DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102 of this title, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filling date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-5, 7-9 and 11-20 are rejected under 35 U.S.C. 103 as being unpatentable by O'Donoghue et al. (U.S. 2015/0178812 A1) in view of Canada et al. (U.S. 2024/0242391 A1).
Regarding Claim 1, O’Donoghue discloses a booklist cover generation method (O’Donoghue, [0013] “a method” and [0032] “a publisher's indicia (e.g., book cover or illustration for the book or e-book) of an e-book for the book title [0035] “the processor 210 to generate lists that reflect sets of e-books or book titles” O’Donoghue teaches a booklist (a book title) cover generation method, comprises:
acquiring booklist information of a target mark booklist wherein the target booklist indicates a book collection (O’Donoghue, [0036] “a collection of records 241 that individually identify book titles that the user has marked as having previously been read” O’Donoghue teaches acquiring a booklist (a book titles) information of a mark booklist indicates a collection of list (records) of the book, and the booklist information represents introduction information for the target booklist (O’Donoghue, [0036] “Each record 241 in the collection can include (i) an identifier to an e-book version of the book title, such as an identifier 243 that locates the particular e-book on the e-book store 122 of the network service 120; and (ii) the publisher's indicia 235 (e.g., publisher's illustration or book cover) for the book title or the e-book version of the book title. Still further, in one implementation, each record 243 in the collection can include a link that enables the user to immediately purchase or download the e-book that corresponds to the identified book title” O’Donoghue teaches the booklist information represents introduction information for the mark booklist such as an e-book version of the book title, publisher's illustration on book cover, the link that enable records, etc.
determining cover image description information for the target booklist based on the booklist information (O’Donoghue, [0062] “FIG. 5, interface 500 can be provided in context of an output of a recommendation engine that recommends book titles to the user. The book title images 510 include publisher indicia for a given book title. The publisher indicia can include the cover or jacket image 512, along with other information (e.g., author, summary etc.)” O’Donoghue teaches determining cover image description information e.g., author, summary etc. based on the recommend book.
generating a cover image for the target booklist based on the cover image description information (O’Donoghue, [0062] “FIG. 5, interface 500 can be provided in context of an output of a recommendation engine that recommends book titles to the user. The book title images 510 include publisher indicia for a given book title. The publisher indicia can include the cover or jacket image 512, along with other information (e.g., author, summary etc.)” O’ Donoghue teaches generating a cover image (Fig. 5) for the mark booklist based on the cover image description information e.g., author, summary etc.
However, O’Donoghue does not explicitly teach acquiring booklist information of a target booklist.
where the cover image description information comprises description information corresponding to at least one attribute characteristic dimension of booklist
Canada teaches acquiring booklist information of a target booklist (Canada, [0055] “A GUI element such as a “target” or “focus area” comprising a subset of a display screen on which the stream of image data being captured from the real-world environment is being displayed is presented to a user in order to allow the user to “place” the desired planar surface in the target area for processing” and [0056] “a user may capture image data of the real-world environment that includes a table with a book placed on the table surface. One or both of the table surface and/or book cover may be evaluated by one or more feature detection” Canada teaches acquiring a target booklist (target includes a subset of table with a book) placed on the table surface or book cover with information be evaluated.
the cover image description information comprises description information corresponding to at least one attribute characteristic dimension of booklist (Canada, [0056] “One or both of the table surface and/or book cover may be evaluated by one or more feature detection algorithms” and [0028] “all objects in the catalog may have various properties and/or attributes associated with it. For example, each item in a catalog may be associated with , a representative 2D image, and dimensions (e.g., a product's height, width and depth)” Canada teaches the book cover image corresponding to at least one attribute dimension of booklist e.g., a product’s height, width and depth.
O’Donoghue and Canada are combinable because they are from the same field of endeavor, system and method for image processing and try to solve similar problems. It would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention was made for modifying the method of O’Donoghue to combine with acquiring booklist information of a target booklist (as taught by Canada) in order to acquire booklist information of a target booklist because Canada can provide acquiring a target booklist (target includes a subset of table with a book) placed on the table surface or book cover with information be evaluated (Canada, [0055], [0056]). Doing so, it may provide an approach allows a user to navigate to a product page to view the product in a desired environment, the user can search for candidate art pieces or other items of interest from within the virtual environment of the physical space (Canada, [0030]).
