
`
`"While Apple and third-party developers will
`See also Nardi at 99:
`provide many detectors and actions, it is clear that enabling end users to
`write their own detectors and actions will make Apple Data Detectors
`much more powerful and useful by providing domain-specific
`programming capabilities appropriate for the specific needs of specific
`users [8]."
`
`See also Nardi at 101: "Unlike systems based on predefined
`recognizer/action pairs, such as the Selection Recognition Agent [10],
`the Apple Data Detectors' scripting ability allows any set of arbitrary
`actions to be executed when the user selects a particular action (see
`Figure 3). Scripting is not limited to the parameters of a command line
`interface to the application; it can do anything that can be expressed in
`the scripting language, including manipulation of data structures inside
`the application, if the application's scripting model makes that possible."
`
`See also Nardi at 101: "The ability to work within existing documents
`provides immediate user value and leverages the data that the user is
`already using."
`
`See also Nardi at 101: "Having to choose a particular action is actually
`
`33
`
`

`

`Case 1:13-cv-00919-LPS Document 307-7 Filed 03/10/21 Page 5 of 28 PageID #: 26828
`
`Exhibit C-7
`
`Disclosure
`an artifact of Apple Data Detectors' ability to find more than one
`structure in a selection and the need to offer more than one action for the
`same structure (such as 'open URL' and 'place URL in hot list'). But
`multiple structures and actions are of benefit to users in terms of their
`being able to choose the structure to be manipulated and to choose the
`action to be employed. Users therefore remain in control of their work
`with the computer at all times."
`
`See also Nardi at 102: "We also see evidence that end users with
`varying degrees of programming skill are extending actions much as we
`had expected. One user—a skilled programmer—used the basic
`detectors and actions that ship with the product as the basis for a new
`detector/action pair for a personally relevant task. He wanted to look
`up software bug reports in a database based on the ID numbers of the
`reports commonly found in other bug reports, email messages, and other
`program management documents. He distributed this detector/action
`throughout his work group, and a colleague—a marketing manager with
`much less programming experience than the original programmer—was
`able to adapt the action so the detector could run on his laptop computer
`(where his email and other documents reside) and display the bug reports
`on his desktop machine (where is program management tools reside).
`This extension required changes to only a few lines of code in the action,
`something well within his technical ability."
`
`If the Judge or Jury finds that IAD or the IAD System does not disclose
`this element, the element and the claim are still rendered obvious for the
`reasons stated in Exhibit F, Table 5.
`
`A computer running IAD would contain a storage medium containing the
`IAD program.
`
`The User Manual states at pp. 1-2:
`
`'843 Patent Claims
`
`Claim 23
`At least one non-transitory
`computer readable medium
`encoded with instructions which,
`when loaded on a computer,
`establish processes for finding data
`related to the contents of a
`document using a first computer
`program running on a computer, the
`processes comprising:
`
`3 4
`
`

`

`Case 1:13-cv-00919-LPS Document 307-7 Filed 03/10/21 Page 6 of 28 PageID #: 26829
`
`Exhibit C-7
`
`'843 Patent Claims
`
`Disclosure
`Apple Internet Address Detectors User's Manual
`
`Apple Internet Addrc» Detectors utilizes a new Apple technology called
`Data Detcclorsi Data Detectors enables your computer to recogni/e and then
`act on certain ty pes of information, or data in your documents. Apple Data
`Detectors can recognize several different types of data, and soon software
`developers will extend the capabilities of Apple Data Detectors even further.
`
`Apple Internet Address Detectors for Mac OS 8 can recognize and act on
`data that's in the form of Internet addresses, which includes the following:
`a e-mail addresses
`• Web sites
`• newsgroup names
`• filenames on FTP (file transfer protocol) sites
`• names of remote computers
`
`For example, if y ou have a word-processing document that contains sev eral
`e-mail addresses. Apple Data Detectors can quickly scan the document
`identify all the addresses, and then open a new e-mail message addressed to
`the one you select. Or. let's say that someone sends you a World Wide Web
`address in an e-mail message. Vou can use Apple Data Detectors to find the
`address within the message, then open the Web page in your favorite Web
`browser program.
`
`For each type of information that Apple Data Detectors identifies, you can
`select an action to perform with it. The actions available with Apple Internet
`Address Detectors include
`a addressing a new e-mail message to the selected address
`a opening a Web browser program and connecting to the selected Web site
`a bookmarking the selected Web site in a Web browser program
`a saving a Web document as a file on your hard disk
`a downloading the selected file from an FTP site
`a connecting to the selected remote computer
`a opening a newsgroup with your news reader program
`
`The User Manual states at p. 4:
`
`35
`
`

