PROVIDING SELECBLE QUICK ACTIONS ON HANDWRITTEN DATA IN A HANDWRITTEN DOCUMENT

Abstract

A method for providing selectable fast actions on handwritten data in a handwritten document is disclosed. The method involves retrieving the handwritten data corresponding to handwriting made by a user in the handwritten document and recognizing text associated with the received handwritten data by applying a handwriting recognition technique. The method also involves identifying keywords in the recognized text and classifying each identified keyword into an entity type by applying named entity recognition, named entity linking, and / or a knowledge graph.In some embodiments, the method involves identifying actionable elements associated with the classified entity type corresponding to the respective keyword and generating user-selectable quick actions for each keyword based on the identified actionable elements, via the knowledge graph. The method further involves replaying the generated quick actions associated with the respective keyword onto the handwritten document based on a profile assigned to the user.

Description

BACKGROUNDTechnical field

[0001] The present disclosure relates to the field of handwritten data, and more particularly to a system and method for providing selectable quick actions on handwritten data in a handwritten document. Description of the state of the art

[0002] With the rapidly growing adoption of digital writing devices, such as tablets, electronic boards, pen tablets, and the like, more and more notes are being taken in the form of handwritten data in handwritten documents delivered via digital writing devices. Such handwritten documents offer several advantages over typed documents, including the personal touch of the user's handwriting; their authenticity, which is especially important in legal or historical documents; flexibility, which allows for customization and personalization based on personal preferences for font, color, or style; and time savings by enabling quick note-taking.

[0003] However, electronic devices such as digital writing pads, computers, mobile phones, tablets, personal digital assistants (PDAs), or the like, treat handwritten documents merely as images of a user's writing, which the user can later access and view as needed. Thus, the advantage of electronic handwritten documents over traditional pen-and-paper note-taking is limited to their portability. Furthermore, to interact with one or more terms (e.g., words) in the handwritten data, the user must perform a series of actions, which is time-consuming and may be inconvenient for the user.For example, if the user wants to know more about the name of a company contained in a handwritten document, the user must minimize the handwritten document, then open a search engine, then enter the company name based on their interpretation, and then browse multiple pages of search results to obtain the information they are looking for. As another non-limiting example, if a date of an upcoming event that the user plans to attend is contained in the handwritten document, the user must minimize the handwritten document, go to the calendar, search for the date, and enter the name of the event to mark the event on the calendar.

[0004] While traditional electronic handwriting technologies may be time-efficient when writing data by hand compared to typing on paper, they are time-consuming when it comes to gathering information or performing actions related to a term (or word) written on the handwritten document. Furthermore, traditional electronic handwriting technologies do not offer the benefits associated with digitizing handwriting, and their advantages are currently limited to their portability compared to the pen-and-paper method and their personal touch compared to typed documents.

[0005] Therefore, there is a need for a system and method to make handwritten documents more interactive and thus overcome the above-mentioned disadvantages of the known technologies. SHORT SUMMARY

[0006] The following embodiments relate to a system and method for providing selectable quick actions on handwritten data in a handwritten document.

[0007] One embodiment of the present disclosure discloses a system for providing selectable quick actions on handwritten data in a handwritten document. The system includes a receiver module configured to obtain the handwritten data corresponding to writing made by a user in the handwritten document on a screen of an electronic device, such as a touch-enabled device, a stylus-enabled device, or a pen-enabled device. The electronic device may be a mobile phone, a tablet, a personal computer, a digital signage, a smartboard, or a television.In some embodiments of the present disclosure, the handwritten data is received in the form of one or more tuples comprising x-coordinate data, y-coordinate data, pressure, writing speed, and orientation, or any combination thereof.

[0008] The system also includes a recognition module for recognizing text associated with the received handwritten data by applying a handwriting recognition technique. The handwriting recognition technique analyzes each received tuple to identify the closest (e.g., most similar) recognized term (e.g., a word) that the respective received tuple potentially represents. In some embodiments of the present disclosure, the recognition module identifies one or more keywords in the recognized text by removing unnecessary data from the recognized text. Such unnecessary data may be periods, punctuation marks, spaces, or a combination thereof.

[0009] The system also includes an analysis module to classify each identified keyword into one or more entity types by applying named entity recognition, named entity linking, a knowledge graph, or a combination thereof. The entity types can be one or more of "person," "company," "legal person," "location," "event," "abstract concept," "service," "product," or a combination thereof. Entity types are labeled with German names here, but can of course also be labeled with English names. The analysis module also determines a set of actionable items associated with a classified entity type, where a set can, for example, comprise one or more elements.The set of actionable elements may include: displaying relationships, displaying social media links, displaying a description, displaying alternative names, displaying mail (or an email address), displaying a planner, displaying weather information, displaying options for booking accommodation, displaying options for adding an event to a calendar, displaying summarized relevant information, displaying options for a digital wallet, displaying a "more..." link, displaying options for a direct call, displaying RSVP options, displaying options for enabling / disabling an event, and / or displaying options for purchasing a product, or a combination thereof.

[0010] In one embodiment of the present disclosure, the analytics module generates, via the knowledge graph, for each keyword, one or more quick actions selectable by the user based on the determined set of actionable items. The one or more quick actions may include providing, for each keyword, personal information, business information, one-touch social media links, a description, alternate names, mail shortcuts, planners, weather information, options for booking lodging, an option to add an event to a calendar, summarized relevant information along with one or more links, shortcuts to a digital wallet, "More...“links, displaying call options, displaying options for an RSVP message, displaying shortcuts to activate / deactivate a service, displaying options to purchase a product, or a combination thereof.

[0011] Additionally, the system includes a rendering module for rendering the generated quick actions associated with the respective keyword or identified entity type on the handwritten document based on a profile associated with the user. In some embodiments of the present disclosure, the rendering module may render the one or more quick actions in the form of a list of all quick actions for each keyword or for the identified entity type on the handwritten document. Highlights may be added to the one or more keywords to render the corresponding quick actions, or the one or more quick actions may be presented in a dynamic window overlaid on, adjacent to, above, or below the one or more keywords in the digital document.In one embodiment of the present disclosure, the dynamic window is generated for a particular keyword when a predicted user action score for a particular quick action is greater than a threshold. Additionally, the dynamic window may appear based on an action that includes clicking on the keyword, hovering over the keyword for more than a threshold amount of time, or a combination thereof.

[0012] In one embodiment of the present disclosure, the rendering module uses predictive learning based on the profile associated with the user to identify the one or more keywords or identified entity types for which the one or more quick actions should be rendered. The profile associated with the user may also include historical data of the user indicating keywords of interest to the user, keywords the user should know, keywords the user knows, keywords appropriate for the user, keywords inappropriate for the user, or a combination thereof.

[0013] In another embodiment of the present disclosure, the rendering module uses predictive learning based on the profile associated with the user to identify one or more specific quick actions of interest to the user. The profile associated with the user may include user interests, the user's occupation, the user's schedule, the user's event list, or a combination thereof.