Regarding Claim 2, a combination of O’Donoghue and Canada discloses the method of claim 1, wherein the determining cover image description information for the target booklist based on the booklist information, comprises:
determining book type information corresponding to the target booklist based on the booklist information (O’Donoghue, [0033] “the display 230 can correspond to an electronic paper type display, which mimics conventional paper in the manner in which content is displayed, display technologies include electrophoretic displays, electrowetting displays, and electrofluidic displays” O’Donoghue teaches determining book type information e.g., a paper type display corresponding to the target booklist in which content is displayed such as electrophoretic displays, electrowetting displays, and electrofluidic displays;
determining the cover image description information for the target booklist based on the book type information (O’Donoghue, [0034] the processor 210 identifies input from the user that corresponds to (i) the user browsing book titles for purchase or download…(iv) the user performing page viewing activities with a rendered e-book…(e.g., the user read a paperback or hard cover version of the book) O’Donoghue teaches determining (identifying) the cover image description information e.g., the version of the book based on the book type information (e-book display).
Regarding Claim 3, a combination of O’Donoghue and Canada discloses the method of claim 2, wherein the booklist information of the target booklist comprises:
title information and brief information, and wherein the determining cover image description information for the target booklist based on the booklist information, comprises:
inputting the title information and/or brief information into a booklist type determination model to obtain the book type information corresponding to the target booklist (O’Donoghue, [0034] “the processor 210 generates a prompt via the display 230, and detects a corresponding input from the user that corresponds to a book read input 225, reflects a designation by the user that a particular book title has previously been read by the user. the book read input 225 can register that the book title that the user has encountered e.g., when browsing or receiving recommendations
…e.g., the user read a paperback or hard cover version of the book” O’Donoghue teaches inputting the title information e.g., a designation version by the user that a particular book title has previously been read by the user or register that the book tile when browsing or receiving recommendation to obtain the book type in e-book display.
Regarding Claim 4, a combination of O’Donoghue and Canada discloses the method of claim 2, wherein the determining the cover image description information for the target booklist based on the book type information, comprises:
determining multiple pieces of candidate cover image description information corresponding to the book type information in a library of cover image description information (O’Donoghue, [0015] “The library representation includes the publisher indicia of the electronic book identified by one or more first records in the collection and the publisher indicia of the second record” and Fig. 1 [0035] “The library logic can be implemented by the processor 210 to generate lists that reflect sets of e-books or book titles” O’Donoghue teaches determining multiple pieces of pieces of candidate cover image description, e.g., the publisher indica images of records in the collection of the lists that reflect sets of e-book (book type) or book titles from a library (Fig. 1);
However, O’Donoghue does not explicitly teach selecting any target cover image description information from the multiple pieces of candidate cover image description information; and determining the target cover image description information as the cover image description information for the target booklist.
Canada teaches selecting any target cover image description information from the multiple pieces of candidate cover image description information; and determining the target cover image description information as the cover image description information for the target booklist (Canada, [0055] “a “target” or “focus area” comprising a subset of a display screen on which the stream of image data being captured…in order to allow the user to “place” the desired planar surface in the target area for processing” and Fig. 2A, 2B, [0029] “a product page 208 may have a button 206 that allows the user to view the product associated with that product page in a camera environment” Canada teaches selecting a target cover image description (a couch 222 using button 206, Fig. 2B) from the multiple pieces of candidate cover image and determining the target cover image description information e.g., “North South Furniture prices: $98.99, Buy it, etc.
O’Donoghue and Canada are combinable see rationale in claim 1.
Regarding Claim 5, the method of claim 4, O’Donoghue does not explicitly teach wherein the selecting any target cover image description information from the multiple pieces of candidate cover image description information, comprises:
determining descriptive keywords based on the list information of the target list; and selecting the target cover image description information from the multiple pieces of candidate cover image description information according to the descriptive keywords.
However, Canada teaches determining descriptive keywords based on the list information of the target list (Canada, [0031] “The search term can be compared to a stored set of keywords to determine matching keywords to the search term, where a stored keyword is associated with a product” Canada teaches a set of keywords to determine matching keywords to the search term is associated with a target product; and
selecting the target cover image description information from the multiple pieces of candidate cover image description information according to the descriptive keywords (Canada, Fig. 2A, 2B, [0029] “a product page 208 may have a button 206 that allows the user to view the product associated with that product page in a camera environment” Canada teaches selecting a target cover image description (a couch 222 using button 206, Fig. 2B) from the multiple pieces of candidate cover image and determining the target cover image description keywords e.g., “Home décor, North South Furniture prices: $98.99, Buy it, etc.