`

`Case 1:13-cv-00919-LPS Document 307-7 Filed 03/10/21 Page 7 of 28 PageID #: 26830
`
`'843 Patent Claims
`
`Exhibit C-7
`
`Disclosure
`Getting started with Apple Data Detectors
`Apple Data Dilectors works «ith any Mac OS program in which you can
`select or highlight text. Apple Data Detectors quickly scans the selected te.vt
`for information in specific formats. It uses detectors that are programmed to
`recognize specific types of information. For example, this version of Apple
`Data Detectors includes several detectors that can recognize Internet
`addresses and uniform resource locators (URLs).
`
`Once a detector has identified a piece of information it recognizes. Apple
`Data Detectors creates a menu of actions for you to choose from. .Actions are
`things you can do w ith the detected information, such as sending it to another
`program or saving it for later use. The actions that are available depend on
`the ty pe of information detected.
`
`This table summarizes the actions supplied with Apple Internet
`Address Detectors;
`
`Type of data
`
`Example
`
`Actions
`
`t-mil 3dcr«s
`
`moof@9ppl<.com
`
`stud
`
`iiittii
`
`Web iddress
`
`knpitavw.ipplt.conyfilt.litril mw W<b site, boeknift Hi
`orsm as dectmttt
`
`ntnsgrctp
`
`Mirp.sys.mJe
`
`rod nms group
`
`(i« on in FTP sitt
`
`ftp-'.'jpplt.cor.lik si
`
`davmload the fi«
`
`host addttss
`
`rts<>rdi.ipp<«.oim
`
`otMeet to
`
`renole eorrpusr
`
`The User Manual states at pp. 5-6:
`
`36
`
`

`

`Case 1:13-cv-00919-LPS Document 307-7 Filed 03/10/21 Page 8 of 28 PageID #: 26831
`
`'843 Patent Claims
`
`Exhibit C-7
`
`Disclosure
`Using Apple Data Detectors
`
`To use Apple Data Deteclors. follow these steps:
`
`1
`
`Select some text in any application that allows you to highlight text.
`
`Make sure the selected text contains at least one type of data that Apple Data
`Detectors recognizes. (In this example, the selected text contains one
`complete Internet address.)
`
`•
`
`Note Pail
`
`E B
`rs.
`For cddiUonol informalion, sea
`Apple's Vteb sil9 ol wvyw.oppie corn
`
`2
`
`Hold down the Control key. then press and hold down the mouse button.
`
`A "contextual menu" appears. It lists all the recognized data found in
`the selection.
`
`Note Pail
`
`•
`QB
`MMffllW- Help
`
`www^pplexom •
`
`Tip: If the contextual menu is empty, or the message "no structures
`found in selection" appears, the text you selected did not contain am
`recognizable data.
`
`After the contextual menu appears, you can release the Control key. Be sure
`to keep holding dow n the mouse button or the menu «ill disappear.
`
`3 Choose a recognized data item from the contextual menu, then choose an action from
`the submenu that appears.
`
`•
`
`Note Pad z
`
`For oddilionol infomnolion, se©
`Apple a WeD site at wrvw eppleconrj
`
`ETBI m Help
`
`wfc-w.<i|ip le.ro m •
`
`Connect with Cyberdog
`Connect with Internet Confuj
`Connect wtth NCSA Telnet
`View in America Online
`View in CVberdog
`View In Internet explorer
`View in Netscape Noviqotor
`Vii'W with Intrmi't (nnhij
`
`IAD could operate on text entered by a user in a Simple Text file, a
`Claris Emailer email, or text entered using any other application.
`
`See also Nardi at pp. 96-98 (including figs. 1,2): "As Apple Computer
`researchers, we started from a simple but focused approach to agents:
`That they should have the ability to infer appropriate high-level goals
`from user actions and requests and take action to achieve these goals.
`Further, based on a study of reference librarians as exemplary human
`agents [9], we wanted to build a system in which the user would not have
`to state goals explicitly and in detail. We learned from librarians that a
`
`37
`
`