[0014] One embodiment of the present disclosure discloses a method for providing selectable quick actions on handwritten data in a handwritten document. The method includes the steps of obtaining the handwritten data corresponding to writing made by a user in the handwritten document on a screen of an electronic device and recognizing text associated with the received handwritten data by applying a handwriting recognition technique. In some embodiments of the present disclosure, the method includes the steps of identifying one or more keywords in the recognized text and classifying each identified keyword into an entity type of one or more entity types.The classification of keywords into entity types is performed by applying named entity recognition, named entity linking, a knowledge graph, or a combination thereof.

[0015] In some embodiments of the present disclosure, the method includes the steps of determining a set of actionable items associated with the classified entity type, and generating, using the knowledge graph, one or more quick actions for one or more keywords or the classified entity type based on the determined set of actionable items. The one or more quick actions are selectable by the user. The method further includes the steps of rendering the generated one or more quick actions associated with one or more keywords or the classified entity types on the handwritten document based on a profile associated with the user.

[0016] In one embodiment of the present disclosure, the method includes the steps of displaying the one or more quick actions in the form of a list of all quick actions for one or more keywords or the classified entity type on the handwritten document. The method may further include adding highlighting to the one or more keywords to display the corresponding quick actions and / or displaying the one or more quick actions in a dynamic window overlaid on, adjacent to, above, or below the one or more keywords in the digital document. In one embodiment, the dynamic window is generated for a particular keyword when a predicted user action score for a particular quick action is greater than a threshold.Such a dynamic window may appear based on an action such as clicking on the keyword, hovering over the keyword for more than a threshold amount of time, or a combination thereof.

[0017] In one embodiment of the present disclosure, the method includes the steps of applying predictive learning based on the profile associated with the user to identify the one or more keywords for which the one or more quick actions should be rendered to the user. The profile associated with the user may also include historical data of the user indicating keywords of interest to the user, keywords the user should know, keywords the user knows, keywords appropriate for the user, keywords inappropriate for the user, or a combination thereof.

[0018] In one embodiment of the present disclosure, the method includes the steps of applying predictive learning based on the profile associated with the user to identify one or more particular quick actions of interest to the user, wherein a profile associated with the user includes user interests, the user's occupation, a user's schedule, a user's event list, or a combination thereof.

[0019] Features and advantages of the present subject matter should become more apparent in light of the following detailed description of selected embodiments illustrated in the accompanying figures. As should be appreciated, the disclosed subject matter is susceptible to modification in various respects without departing from the scope of the present disclosure. Accordingly, the drawings and descriptions are to be considered as illustrative only. SHORT DESCRIPTION OF THE CHARACTERS

[0020] In the figures, similar components and / or features may be assigned the same reference symbol. Furthermore, different components of the same type may be distinguished by following the reference symbol with a second symbol (letter or the like) that distinguishes the similar components from each other. If only the first reference symbol is used in the description, the description also applies to each of the corresponding components with the same first reference symbol, regardless of the second reference symbol. Fig. 1 illustrates a block diagram of a system for providing selectable quick actions on handwritten data in a handwritten document according to various embodiments of the present disclosure. Fig. 2A illustrates exemplary handwritten data received by an electronic device, according to an embodiment of the present disclosure. Fig. 2B illustrates exemplary recognized text recognized by a recognition module, according to an embodiment of the present disclosure. Fig. 2C illustrates exemplary analyzed data analyzed by an analysis module, according to an embodiment of the present disclosure. Fig. 2D illustrates exemplary quick actions rendered on the screen of the electronic device, according to an embodiment of the present disclosure. Fig. 2E illustrates example quick actions rendered on the screen of the electronic device, according to an embodiment of the present disclosure. Fig. 2F illustrates example quick actions rendered on the screen of the electronic device, according to an embodiment of the present disclosure. Fig. 2G illustrates example quick actions rendered on the screen of the electronic device, according to an embodiment of the present disclosure. Fig. 3 illustrates an example of potential term (word) recognition according to an embodiment of the present disclosure. Fig. 4 illustrates an example of a multi-level relationship between two terms according to an embodiment of the present disclosure. Fig. 5 illustrates an exemplary implementation of the system for reproducing selectable quick actions using a knowledge graph according to an embodiment of the present disclosure. Fig. 6A to Fig. 6H show example results of the system for reproducing selectable quick actions according to various embodiments of the present disclosure. Fig. 7 illustrates a flow diagram of an exemplary method for providing selectable quick actions on handwritten data in a handwritten document according to an embodiment of the present disclosure. Fig. 8 illustrates an example computer system in or with which an embodiment of the present disclosure may be used.

[0021] Other features of embodiments of the present disclosure will become apparent from the accompanying drawings and the following detailed description. EMBODIMENTS

[0022] Embodiments of the present disclosure include various steps, which are described below. The steps may be performed by hardware components or may be provided in the form of machine-executable instructions that can be used to cause a general-purpose or special-purpose processor programmed with the instructions to perform the steps. Alternatively, steps may be performed by a combination of hardware, software, firmware, and / or human operators.

[0023] Embodiments of the present disclosure may be provided as a computer program product, which also includes machine-readable storage media storing instructions that can be used to program a computer (or other electronic device) to perform a process. Machine-readable media may include, but are not limited to, solid-state (FDD) drives, magnetic tapes, floppy disks, optical disks, compact disc read-only memories (CD-ROMs) and magneto-optical disks, semiconductor memories such as ROMs, PROMs, random-access memories (RAMs), programmable read-only memories (PROMs), erasable PROMs (EPROMs), electrically erasable PROMs (EEPROMs), flash memory, magnetic or optical cards, or other types of media / machine-readable media suitable for storing electronic instructions (e.g., computer programming code such as software or firmware).

[0024] Various methods described herein may be implemented by combining one or more machine-readable storage media containing the code according to the present disclosure with suitable standard computer hardware to execute the code contained therein. An apparatus for implementing various embodiments of the present disclosure may include one or more computers (or one or more processors within the single computer) and storage systems containing or having network access to one or more computer programs encoded according to various methods described herein, and the method steps of the disclosure could also be provided by modules, routines, subroutines, or subsections of a computer program product. terminology

[0025] The following are brief definitions of terms used in this application.

[0026] The terms "connected" or "coupled" and related terms are used in an operative sense and are not necessarily limited to a direct connection or coupling. For example, two devices may be coupled directly or through one or more intermediate media or devices. As another example, devices may be coupled such that information can be passed between them while not physically connected to each other. Based on the disclosure provided herein, one of ordinary skill in the art will recognize a variety of ways in which a connection or coupling, as defined above, exists.

[0027] If this description indicates that a component or feature "may" or "could" be provided or included or have a particular characteristic, then that particular component or feature may not be provided or have that characteristic.

[0028] In this specification and in the following claims, the meaning of "a," "an," and "the" in conjunction with the singular also includes the plural, unless the context otherwise indicates. In this specification, the meaning of "in" includes both "in" and "on," unless the context otherwise indicates.