O’Donoghue and Canada are combinable see rationale in claim 1.
Regarding Claim 7, the method of claim 1, O’Donoghue does not explicitly teach wherein the generating the cover image for the target booklist based on the cover image description information, comprises at least one of:
inputting the cover image description information into a cover generation module to obtain the cover image for the target booklist (O’Donoghue, [0062] “FIG. 5. The interface 500 can include a feature 515 that enables the user to provide feedback that includes input indicating the user has previously read the book title. The feature 515 can correspond to the user indicating that they have read the book title” O’Donoghue teaches inputting the cover image description “I’ve Read it” 515 to obtain the cover image for the target booklist.
or determining descriptive keywords based on the booklist information of the target list,
However, O’Donoghue does not explicitly teach generating the cover image for the target booklist based on the descriptive keywords and the cover image description information.
Canada teaches generating the cover image for the target booklist based on the descriptive keywords and the cover image description information (Canada, “Fig. 2A, 2B, [0029] “a product page 208 may have a button 206 that allows the user to view the product associated with that product page in a camera environment” Canada teaches generating cover image (Fig. 2B) based on the descriptive keywords (button 206, Fig. 2A) and the cover image description information “Tap to view in your home”.
O’Donoghue and Canada are combinable see rationale in claim 1.
Regarding Claim 8, the method of claim 7, O’Donoghue does not explicitly teach wherein the determining descriptive keywords based on the booklist information of the target list, comprises:
determining the descriptive keywords based on the title information of the target booklist; or, determining at least one intention information based on the title information of the target booklist, and
determining the descriptive keywords based on the intention information.
However, Canada teaches determining the descriptive keywords based on the title information of the target booklist; and determining the descriptive keywords based on the intention information (Canada, Fig. 2A, 2B, [0029] “a product page 208 may have a button 206 that allows the user to view the product associated with that product page in a camera environment” Canada teaches determining the descriptive keywords based on the title information of the target booklist e.g. Fig. 2A, the key word “ Home décor” as the title information of the target booklist, and determining the descriptive keywords “Tap to view” based on the intention information “Tap to view in your home”.
O’Donoghue and Canada are combinable see rationale in claim 1.
Regarding Claim 9, the method of claim 8, O’Donoghue does not explicitly teach wherein the determining at least one intention information based on the title information of the target booklist, comprises:
inputting the title information into an intention determination model to obtain at least one intention information corresponding to the title information, wherein each intention information corresponds to at least one intention dimension;
where, the intention dimension comprises one of theme, role, plot, style and evaluation.
However, Canada teaches wherein the determining at least one intention information based on the title information of the target booklist (Canada, [0061] “Once the user confirms the selection a notification 722 might be sent to the customer to notify the customer of the selection, as illustrated in the example situation 720 of FIG. 7B” Canada teaches determining one intention information based on the title information of the target booklist (Fig. 7B), comprises:
inputting the title information into an intention determination model to obtain at least one intention information corresponding to the title information (Canada, [0061] Once the user confirms the selection a notification 722 might be sent to the customer to notify the customer of the selection, as illustrated in the example situation 720 of FIG. 7B. The notification can include a link, option, or instructions for accessing a view 740 of the selections and the space, as illustrated in FIG. 7C” Canada teaches inputting the title information (yes, no) into an intention determination model (confirm model) to obtain one intention information (we want…them now?), wherein each intention information corresponds to at least one intention dimension (Canada, [0075] “there can be various ways to determine which items to suggest for a customer space, autosuggestions based at least in part upon items purchased by the customer, items purchased by others having similar items in a similar space. These can also be based upon the size of the space, colors of the space” Canada teaches an intention information corresponding to one intention dimension (based upon the size of the space).
where, the intention dimension comprises one of theme, role, plot, style and evaluation (Canada, [0055] “A user captures image data of the physical space and provides an indication of a selection of one or more areas of the image data that the user would like to have evaluated for the presence of a suitable planar surface” and [0056] “One or both of the table surface and/or book cover may be evaluated by one or more feature detection algorithms (e.g., interest point extraction, regions of interest points, edge detection, ridge descriptor analysis etc.) to determine if the planar surface is a feature-rich surface; i.e., a flat object or plane with complex intensity patterns” Canada teaches the intention dimension include one of plot, style e.g., interest point extraction, regions of interest points, edge detection, ridge descriptor analysis etc.) to determine if the planar surface is a feature-rich surface; i.e., a flat object or plane with complex intensity patterns.