`

`Case 1:13-cv-00919-LPS Document 307-7 Filed 03/10/21 Page 9 of 28 PageID #: 26832
`
`'843 Patent Claims
`
`Exhibit C-7
`
`Disclosure
`large part of their value to clients is in working with imprecise requests.
`Beyond this concern, our general design strategy was to keep the most
`basic user question in front of us at all times: Will this software do
`something useful for users in an intelligent way that makes them more
`productive? The system we describe here—Apple Data
`Detectors—meets our criteria of being unobtrusive, being able to infer
`user needs, and doing useful work. Apple Data Detectors shipped as a
`product in 1997.
`
`Earlier work on intelligent agents was multifaceted, to the point where it
`is difficult to find a consensus among researchers on exactly what
`constitutes an 'agent' or even 'intelligence.' However, in nearly all
`cases, systems described as 'agent-based' rely on some explicitly
`represented knowledge about relevant aspects of the world—the objects
`or concepts being addressed by the software, the tasks relevant to the
`user, and the user's own knowledge about the world. Researchers have
`used machine learning techniques to track user actions and construct
`models of user preferences [7], create explicit models of user knowledge
`and skill levels in an attempt to anticipate user actions, misconceptions,
`and information needs [2], and implement planning systems to leap from
`a user's stated intention to the specific actions required to achieve that
`intention |3]. The locality of agents also varies across different
`agent-based systems; some act only within one's own machine, find
`others autonomously crawl the Web, searching for interesting content
`[4]. We tried to find a middle ground by using explicit representations
`of user-relevant information as a means of identifying actions users
`might wish to take but to leave the choice of these actions to users."
`
`See also Nardi at fig. 4: "This script uses two applications: First, a
`'personal information manager' (Now Contact 3.5) is opened and used as
`a database. Then the script opens an empty word processor document
`(via Corel WordPerfect) and writes the date, name, address, and
`salutation into it, leaving the user ready to write the letter."
`
`See also Nardi at 103-04: "Apple Data Detectors is a first step toward
`extracting semantics from everyday documents without asking users to
`create documents in new ways. Such an intelligent agent redefines
`'document' from a stream of characters to a data structure containing
`specific, known kinds of structures that can play specific, known roles in
`user interactions. Such an approach can provide a foundation for more
`powerful analyses beyond our current recognition and parsing
`technology. Future work could explore the use of more sophisticated
`kinds of recognition and parsing, including those that rely on finite state
`technology and linguistically informed context analysis [5], as well as
`integration with statistical techniques of data analysis, such as
`relevance-based techniques.
`
`3 8
`
`

`

`Case 1:13-cv-00919-LPS Document 307-7 Filed 03/10/21 Page 10 of 28 PageID #: 26833
`
`'843 Patent Claims
`
`Disclosure
`
`Exhibit C-7
`
`displaying the document
`electronically using the first
`computer program;
`
`One important future step for research will be to build knowledge into
`the system about the structures being recognizing and how these
`structures are related to user goals and tasks. Doing so will provide the
`basis for more flexible and powerful task support. For instance, if we
`can attribute some reasonable set of email address semantics to the
`textual presentation of an email address in a document, the system can
`use the address as a pointer to the person with that address. We can
`then carry out system actions intended for people (such as 'Place a phone
`call to this person') on an email address and let the system figure out the
`person implied by the address.
`(This can already be done through
`Apple Data Detectors but requires writing a script, rather than relying on
`inferencing as suggested here.) Such interaction might require a
`different user interface from the one used today. One can certainly
`imagine many different kinds of user interfaces to the basic
`structure-detection technology underlying the current system."
`IAD could operate on text entered by a user in a Simple Text file, a
`Claris Emailer email, or text entered using any other application.
`
`See also Nardi at fig. 1.
`
`See also Nardi at fig. 4: "This script uses two applications: First, a
`'personal information manager' (Now Contact 3.5) is opened and used as
`a database. Then the script opens an empty word processor document
`(via Corel WordPerfect) and writes the date, name, address, and
`salutation into it, leaving the user ready to write the letter."
`
`See also Nardi at 98: "Our first step was to find a user problem that
`needed solving in which intelligent agents would add value.
`In an
`investigation of how people file information on their computer desktops
`[1], we discovered that a common user complaint is that they cannot
`easily take action on the structured information found in everyday
`documents (structured information being data-recognizable by a
`grammar). Ordinary documents are full of such structured information:
`phone numbers, fax numbers, street addresses, email addresses, email
`signatures, abstracts, tables of contents, lists of references, tables,
`figures, captions, meeting announcements, Web addresses, and more.
`In addition, there are countless domain-specific structures .... These
`structures are not only relevant to users, but because of their structure,
`are also recognizable by parsing technologies. Once identified, the
`structure's type can be used to identify appropriate actions that might be
`carried out, like placing a meeting on a calendar, adding an address to an
`address book, dialing a phone number, opening a URL, finding the
`current price of a stock, filing an ISBN number, and compiling a list of
`abstracts.
`
`3 9
`
`