[0029] The terms "in one embodiment," "according to an embodiment," and the like generally mean that the particular feature, structure, or characteristic following the term is included in at least one embodiment of the present disclosure, and may be included in more than one embodiment of the present disclosure. Such terms expressly do not necessarily refer to the same embodiment.

[0030] Example embodiments will now be described in more detail with reference to the accompanying drawings, in which example embodiments are shown. This disclosure may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. These embodiments are intended to thoroughly and completely disclose the invention and to fully convey the scope of the disclosure to those of ordinary skill in the art. Furthermore, all statements made herein, the embodiments of the disclosure, and specific examples thereof are intended to include both structural and functional equivalents thereof. Furthermore, such equivalents are intended to include both currently known equivalents and equivalents developed in the future (i.e., any evolved elements which perform the same function, regardless of structure).

[0031] Thus, for example, one of ordinary skill in the art will recognize that the diagrams, schematics, and the like represent conceptual views or processes illustrating systems and methods embodying this disclosure. The functions of the various elements shown in the figures may be provided through the use of dedicated hardware, as well as hardware capable of executing associated software. Likewise, any switches shown in the figures are to be understood only conceptually. Their functionality may be performed through the operation of program logic, through dedicated logic, through the interaction of program control and dedicated logic, or even manually, with the exact technique being selectable by the entity implementing the present disclosure.Those of ordinary skill in the art will further recognize that the exemplary hardware, software, processes, methods, and / or operating systems described herein are for illustrative purposes only and are not intended to be limited to any particular one.

[0032] Embodiments of the present disclosure relate to a system and method for providing selectable quick actions on handwritten data in a handwritten document. The system obtains (e.g., receives) the handwritten data corresponding to writing made by a user in the handwritten document on a screen of an electronic device. Further, the system recognizes text associated with the received handwritten data by applying a handwriting recognition technique and identifies one or more keywords in the recognized text. The system classifies each identified keyword into an entity type of one or more entity types by applying Named Entity Recognition (NER), Named Entity Linking (NEL), and Proper noun linking) and / or a knowledge graph. The system further determines a set of actionable items associated with the classified entity type corresponding to the respective keyword and, via the knowledge graph, generates one or more user-selectable quick actions for one or more keywords or their identified entity types based on the determined set of actionable items. The system further renders the generated quick actions associated with the one or more keywords or their identified entity types on the handwritten document based on a profile associated with the user.

[0033] Fig. 1 illustrates a block diagram of a system 100 for rendering selectable quick actions (hereinafter also referred to as "system 100"), that is, a system for providing selectable quick actions to handwritten data in a handwritten document, according to various embodiments of the present disclosure. For the purposes of the disclosure, the handwritten document corresponds to a digital document including handwritten data. Such handwritten data may correspond to one or more words on the handwritten document, a sentence on the handwritten document, or the entire handwritten document as a whole. Further, the handwritten data may include static handwritten data and dynamic handwritten data. The static handwritten data may correspond to geometric data associated with the user's handwritten data, such as an image.The dynamic handwritten data may correspond to a chronological sampling of the movement of handwritten data, such as x-coordinate data, y-coordinate data, pressure, writing speed, and orientation.

[0034] In one embodiment of the present disclosure, providing selectable quick actions may include providing one or more shortcuts to the user that may present an option to perform a quick action, or to obtain more information, or both, with respect to the handwritten data on the handwritten document.The selectable quick actions may include, but are not limited to: displaying personal information, displaying business information, displaying one-touch social media links, displaying a description, displaying alternate names, displaying mail abbreviations, displaying planners, displaying weather information, displaying options for booking accommodations, displaying an option to add an event to a calendar, displaying summarized relevant information along with one or more links, displaying a "More..." link, displaying calling options, displaying options to send an RSVP message, displaying shortcuts to enable / disable a service, displaying a link to purchase a product, or a combination thereof.

[0035] In one embodiment of the present disclosure, the system 100 for managing handwritten documents as described in Fig. 1, may be implemented on a server and may include a receiver module 102, a recognition module 104, an analysis module 106, a rendering module 108, and a knowledge graph 110. The receiver module 102, the recognition module 104, the analysis module 106, the rendering module 108, and the knowledge graph 110 may be communicatively coupled to a storage and processing unit of the system 100. The server may be a centralized server or a decentralized server. In one embodiment, various modules of the system may also utilize cloud resources, such as cloud storage and cloud processing. In one embodiment, the system 100 may be implemented on an end-user device.

[0036] The processing unit of system 100 may control the operations of receiver module 102, detection module 104, analysis module 106, rendering module 108, and knowledge graph 110. In one embodiment of the present disclosure, the processor and memory may form part of a chipset installed in system 100. In another embodiment of the present disclosure, the memory may be implemented as static memory or dynamic memory. In one example, the memory may be provided within system 100, such as on-premises storage. In another example, the memory may be provided external to system 100, such as cloud-based storage.Furthermore, the processing unit may be implemented as one or more microprocessors, microcomputers, digital signal processors, central processing units, state machines, logic circuits, and / or any devices that manipulate signals based on operating instructions.

[0037] In one embodiment of the present disclosure, the receiver module 102 may acquire the handwritten data corresponding to strokes made by the user in the handwritten document on a screen of an electronic device. The electronic device may be a touch-enabled device, a stylus-enabled device, or a pen-enabled device, and may allow the user to enter the handwritten data by touch or with the aid of a stylus or pen when preparing the handwritten document. Accordingly, the electronic device may be embodied as, but is not limited to, a mobile phone, a tablet, a personal computer, a digital signage, a smartboard, or a television.The handwritten data can be received in the form of one or more tuples, such as (x, y, p, s, o), where “x” represents x-coordinates, “y” represents y-coordinates, “p” represents pressure, “s” represents writing speed, and “o” represents orientation.

[0038] In one embodiment of the present disclosure, the recognition module 104 may recognize text associated with (e.g., corresponding to) the received handwritten data, such as words, phrases, and sentences. Further, the text may be recognized by applying a handwriting recognition technique (e.g., a universal ink model). To recognize the text, the handwriting recognition technique may analyze each received tuple to identify a closest recognized term that the respective received tuple potentially represents. In one embodiment of the present disclosure, the recognition module 104 may identify one or more keywords in the recognized text. To identify one or more keywords, the recognition module 104 may remove unnecessary data, such as unnecessary words, periods, punctuation marks, and spaces, from the recognized text.The recognition module 104 may also remove connecting words and articles if necessary. For example, if the recognized text is "Company A, based in the USA, is developing a product A," the recognition module 104 identifies "Company A," "USA," and "Product A" as keywords by removing "based in the" and "develops a" from the recognized text.