O’Donoghue and Canada are combinable see rationale in claim 1.
Regarding Claim 11, the method of claim 7, O’Donoghue does not explicitly teach wherein the generating the cover image for the target booklist based on the descriptive keywords and the cover image description information, comprises:
obtaining image content according to the cover image description information; generating the cover image for the target booklist based on the descriptive keywords and the image content.
However, Canada teaches obtaining image content according to the cover image description information; generating the cover image for the target booklist based on the descriptive keywords and the image content (Canada, [0031] “The search term can be compared to a stored set of keywords to determine matching keywords to the search term, where a stored keyword is associated with a product” and “Fig. 2A, 2B, [0029] “a product page 208 may have a button 206 that allows the user to view the product associated with that product page in a camera environment” Canada teaches obtain a target cover image description (a couch 222, Fig. 2B) and generating cover image (button 206) based on the descriptive keywords and the image content e.g., Home décor, “North South Furniture”, prices: $98.99, Buy it, etc.
O’Donoghue and Canada are combinable see rationale in claim 1.
Regarding Claim 12, the method of claim 11, O’Donoghue does not explicitly teach wherein the generating the cover image for the target booklist based on the descriptive keywords and the image content, comprises:
when it is recognized that there exists a target object in the image content, determining a presentation position for the descriptive keywords based on the target object; adding the descriptive keywords onto the image content according to the presentation position for the descriptive keywords, to generate the cover image for the target booklist.
However, Canada teaches when it is recognized that there exists a target object in the image content, determining a presentation position for the descriptive keywords based on the target object (Canada, Fig. 2A, [0029] “a product page 208 may have a button 206 that allows the user to view the product associated with that product page in a camera environment, an image of a couch 222 is shown to be displayed over the view of the scene in the image 224” Canada teaches exists a target object in the image content (a couch 222 in the image 224) and determining a presentation position for the descriptive key words e.g., Home décor, North South Furniture, Price: $98, 99;
adding the descriptive keywords onto the image content according to the presentation position for the descriptive keywords, to generate the cover image for the target booklist (Canada, Fig. 2A, 2B, [0029] “a product page 208 may have a button 206 that allows the user to view the product associated with that product page in a camera environment, the virtual sticker can include a representation of the product as well as additional content, such as a border, a drop shadow, etc.” Canada teaches adding the descriptive keywords onto the image content e.g., “Tap to view in your home” (Fig. 2A) to generate the cover image for the target booklist, see Fig. 2B.
O’Donoghue and Canada are combinable see rationale in claim 1.
Regarding Claim 13, the method of claim 12, O’Donoghue does not explicitly teach further comprising:
selecting a target text style from a text style library according to the type of the descriptive keywords; adding the descriptive keywords onto the image content according to the presentation position for the descriptive keywords and the target text style for the descriptive keywords to generate the cover image for the target booklist.
However, Canada teaches selecting a target text style from a text style library according to the type of the descriptive keywords; adding the descriptive keywords onto the image content according to the presentation position for the descriptive keywords and the target text style for the descriptive keywords to generate the cover image for the target booklist (Canada, Figs. 2A, 2B, [0029] “a product page 208 may have a button 206 that allows the user to view the product associated with that product page in a camera environment (e.g., an augmented view of the physical space). The image can be a two-dimensional rendering of the produce such as a virtual sticker, the virtual sticker can include a representation of the product as well as additional content, such as a border, a drop shadow, etc.” Canada teaches selecting a target text style from a text style library according to the type of the descriptive keywords (select the virtual sticker, button 206, Fig. 2A), adding the descriptive keywords onto the image content and the target text style for the descriptive keywords (the virtual sticker, descriptive key words 206 “Tap to view in your home”) to generate the cover image for the target booklist, see Fig. 3B.
O’Donoghue and Canada are combinable see rationale in claim 1.