`

`Case 1:13-cv-00919-LPS Document 307-7 Filed 03/10/21 Page 11 of 28 PageID #: 26834
`
`'843 Patent Claims
`
`Exhibit C-7
`
`Disclosure
`Apple Data Detectors supports a wide range of uses. Think of all the
`structured information in the documents you work with; in addition to
`those mentioned already, add bibliography items, forms (such as travel
`expensive reports and non-disclosure agreements), executive summaries,
`and most important, such domain-specific kinds of data as legal
`boilerplate, customer orders, and library search requests. Specific
`detectors can be created for each of these types of information."
`
`See also Nardi at 98: "User interface. To use Apple Data Detectors,
`users select a region of a document with some information of interest.
`Pressing a modifier key and the mouse button instructs the system to
`analyze the data within the selected region and to find all structures for
`which it has grammars.
`It then offers appropriate actions for each
`structure (see Figure 1)."
`
`See also Nardi at 101: "Apple Data Detectors therefore has the ability
`to infer appropriate high-level goals from user actions and requests and
`take appropriate action to achieve these gaols. When users invoke it on
`a region of text in a document, they are saying, in effect, 'Find the
`important stuff in here and help me do reasonable things to it.' Users
`can be imprecise, throwing the system a broad hint that there is
`something of interest, then let the system use its knowledge to do the
`right thing. Users work on their tasks in terms of high-level goals, such
`as 'put this address in my address book'—not by opening folders,
`clicking on icons, cutting, and pasting. Direct manipulation is a
`wasteful, frustrating way for users to interact with machines capable of
`showing more intelligence."
`
`See also Nardi at 101: "Apple Data Detectors assumes a world of
`heterogenous data (in the user's machine) that comes from different
`applications in different file formats. For example, it makes sense to
`put an address in an address book, whether the address is from a message
`sent in any of several mail programs, appears in a downloaded document,
`or is in another address book maintained by the user. Apple Data
`Detectors is a pervasive technology, giving users access to actions
`appropriate for data in an entire set of documents."
`
`See also Nardi at 102: "We also see evidence that end users with
`varying degrees of programming skill are extending actions much as we
`had expected. One user—a skilled programmer—used the basic
`detectors and actions that ship with the product as the basis for a new
`detector/action pair for a personally relevant task. He wanted to look
`up software bug reports in a database based on the ID numbers of the
`reports commonly found in other bug reports, email messages, and other
`program management documents. He distributed this detector/action
`throughout his work group, and a colleague—a marketing manager with
`
`40
`
`

`

`Case 1:13-cv-00919-LPS Document 307-7 Filed 03/10/21 Page 12 of 28 PageID #: 26835
`
`'843 Patent Claims
`
`while the document is being
`displayed, analyzing, in a computer
`process, first information from the
`document to determine if the first
`information is at least one of a
`plurality of types of information
`that can be searched for in order to
`find second information related to
`the first information;
`
`Exhibit C-7
`
`Disclosure
`much less programming experience than the original programmer—was
`able to adapt the action so the detector could run on his laptop computer
`(where his email and other documents reside) and display the bug reports
`on his desktop machine (where is program management tools reside).
`This extension required changes to only a few lines of code in the action,
`something well within his technical ability."
`
`See also Nardi at 103-04: "Apple Data Detectors is a first step toward
`extracting semantics from everyday documents without asking users to
`create documents in new ways. Such an intelligent agent redefines
`'document' from a stream of characters to a data structure containing
`specific, known kinds of structures that can play specific, known roles in
`user interactions. Such an approach can provide a foundation for more
`powerful analyses beyond our current recognition and parsing
`technology. Future work could explore the use of more sophisticated
`kinds of recognition and parsing, including those that rely on finite state
`technology and linguistically informed context analysis [5], as well as
`integration with statistical techniques of data analysis, such as
`relevance-based techniques.
`
`One important future step for research will be to build knowledge into
`the system about the structures being recognizing and how these
`structures are related to user goals and tasks. Doing so will provide the
`basis for more flexible and powerful task support. For instance, if we
`can attribute some reasonable set of email address semantics to the
`textual presentation of an email address in a document, the system can
`use the address as a pointer to the person with that address. We can
`then carry out system actions intended for people (such as 'Place a phone
`call to this person') on an email address and let the system figure out the
`person implied by the address.
`(This can already be done through
`Apple Data Detectors but requires writing a script, rather than relying on
`inferencing as suggested here.) Such interaction might require a
`different user interface from the one used today. One can certainly
`imagine many different kinds of user interfaces to the basic
`structure-detection technology underlying the current system."
`The User Manual states at pp. 5-6:
`
`41
`
`