[0039] In one embodiment of the present disclosure, the analysis module 106 may classify each identified keyword into an entity type from one or more entity types. The one or more entity types may be, but are not limited to, a person, a business, a legal entity, a location, an event, an abstract concept, a service, a product, or a combination thereof. In one embodiment of the present disclosure, the entity type may be classified by applying named entity recognition, named entity linking, the knowledge graph 110, or a combination thereof. In one example, the entity types that do not correspond to sensitive data, such as a person, a business, a legal entity, a location, an event, an abstract concept, a service, or a product, may be classified by named entity linking and the knowledge graph 110.

[0040] In one embodiment of the present disclosure, the analysis module 106 may determine a set of actionable items associated with the classified entity type corresponding to the respective keyword. For the purposes of the disclosure, the actionable items may correspond to abbreviations provided for a keyword, for example, for using the keyword to obtain more information about the keyword, or both.The set of actionable elements may include, but are not limited to, displaying relevant information, displaying social media links, displaying a description, displaying alternative names, displaying email addresses, displaying a planner, displaying weather information, displaying options to book accommodation, displaying an option to add an event to a calendar, displaying summarized relevant information, displaying options for a digital wallet, displaying a "More..." link, displaying options for a direct call, displaying RSVP options, displaying options to enable / disable an event, displaying options to purchase a product, or a combination thereof.

[0041] In one embodiment of the present disclosure, the analysis module 106 may generate, via the knowledge graph 110, one or more quick actions for each keyword based on the determined set of actionable items. For example, if the keyword is associated with a conference on July 22nd, then the actionable item may be "displaying an option to add an event to a calendar," and an option to add the conference to the calendar for July 22nd may be generated. The actionable item may include information that may be necessary to assist the user in performing a quick action. In the present example, the actionable item "adding an event to a calendar" may include the event name and date information required to create a calendar entry.

[0042] In one embodiment of the present disclosure, the rendering module 108 renders the generated quick actions associated with the respective keyword on the handwritten document based on a profile associated with the user. In one embodiment of the present disclosure, the rendering module 108 may use predictive learning based on the profile associated with the user to identify the one or more keywords for which the one or more quick actions should be rendered.In such a scenario, the profile associated with the user may also include historical data about the user, indicating keywords of interest to the user, keywords the user should know, keywords the user knows, keywords appropriate for the user, keywords inappropriate for the user, or a combination thereof.

[0043] In another embodiment of the present disclosure, the rendering module 108 may employ predictive learning based on the profile associated with the user to identify one or more specific quick actions of interest to the user. In such a scenario, the profile associated with the user may include, but is not limited to, user interests, the user's occupation, the user's schedule, the user's event list, or a combination thereof.

[0044] In one embodiment of the present disclosure, the rendering module 108 renders the one or more quick actions in the form of a list of all quick actions for each keyword on the handwritten document, wherein highlighting is added to the one or more keywords to render the corresponding quick actions, and / or wherein the one or more quick actions are presented in a dynamic window that overlays, is positioned next to, above, or below the one or more keywords in the handwritten document. The dynamic window for a particular keyword may be generated, for example, when a predicted user action score for a particular quick action is greater than a threshold.Furthermore, such a dynamic window may appear based on an action such as, but not limited to, clicking on the keyword or hovering (e.g., with a mouse cursor or the like) over the keyword for more than a threshold amount of time.

[0045] Fig. 2A illustrates exemplary written data received by an electronic device, according to an embodiment of the present disclosure. Fig. 2B illustrates, by way of example, recognized (English) text recognized by a recognition module 104, according to an embodiment of the present disclosure. Fig. 2C illustrates exemplary analyzed data analyzed by an analysis module 106, according to one embodiment of the present disclosure. Fig. 2D illustrates exemplary quick actions rendered on the screen of electronic device 202, according to one embodiment of the present disclosure. Fig. 2E illustrates example quick actions rendered on the screen of electronic device 202, according to one embodiment of the present disclosure. Fig. 2F illustrates example quick actions rendered on the screen of electronic device 202, according to one embodiment of the present disclosure. Fig. Figure 2G illustrates exemplary quick actions displayed on the screen of electronic device 202, according to one embodiment of the present disclosure. For brevity, the Fig. 2A to Fig. 2G explained together.

[0046] In an illustrated embodiment of the present disclosure, as shown in Fig. As shown in Figure 2A, the electronic device 202 may provide a user interface 204 to enable the user to create a handwritten document 206, such as a new document. To create the new document, the user may add handwritten text 208, such as "Company A is producing a new type of tablet," to the new document by writing on the screen of the electronic device 202 through touch or using a stylus or pen.

[0047] In an illustrated embodiment of the present disclosure, as shown in Fig. As shown in Figure 2B, the recognition module 104 can recognize the above-mentioned handwritten text 208 as a recognized text 210, namely, "Company A is producing a new type of tablet." Furthermore, the recognition module 104 can identify one or more keywords 212 from the recognized text 210, here, "Company A" and "tablet."

[0048] In one embodiment of the present disclosure, as in Fig. 2C, the analysis module 106 may analyze the keywords "company A" and "tablet" to determine the list of actionable items 214, such as "display name," "display stock price," "display social media," "display description," and "display email address" for the keyword "Company A" of the entity type "Company"; and display "Add to cart," "display user manual," "quick buy," and "reviews" for the keyword "tablet" of the entity type "Product." The one or more actionable items to be associated with the respective entity type may be pre-assigned. In one embodiment, one or more actionable items may be determined based on the closest match of a new entity type to an existing entity type.

[0049] In one embodiment of the present disclosure, the rendering module 108 may render the generated quick actions associated with the respective keyword on the handwritten document 206, as shown in Fig. 2D to Fig. 2G. In one embodiment of the present disclosure, the quick actions may be represented as selectable options, such as "View company details" for "Company A" and "Add to cart" for "Tablet," as indicated by 216A and 216B in Fig. 2D. In another embodiment of the present disclosure, the quick actions may be rendered as selectable options, with the dynamically generated font style matching the user's handwriting style used in the handwritten document 206, as shown in Fig. 2E. For example, actionable elements “View company details” for “company A” and “Add to cart” for “tablet” are shown as shown by 218A and 218B in Fig. 2E, presented in a font style consistent with the user's handwriting style. The font used to present the actionable element can be generated either dynamically based on the user's handwriting style or based on a best-matching, selectable default font. The user can thus be prompted to click on the selectable options to quickly perform one or more actions, such as viewing company details or adding the tablet to the shopping cart for purchase, without having to complete a series of steps.

[0050] In yet another embodiment of the present disclosure, the quick actions may be presented as drop-down menus, such as “Know more about Company” for “company A” and “more on tablet” for “tablet”, as illustrated by 220A and 220B in Fig. 2F. The user can thus be prompted to click on the drop-down menus to quickly perform one or more actions, such as viewing company details, viewing the company's stock price, viewing the tablet's specifications, or adding the tablet to the shopping cart, without having to complete a series of steps.