Regarding Claim 14, the method of claim 13, O’Donoghue does not explicitly teach further comprising:
determining a presentation size for the descriptive keywords according to the image content; adding the descriptive keywords onto the image content according to the presentation position, the presentation size and the target text style for the descriptive keywords to generate the cover image for the target booklist.
However, Canada teaches determining a presentation size for the descriptive keywords according to the image content; adding the descriptive keywords onto the image content according to the presentation position, the presentation size and the target text style for the descriptive keywords to generate the cover image for the target booklist (Canada, Fig. 2A, [0028] “all objects in the catalog may have various properties and/or attributes associated with it. . For example, each item in a catalog may be associated with a unique identifier (ID), a particular product page, a representative 2D image, additional images, products other people have viewed, a price, a sale price, a rating, user comments, and dimensions (e.g., a product's height, width and depth), etc.” Canada teaches determining a presentation size keyword (height, width, deep) according to the image and adding keywords according to the presentation e.g., unique identifier (ID), sale price, rating, user comments.
O’Donoghue and Canada are combinable see rationale in claim 1.
Regarding Claim 15, a combination of O’Donoghue and discloses an electronic device (O’Donoghue, [0015] “an electronic book of the book title”) comprising:
a processor (O’Donoghue, [0019] “one or more processors” and a memory “various forms of memory”, wherein the memory is used for storing a computer program, and the processor is used for calling and running the computer program (O’Donoghue, [0019] “that utilize processors, memory, and instructions may be implemented in the form of computer programs” stored in the memory to execute:
acquiring booklist information of a target booklist, wherein the target booklist indicates a book collection, and the booklist information represents introduction information for the target booklist;
determining cover image description information for the target booklist based on the booklist information, wherein the cover image description information comprises description information corresponding to at least one attribute characteristic dimension of booklist;
generating a cover image for the target booklist based on the cover image description information.
Claim 15 is substantially similar to claim 1 and is rejected based on similar analyses.
Regarding Claim 16, a combination of O’Donoghue and discloses the electronic device of claim 15, wherein the determining cover image description information for the target booklist based on the booklist information, comprises:
determining book type information corresponding to the target booklist based on the booklist information;
determining the cover image description information for the target booklist based on the book type information.
Claim 16 is substantially similar to claim 2 and is rejected based on similar analyses.
Regarding Claim 17, a combination of O’Donoghue and discloses the electronic device of claim 15, wherein the generating the cover image for the target booklist based on the cover image description information, comprises at least one of:
inputting the cover image description information into a cover generation module to obtain the cover image for the target booklist, or
determining descriptive keywords based on the booklist information of the target list, and generating the cover image for the target booklist based on the descriptive keywords and the cover image description information.
Claim 17 is substantially similar to claim 7 and is rejected based on similar analyses.
Regarding Claim 18, a combination of O’Donoghue and a non-transitory computer-readable storage medium (O’Donoghue, [0019] “a computer-readable medium” for storing a computer program that causes a computer to execute:
acquiring booklist information of a target booklist, wherein the target booklist indicates a book collection, and the booklist information represents introduction information for the target booklist;
determining cover image description information for the target booklist based on the booklist information, wherein the cover image description information comprises description information corresponding to at least one attribute characteristic dimension of booklist;
generating a cover image for the target booklist based on the cover image description information.
Claim 18 is substantially similar to claim 1 and is rejected based on similar analyses.
Regarding Claim 19, a combination of O’Donoghue and discloses the non-transitory computer-readable storage medium of claim 18, wherein the determining cover image description information for the target booklist based on the booklist information, comprises:
determining book type information corresponding to the target booklist based on the booklist information;
determining the cover image description information for the target booklist based on the book type information.
Claim 19 is substantially similar to claim 2 and is rejected based on similar analyses.
Regarding Claim 20, a combination of O’Donoghue and discloses the non-transitory computer-readable storage medium of claim 18, wherein the generating the cover image for the target booklist based on the cover image description information, comprises at least one of:
inputting the cover image description information into a cover generation module to obtain the cover image for the target booklist, or
determining descriptive keywords based on the booklist information of the target list, and generating the cover image for the target booklist based on the descriptive keywords and the cover image description information.
Claim 20 is substantially similar to claim 7 and is rejected based on similar analyses.