`

`Case 1:13-cv-00919-LPS Document 307-7 Filed 03/10/21 Page 13 of 28 PageID #: 26836
`
`'843 Patent Claims
`
`Exhibit C-7
`
`Disclosure
`Using Apple Data Detectors
`
`To use Apple Data Deteclors. follow these steps:
`
`1
`
`Select some text in any application that allows you to highlight text.
`
`Make sure the selected text contains at least one type of data that Apple Data
`Detectors recognizes. (In this example, the selected text contains one
`complete Internet address.)
`
`•
`
`Note Pail
`
`E B
`rs.
`For cddiUonol informalion, sea
`Apple's Vteb sil9 ol wvyw.oppie corn
`
`2
`
`Hold down the Control key. then press and hold down the mouse button.
`
`A "contextual menu" appears. It lists all the recognized data found in
`the selection.
`
`Note Pail
`
`•
`QB
`MMffllW- Help
`
`www^pplexom •
`
`Tip: If the contextual menu is empty, or the message "no structures
`found in selection" appears, the text you selected did not contain am
`recognizable data.
`
`After the contextual menu appears, you can release the Control key. Be sure
`to keep holding dow n the mouse button or the menu «ill disappear.
`
`3 Choose a recognized data item from the contextual menu, then choose an action from
`the submenu that appears.
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`View in CVberdog
`View In Internet explorer
`View in Netscape Noviqotor
`Vii'W with Intrmi't (nnhij
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`When a user selects text and right-clicks in Simple Text, IAD can detect
`URLs and provide options:
`
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`Case 1:13-cv-00919-LPS Document 307-7 Filed 03/10/21 Page 14 of 28 PageID #: 26837
`
`Exhibit C-7
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`'843 Patent Claims
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`View in America Online
`View in Cyberdog
`View in Internet Explorer
`View in Netscape Navigator
`Viewwith InternetConfig
`
`This feature was available in a Claris Emailer email as well, and starting
`with Claris Emailer version 2.0v3, a user needed to only right-click (and
`not select text) to obtain a list of actions for a URL.
`
`When a user selects text and right-clicks in Simple Text, IAD can detect
`email addresses and provide options:
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`Send mail with Internet i
`Send mail with Internet 1
`Sfiui mail with NeUcape
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`This feature was available in a Claris Emailer email as well, and starting
`with Claris Emailer version 2.0v3, a user needed to only right-click (and
`not select text) to obtain a list of actions for an email address.
`
`When a user selects text and right-clicks in Simple Text, IAD can detect
`occurrences of a city name followed by a state name or US Postal
`abbreviation and occurrences of the name of a state, territory, or
`
`43
`
`

`

`Case 1:13-cv-00919-LPS Document 307-7 Filed 03/10/21 Page 15 of 28 PageID #: 26838
`
`'843 Patent Claims
`
`Exhibit C-7
`
`Disclosure
`protectorate of the United States and provide options. The user could
`then obtain a map of the selected US city, for which the system would
`search the Yahoo map website for a map of the city, or the user could
`obtain a zip code for the selected US city, for which the system would
`search the US Postal Service website for a list of zip codes for the city.
`See US Geographic Detectors 1.0 Read Me file. For example:
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`This feature was available in a Claris Emailer email as well, and starting
`with Claris Emailer version 2.0v3, a user needed to only right-click (and
`not select text) to obtain a list of actions for geographic information.
`
`See also Nardi at 98: "Our first step was to find a user problem that
`needed solving in which intelligent agents would add value.
`In an
`investigation of how people file information on their computer desktops
`[1], we discovered that a common user complaint is that they cannot
`easily take action on the structured information found in everyday
`documents (structured information being data-recognizable by a
`grammar). Ordinary documents are full of such structured information:
`phone numbers, fax numbers, street addresses, email addresses, email
`signatures, abstracts, tables of contents, lists of references, tables,
`figures, captions, meeting announcements, Web addresses, and more.
`In addition, there are countless domain-specific structures .... These
`structures are not only relevant to users, but because of their structure,
`are also recognizable by parsing technologies. Once identified, the
`structure's type can be used to identify appropriate actions that might be
`carried out, like placing a meeting on a calendar, adding an address to an
`address book, dialing a phone number, opening a URL, finding the
`current price of a stock, filing an ISBN number, and compiling a list of
`abstracts.
`
`Apple Data Detectors supports a wide range of uses. Think of all the
`structured information in the documents you work with; in addition to
`those mentioned already, add bibliography items, forms (such as travel
`expensive reports and non-disclosure agreements), executive summaries,
`and most important, such domain-specific kinds of data as legal
`boilerplate, customer orders, and library search requests. Specific
`det