[0051] In yet another embodiment of the present disclosure, the quick actions may be rendered as dynamic windows 222A and 222B that overlay the keywords “Company A” and “tablet,” respectively, or are arranged next to or below them, for example, as in Fig. 2G. Such dynamic windows 222A and 222B may display one or more documents with detailed information about the keywords. Alternatively or additionally, such dynamic windows 222A and 222B may also include one or more hyperlinks to display more information or perform one or more actions, such as "Add to cart," as described above.

[0052] Fig. 3 illustrates an example 300 of potential term recognition according to an embodiment of the present disclosure. In the illustrated embodiment, recognition module 104 may receive a handwritten document 302 having handwritten text as an object 304. As shown, the handwritten text indicates "hello world." Recognition module 104 may process handwritten document 302 to extract object 304 from handwritten document 302. Further, recognition module 104 may use a suitable ink-to-text model to recognize phrase 306, "hello world."

[0053] Fig. 4 illustrates an example 400 of a multi-level relationship between two terms (two words) according to an embodiment of the present disclosure. In one embodiment of the present disclosure, the analysis module 106 may determine a multi-level relationship between two terms in the knowledge graph 110 to classify the respective identified keyword 212 into the corresponding entity type. Assume that the two terms "Playdium" and "Harry" are associated with a school icon 402 and a personal profile 404, respectively.The school symbol 402 has a corresponding unique identifier (URI, short for Uniform Resource Identifier) ​​406A such as "2y5sch001", a type 408A such as "education#school", a label 410A such as "Playdium School of Witchcraft and Wizadry@en_US" (German: "Playdium Schule für Hexen- und Zauberkunst@en_US"), an alias 412A such as "Playdium@en_US", a description 414A such as "Playdium is a fictional Scottish boarding school of magic@en_US" (German: "Playdium ist ein fiktionales Schottlands Internat der Magie@en_US") and a literal 416A such as "10th century" (German: "zehntes Jahrhundert").Furthermore, the personal profile 404 has a corresponding URI 406B such as “5b5stu008,” a type 408B such as “core#person,” a label 410B such as “Harry@en_US,” an alias 412B such as “HS,” a description 414B such as “Harry is a fictional character@en_US,” and a literal 416B such as “Harry@en_US” and “Simons@en_US.” In one embodiment, the symbol may be a visual representation of the candidate term, the type may be defined within an ontology used by the knowledge graph 110, the label may be considered the main label, while others may be considered aliases, the description may be a short multilingual description of the candidate term, and the literals are properties of the candidate term defined in the ontology to provide additional information. the possible terms are defined.The analysis module 106 can determine the multilevel relationship between the two terms based on the corresponding data mentioned above. For example, the analysis module 106 can determine a first relationship 418 in which "Playdium (School)" 402 has a student named "Harry 404," and a second relationship 420 in which "Harry 404" is a member (student) of "Playdium 402." The multilevel relationship information between entities associated with keywords (terms) can be used to determine the entity type of each keyword (term) and to select one or more actionable items for each keyword. Thus, a multilevel relationship refers to a relationship between individual data items organized into multiple hierarchical levels.

[0054] Fig. 5 illustrates an example implementation 500 of the selectable quick action rendering system 100 using a knowledge graph, according to an embodiment of the present disclosure. For example, in one embodiment of the present disclosure, the user may write "Wacom is building the future of notetaking with digital ink." in a handwritten document 206, as shown by 502. The selectable quick action rendering system 100 may first recognize the handwritten text 208, as shown by 514, and identify "Wacom" and "digital ink" as keywords for providing one or more quick actions. The selectable quick action rendering system 100 then classifies each of the identified keywords 212 into a corresponding entity type.To classify each of the keywords 212 into an entity type, the analysis module 106 performs a first-level search for "Wacom" and "digital ink" in the knowledge graph 110 to identify first-level search nodes 508 and 506, respectively. The selectable quick action rendering system 100 may then determine a multi-level relationship through nodes 512 and 510, respectively. Based on such a multi-level relationship of the identified keywords, the analysis module 106 identifies the entity type of the keywords 212, such as "company" for "Wacom" and "product" for "digital ink." The analysis module 106 then determines a set of actionable elements for the keywords to generate one or more corresponding quick actions.In an exemplary embodiment, one or more quick actions are rendered on the handwritten document 206 in the form of a dynamic window, as shown by 504, to encourage the user to display more information about the keyword "Wacom."

[0055] Fig. 6A to 6H show exemplary results of the system 100 for reproducing selectable quick actions according to various embodiments of the present disclosure. For brevity, the Fig. 6A to Fig. 6H explained together.

[0056] In an implementation 600A of the present disclosure, as in Fig. 6A, the electronic device 202 may enable the user to generate a handwritten document 206, such as "Document 1," with handwritten text 208. Further, the selectable quick action rendering system 100 may use one or more steps, as described above, to recognize the handwritten text 208 and identify one or more keywords, such as "Markus Weber" 602A, and classify them into the "Person" entity type. Based on the classified entity type, the selectable quick action rendering system 100 determines a set of actionable items to be rendered for people and generates one or more quick actions specific to "Markus Weber" 602A.Further, the selectable quick action playback system 100 may highlight “Markus Weber” 602A on the handwritten document 206 so that when the user clicks on it, a dynamic window 604A appears on the screen of the electronic device 202 displaying more information about “Markus Weber” 602A corresponding to the quick action generated.

[0057] In another implementation 600B of the present disclosure, as in Fig. 6B, the selectable quick action rendering system 100 may identify one or more keywords, such as "Wacom Europe GmbH" 602B, and classify them into the entity type "Company." Based on the classified entity type, the selectable quick action rendering system 100 determines a set of actionable items to be rendered for companies and generates one or more quick actions specific to "Wacom Europe GmbH" 602B. Further, the selectable quick action rendering system 100 may highlight "Wacom Europe GmbH" 602B on the handwritten document 206 so that when the user clicks (e.g., with a mouse cursor or the like), the user may select the quick action(s) to be rendered.) hovers over “Wacom Europe GmbH” 602B for more than a threshold amount of time, a dynamic window 604B appears on the screen of the electronic device 202, displaying more information about “Wacom Europe GmbH” 602B corresponding to the quick action generated.

[0058] In yet another implementation 600C of the present disclosure, as in Fig. 6C, the selectable quick action rendering system 100 may identify one or more keywords, such as "WILL" 602C, and classify them into the entity type "Product." Based on the classified entity type, the selectable quick action rendering system 100 determines a set of actionable items to be rendered for the product and generates one or more quick actions specific to "WILL" 602C. Further, the selectable quick action rendering system 100 may highlight "WILL" 602C on the handwritten document 206 such that when the user hovers (with a mouse cursor or the like) over or clicks on "WILL" 602C for more than a threshold amount of time, a dynamic window 604C appears on the screen of the electronic device 202, displaying more information about "WILL" 602C corresponding to the generated quick action.

[0059] In yet another implementation 600D of the present disclosure, as in Fig. 6D, the selectable quick action rendering system 100 may identify one or more keywords, such as "Wacom Intuos" 602D, and classify them into the "Product" entity type. Based on the classified entity type, the selectable quick action rendering system 100 determines a set of actionable items that should be rendered for the product and generates one or more quick actions specific to the "Wacom Intuos" 602D. Further, to render selectable quick actions, the system 100 may highlight “Wacom Intuos” 602D on the handwritten document 206 such that when the user clicks on “Wacom Int” 602D or hovers over “Wacom Int” 602D for more than a threshold amount of time, a dynamic window 604D appears on the screen of the electronic device 202 displaying more information about “Wacom Intuos” 602D corresponding to the quick action generated.

[0060] In yet another implementation 600E of the present disclosure, as in Fig. 6E, the selectable quick action rendering system 100 may identify one or more keywords, such as "semantic ink" 602E, and classify them into the "technology" entity type. Based on the classified entity type, the selectable quick action rendering system 100 determines a set of actionable items that should be rendered for the technology and generates one or more quick actions specific to "semantic ink" 602E. Further, the selectable quick action rendering system 100 may highlight "semantic ink" 602E on the handwritten document 206 and display a small window 604E to render quick information about "semantic ink" 602E extracted from one or more sources corresponding to the generated quick action.

[0061] In yet another implementation 600F of the present disclosure, as in Fig. 6F, the selectable quick action rendering system 100 may identify one or more keywords, such as "Named Entity Linking" 602F, and classify them into the "Technology" entity type. Based on the classified entity type, the selectable quick action rendering system 100 determines a set of actionable items that should be rendered for the technology and generates one or more quick actions specific to "Named Entity Linking" 602F. Further, the selectable quick action rendering system 100 may highlight "Named Entity Linking" 602F on the handwritten document 206 and display a small window 604F to show detailed information about "Named Entity Linking" 602F with one or more hyperlinks to allow the user to access one or more relevant documents to obtain more information about "Named Entity Linking" 602F.

[0062] In yet another implementation 600G of the present disclosure, as in Fig. 6G, the selectable quick action playback system 100 may identify one or more keywords, such as "Shinjuku Grand Tower" 602G, and classify them into the "location" entity type. Based on the classified entity type, the selectable quick action playback system 100 determines a set of actionable items that should be rendered for the location and generates one or more quick actions specific to "Shinjuku Grand Tower" 602G. Further, the selectable quick action playback system 100 may highlight "Shinjuku Grand Tower" 602G on the handwritten document 206 and display a small window 604G to show detailed information about "Shinjuku Grand Tower" 602G, along with a selectable "Navigation to Shinjuku Grand Tower" 606A option.The user can click the selectable option “Navigation to Shinjuku Grand Tower” 606A to automatically open a map for navigation to “Shinjuku Grand Tower” 602G.

[0063] In yet another implementation 600H of the present disclosure, as in Fig. 6H, the selectable quick action playback system 100 may identify one or more keywords, such as "Consumer Electronic Show" and "December 15th" 602H, and classify them into the "Event with Date" entity type. Based on the classified entity type, the selectable quick action playback system 100 determines a set of actionable items to be played for the event and generates one or more quick actions specific to "Consumer Electronic Show" and "December 15th" 602H. Further, to play selectable quick actions, the system 100 may highlight “Consumer Electronic Show” along with “December 15th” 602H on the handwritten document 206 and display a small window 604H to show detailed information about “Consumer Electronic Show” 602H along with a selectable option for “Add Consumer Electronic Show to Calendar for December 15th” 606B.The user can click the selectable option “Add Consumer Electronic Show to Calendar for December 15” 606B to automatically open the calendar to create an entry for the Consumer Electronic Show on December 15 without performing a series of manual steps to open the calendar, enter an event, enter a date, or the like.

[0064] Fig. 7 illustrates a flowchart 700 of an exemplary method for providing selectable quick actions on handwritten data in a handwritten document according to an embodiment of the present disclosure. The method begins at step 702.

[0065] First, in step 704, handwritten data is acquired (e.g., received). The handwritten data may correspond to writing made by a user in the handwritten document on a screen of an electronic device. Next, in step 706, text associated with the handwritten data is recognized. The text may be recognized, for example, by applying a handwriting recognition technique.

[0066] Next, in step 708, one or more keywords are identified in the identified text. In one embodiment of the present disclosure, the one or more keywords are identified by applying predictive learning based on the profile associated with the user. Once the one or more keywords are identified, one or more associated quick actions to be rendered to the user are identified. In such a scenario, the profile associated with the user may also include historical data of the user indicating keywords of interest to the user, keywords the user should know, keywords the user knows, keywords appropriate for the user, and / or keywords inappropriate for the user.In another embodiment of the present disclosure, the one or more keywords are identified by applying predictive learning based on the profile associated with the user to identify one or more specific quick actions of interest to the user. In such a scenario, the profile associated with the user may also include user interests, the user's occupation, the user's schedule, and / or the user's event list.

[0067] Next, in step 710, each identified keyword is classified into an entity type from one or more entity types. The one or more keywords may be classified into a respective entity type by applying named entity recognition, named entity linking, a knowledge graph, or a combination thereof. The entity types may be one or more of "person," "business," "legal entity," "location," "event," "abstract concept," "service," "product," or any combination thereof.

[0068] Next, in step 712, a set of actionable items associated with the classified entity type corresponding to the respective keyword is determined. The set of actionable items may include: displaying relevant information, displaying social media links, displaying a description, displaying alternative names, displaying email addresses, displaying a planner, displaying weather information, displaying options for booking accommodations, displaying options for adding an event to a calendar, displaying aggregated relevant information, displaying options for a digital wallet, displaying a "More..."“links, displaying options to make a direct call, displaying RSVP options, displaying options to opt in / out of an event, displaying options to purchase a product, or a combination thereof.

[0069] Next, in step 714, one or more user-selectable quick actions are generated for each keyword based on the determined set of actionable items via the knowledge graph. The quick actions may include providing, for each keyword, personal information, business information, one-touch social media links, a description, alternate names, mail abbreviations, planners, weather information, options for booking lodging, an option for adding an event to a calendar, summarized relevant information along with one or more links, "More..." links, calling options, RSVP message options, shortcuts for enabling / disabling a service, options for purchasing a product, or a combination thereof.

[0070] Next, in step 716, the generated quick actions associated with the respective keyword are rendered on the handwritten document based on a profile associated with the user. The quick actions may be rendered in the form of a list of all quick actions for the respective keyword on the handwritten document, with highlighting added to the one or more keywords to render the corresponding quick actions, and / or with the quick actions presented in a dynamic window that overlays, is arranged next to, above, or below the one or more keywords in the digital document. Such a dynamic window for a particular keyword may be generated, for example, when a predicted user action score for a particular quick action is greater than a threshold.Further, the dynamic window may appear based on an action, such as clicking on the keyword or hovering over the keyword for more than a threshold amount of time. The method may end at step 718.

[0071] Fig. Figure 8 illustrates an exemplary computer system in or with which embodiments of the present disclosure may be used. As in Fig. 8, a computer system 800 includes an external storage device 814, a bus 812, a main memory 806, a read-only memory 808, a mass storage device 810, a communications port 804, and a processor 802.

[0072] Those skilled in the art will appreciate that computer system 800 may also include more than one processor 802 and more than one communication port 804. Examples of processor 802 include, but are not limited to, Intel® Itanium® and Itanium 2 processors, as well as AMD® Opteron® or Athlon MP® processors, Motorola® series processors, FortiSOC™ system-on-chip processors, and other future processors. Processor 802 may include various modules associated with embodiments of the present disclosure.

[0073] The communications port 804 may be an RS-232 port for use with a modem-based dial-up connection, a 10 / 100 Ethernet port, a Gigabit or 10 Gigabit port using copper or fiber optic, a serial port, a parallel port, or other existing or future ports. The communications port 804 may be selected depending on a network, such as a local area network (LAN), a wide area network (WAN), or any network to which the computer system connects.

[0074] Memory 806 may be random access memory (RAM) or any other dynamic storage device well known in the art. Read-only memory 808 may be any static storage device, e.g., a programmable read-only memory (PROM) chip for storing static information, e.g., boot or BIOS instructions for processor 802.

[0075] Mass storage 810 may be any current or future mass storage device that can be used to store information and / or instructions. Example mass storage solutions include, but are not limited to, hard disk drives and solid-state drives (internal or external, e.g., with Universal Serial Bus (USB) and / or Firewire interfaces), e.g., those available from Seagate (e.g., the Seagate Barracuda 7200 family) or Hitachi (e.g., the Hitachi Deskstar 7K1000), one or more optical disks, RAID (redundant array of independent disks) storage, e.g., an array of hard disks (e.g., a SATA array), as available from various vendors, such as Dot Hill Systems Corp., LaCie, Nexsan Technologies, Inc., and Enhance Technology, Inc.

[0076] Bus 812 communicatively couples processor(s) 814 to the other memory, storage, and communication blocks. Bus 812 may be, for example, a Peripheral Component Interconnect (PCI) / PCI Extended (PCI-X) bus, Small Computer System Interface (SCSI), USB, or the like for connecting expansion cards, drives, and other subsystems, as well as other buses, such as a Front Side Bus (FSB), that connects processor 802 to a software system.

[0077] Optionally, operator and management interfaces, e.g., a display, a keyboard, and a cursor control device, may also be coupled to bus 812 to support direct operator interaction with the computer system. Other operator and management interfaces may be provided by network connections connected through communications port 804. External storage device 814 may be any type of external hard drive, floppy disk, IOMEGA® Zip Drive, Compact Disc Read-Only Memory (CD-ROM), Compact Disc Rewritable (CD-RW), or Digital Video Disc Read-Only Memory (DVD-ROM). The components described above are merely illustrative of various possibilities. In no way is the above exemplary computer system intended to limit the scope of the present disclosure.

[0078] Although embodiments of the present disclosure have been illustrated and described, it should be understood that the disclosure is not limited to these embodiments. Numerous modifications, changes, variations, substitutions, and equivalents will be apparent to those skilled in the art without departing from the scope of the disclosure.

[0079] Thus, one of ordinary skill in the art will recognize that the diagrams, schematics, and the like represent conceptual views or processes illustrating systems and methods embodying this disclosure. The functions of the various elements shown in the figures may be provided through the use of dedicated hardware, as well as hardware capable of executing associated software. Likewise, any switches shown in the figures are to be understood only conceptually. Their functionality may be performed through the operation of program logic, through dedicated logic, through the interaction of program control and dedicated logic, or even manually, with the exact technique being selectable by the entity implementing the present disclosure.Those of ordinary skill in the art will further recognize that the exemplary hardware, software, processes, methods, and / or operating systems described herein are for illustrative purposes only and are not intended to be limited to any particular one.

[0080] As used herein, and unless the context indicates otherwise, the term "coupled with" is intended to include both direct coupling (where two coupled elements touch each other) and indirect coupling (where at least one additional element is located between the two elements). Therefore, the terms "coupled to" and "coupled with" are used interchangeably. In the context of this document, the terms "coupled to" and "coupled with" are also used euphemistically to mean "communicatively coupled with" over a network, where two or more devices can exchange data with each other over the network, possibly via one or more intermediate devices.

[0081] It should be obvious to one skilled in the art that many more modifications than those already described are possible without departing from the inventive concepts herein. The inventive subject matter is therefore not to be limited except to the scope of the appended claims. Furthermore, in interpreting both the specification and the claims, all terms should be construed as broadly as possible, consistent with the context. In particular, the terms "comprising" and "including" should be construed to refer to elements, components, or steps in a non-exclusive manner, indicating that the elements, components, or steps in question may be present or used, or combined with other elements, components, or steps not expressly referred to.If the description or claims refer to at least one of something selected from the group consisting of A, B, C ... and N, the text should be interpreted to require only one element from the group, not A plus N or B plus N, etc.

[0082] While the foregoing describes various embodiments of the disclosure, other and further embodiments of the disclosure may be developed without departing from the basic scope thereof. The scope of the disclosure is determined by the following claims. The disclosure is not limited to the described embodiments, versions, or examples, which are explained to enable one of ordinary skill in the art to make and use the disclosure when combined with information and knowledge available to one of ordinary skill in the art. LIST OF REFERENCE SYMBOLS 100 systems 102 Receiver module 104 Detection module 106 Analysis module 108 Playback module 110 Knowledge graph 202 electronic device 204 User interface 206, 302 handwritten document 208 handwritten text 210 recognized text 212 identified keywords 212 keyword 304 Object 306 expression 402 School symbol 404 personal profile 406B corresponding URI 408A, 408B Type 410A, 410B label 412A, 412B Alias 414A, 414B Description 416A, 416B Literal 418 first relationship 420 second relationship 604A-D dynamic window 604E-H small window 700 Flowchart 800 computer system 802 processor 804 communication port 806 main memory 808 Read-only memory 810 mass storage 810 Mass storage device 812 Bus 814 external storage device QUOTES CONTAINED IN THE DESCRIPTION

[0000] This list of documents submitted by the applicant was generated automatically and is included solely for the convenience of the reader. This list is not part of the German patent or utility model application. The DPMA assumes no liability for any errors or omissions. Cited non-patent literature

[0000] Company A is producing a new type of tablet.” (German: “Company A is producing a new type of tablet

[0047]

Claims

[1] A system for providing selectable quick actions on handwritten data in a handwritten document (206, 302), the system comprising: a receiver module (102) configured to obtain handwritten data corresponding to writings made by a user in a handwritten document (206, 302) on a screen of an electronic device (202); a detection module (104) which is configured: to recognize text associated with the received handwritten data by applying a handwriting recognition technique; and to identify one or more keywords (212) in the recognized text (210); an analysis module (106) which is configured: classify each identified keyword (212) into an entity type of one or more entity types by applying proper name recognition, proper name linking and / or a knowledge graph (110); to determine a set of actionable elements associated with the classified entity type corresponding to the respective keyword; and based on the determined set of actionable elements, generate one or more quick actions selectable by the user for each keyword (212) across the knowledge graph (110); and a playback module (108) configured to play back the generated quick actions associated with the respective keyword on the handwritten document (206, 302) based on a profile (404) associated with the user. [2] The system of claim 1, wherein the electronic device (202) is a touch-enabled device, a stylus-enabled device, and / or a pen-enabled device, and comprises a mobile phone, a tablet, a personal computer, a digital signage, a smartboard, and / or a television. [3] A system according to claim 1 or 2, arranged to receive the handwritten data in the form of one or more tuples comprising data on x-coordinates, data on y-coordinates, pressure, writing speed and / or orientation. [4] The system of claim 3, further comprising the means for analyzing each received tuple by means of the handwriting recognition technique to identify the closest recognized term that the respective received tuple potentially represents. [5] The system of any one of claims 1 to 4, wherein the recognition module (104) is configured to remove unnecessary data from the recognized text (210) and to identify one or more of the keywords (212), the unnecessary data including periods, punctuation marks and / or spaces. [6] The system of any one of claims 1 to 5, wherein the entity types include at least one of "person", "company", "legal entity", "location", "event", "abstract concept", "service", and "product". [7] The system of any one of claims 1 to 6, wherein the set of actionable elements includes at least one of the following: displaying relationship information, displaying social media links, displaying a description (414), displaying alternative names, displaying email addresses, displaying a planner, displaying weather information, displaying options for booking accommodation, displaying an option for adding an event to a calendar, displaying summarized relevant information, displaying options for a digital wallet, displaying a "more..." link, displaying options for a direct call, displaying RSVP options, displaying options for enabling / disabling an event, or displaying options for purchasing a product. [8] The system of any one of claims 1 to 7, wherein the one or more quick actions include providing, for each keyword (212), personal information, business information, one-touch social media links, a description (414), alternative names, mail abbreviations, a planner, weather information, options for booking lodging, an option for adding an event to a calendar, summarized relevant information along with one or more links, a "more..." link, call options, RSVP message options, shortcuts for enabling / disabling a service, or options for purchasing a product. [9] The system of any one of claims 1 to 8, wherein the rendering module (108) renders the one or more quick actions in the form of a list of all quick actions for the respective keyword on the handwritten document (206, 302), wherein a highlight is added to the one or more keywords to render the corresponding quick actions, and / or wherein the one or more quick actions are presented in a dynamic window (222, 604) overlaid on, adjacent to, above, or below the one or more keywords (212) in the handwritten document (206, 302). [10] The system of claim 9, wherein the dynamic window (222, 604) is generated for a particular keyword when a predicted user action score for a particular quick action is greater than a threshold, and wherein the dynamic window (222, 604) appears based on an action that includes clicking on the keyword (212) and / or hovering over the keyword (212) for more than a threshold amount of time. [11] The system of any one of claims 1 to 10, wherein the rendering module (108) uses predictive learning based on the profile (404) associated with the user to identify the one or more keywords (212) for which the one or more quick actions should be rendered, wherein the profile (404) associated with the user also includes historical data of the user indicating keywords (212) of interest to the user, keywords (212) the user should know, keywords (212) the user knows, keywords (212) appropriate for the user, and / or keywords (212) inappropriate for the user. [12] The system of any one of claims 1 to 11, wherein the rendering module (108) uses predictive learning based on a profile (404) associated with the user to identify one or more particular quick actions of interest to the user, wherein a profile (404) associated with the user includes at least one of user interests, user occupation, user schedule, and a user event list. [13] A method for providing selectable quick actions on handwritten data in a handwritten document (206, 302), the method comprising: Obtaining the handwritten data corresponding to writings made by a user in the handwritten document (206, 302) on a screen of an electronic device (202); Recognizing text associated with the received handwritten data by applying a handwriting recognition technique; Identifying one or more keywords (212) in the recognized text (210); Classifying each identified keyword (212) into an entity type of one or more entity types by applying proper name recognition, proper name linking and / or a knowledge graph (110); Determining a set of actionable elements associated with the classified entity type corresponding to the respective keyword; Generating one or more quick actions selectable by the user for each keyword (212) based on the determined set of actionable items via the knowledge graph (110); and Reproducing the one or more generated quick actions associated with the respective keyword on the handwritten document (206, 302) based on a profile (404) associated with the user. [14] The method of claim 13, wherein the entity types include at least one of "person", "business", "legal entity", "location", "event", "abstract concept", "service", and "product". [15] The method of claim 13 or 14, wherein the set of actionable elements includes: displaying relationship information, displaying social media links, displaying a description (414), displaying alternative names, displaying email addresses, displaying a planner, displaying weather information, displaying options for booking accommodation, displaying an option for adding an event to a calendar, displaying summarized relevant information, displaying options for a digital wallet, displaying a "more..." link, displaying options for a direct call, displaying RSVP options, displaying options for enabling / disabling an event, or displaying options for purchasing a product. [16] The method of claim 15, wherein the one or more quick actions include providing, for each keyword (212), personal information, business information, one-touch social media links, a description (414), alternative names, mail abbreviations, a planner, weather information, options for booking lodging, an option for adding an event to a calendar, summarized relevant information along with one or more links, a "more..." link, call options, RSVP message options, shortcuts for enabling / disabling a service, or options for purchasing a product. [17] The method of any one of claims 1 to 16, further comprising displaying the one or more quick actions in the form of a list of all quick actions for the respective keyword on the handwritten document (206, 302), wherein a highlight is added to the one or more keywords to display the corresponding quick actions, and / or wherein the one or more quick actions are displayed in a dynamic window (222, 604) overlaid on, adjacent to, above, or below the one or more keywords (212) in the digital document. [18] The method of claim 17, wherein the dynamic window (222, 604) is generated for a particular keyword when a predicted user action score for a particular quick action is greater than a threshold, and wherein the dynamic window (222, 604) appears based on an action that includes clicking on the keyword (212) and / or hovering over the keyword (212) for more than a threshold amount of time. [19] The method of any one of claims 1 to 18, further comprising applying predictive learning based on the profile (404) associated with the user to identify the one or more keywords (212) for which the one or more quick actions should be rendered to the user, wherein the profile (404) associated with the user also includes historical data of the user indicating keywords (212) of interest to the user, keywords (212) the user should know, keywords (212) the user knows, keywords (212) appropriate for the user, and / or keywords (212) inappropriate for the user. [20] The method of any one of claims 1 to 19, further comprising applying predictive learning based on the profile (404) associated with the user to identify one or more particular quick actions of interest to the user, wherein a profile (404) associated with the user includes at least one of user interests, user occupation, user schedule, and user event list.

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