Claim 6 is rejected under 35 U.S.C. 103 as being unpatentable by O'Donoghue et al. (U.S. 2015/0178812 A1) in view of Canada et al. (U.S. 2024/0242391 A1) and further in view of Zhang et al. (U.S. 2025/0209844 A1).
Regarding Claim 6, the method of claim 4, a combination of O’Donoghue and Canada does not explicitly teach wherein the library of cover image description information is constructed through:
describing different book type information unfoldedly according to preset booklist characteristic dimensions to obtain multiple pieces of cover image description information corresponding to each book type information;
constructing the library of cover image description information based on the multiple pieces of cover image description information corresponding to each book type information.
However, Zhang teaches describing different book type information unfoldedly according to preset booklist characteristic dimensions to obtain multiple pieces of cover image description information corresponding to each book type information (Zhang, [0010] “dividing the text line positions into squares having a preset size, and sequentially connecting midpoints of the squares to obtain the reading order of the characters in text areas in the text line positions” and [0068] “the ratio satisfies the preset condition, the five individual characters may be further arranged according to the reading order of the characters in the text line position (i.e. a direction indicated by an arrow in the right figure), as the final recognition result of the characters in the target ancient book image shown in FIG. 5” Zhang teaches describing different book type information unfoldedly according to preset characteristic dimensions (dividing the text line positions into squares having a preset size..) to obtain multiple pieces of cover image corresponding to each book type information (ratio satisfies the preset condition, the five individual characters arranged according to the reading order of the characters in the text line position in the target ancient book image shown in FIG. 5).
constructing the library of cover image description information based on the multiple pieces of cover image description information corresponding to each book type information (Zhang, [0068] “the individual character positions corresponding to the five individual characters are located…is greater than 0.5, that is, the ratio satisfies the preset condition, arranged according to the reading order of the characters in the text line position (i.e. a direction indicated by an arrow in the right figure), arranged according to the reading order of the characters in the text line position (i.e. a direction indicated by an arrow in the right figure), as the final recognition result of the characters in the target ancient book image shown in FIG. 5” Zhang teaches constructing the library of cover image description information (the individual character positions corresponding to the five individual characters are located…is greater than 0.5, the ratio satisfies the preset condition) based on the multiple pieces of cover image to each book type information (the final recognition result of the characters in the target ancient book image shown in FIG. 5).
O’Donoghue, Canada and Zhang are combinable because they are from the same field of endeavor, system and method for image processing and try to solve similar problems. It would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention was made for modifying the method of O’Donoghue to combine with information unfoldedly according to preset booklist characteristic dimensions (as taught by Zhang) in order to obtain multiple pieces of cover image description information corresponding to each book type information because Zhang can provide information unfoldedly according to preset characteristic dimensions (dividing the text line positions into squares having a preset size..) to obtain multiple pieces of cover image corresponding to each book type information (arranged according to the reading order of the characters in the text line position in the target ancient book image shown in FIG. 5 (Zhang, [0068]). Doing so, it may provide obtain corrected content information corresponding to the individual characters (Zhang, [0012]).
Claim 10 is rejected under 35 U.S.C. 103 as being unpatentable by O'Donoghue et al. (U.S. 2015/0178812 A1) in view of Canada et al. (U.S. 2024/0242391 A1) and further in view of Huo et al. (U.S. 2015/0339700 A1).
Regarding Claim 10, O’Donoghue discloses the method of claim 8, a combination of O’Donoghue and Canada does not explicitly teach wherein the determining the descriptive keywords based on the intention information, comprises:
in response to the number of the intention information being less than a first number threshold, determining the title information as the descriptive keywords;
in response to the number of the intention information being greater than or equal to the first number threshold, selecting one or more intention information from all intention information according to priorities of the intention dimensions, and determining the selected one or more intention information as the descriptive keywords, or
determining the one or more intention information and the title information as the descriptive keywords.
However, Huo teaches wherein the determining the descriptive keywords based on the intention information (Huo, [0016] “obtaining the intention match feature between the promotion information and the keyword based on the promotion information and the keyword of the promotion information”, comprises:
in response to the number of the intention information being less than a first number threshold, determining the title information as the descriptive keywords; in response to the number of the intention information being greater than or equal to the first number threshold (Huo, [0143] “according to a length of time during which a user stays on each web page, a determination is made as to whether the promotion information is actually exposed (browsed by the user) and [0144] “Specifically, a preprocessing model represented by the following formula may be used to preprocess the data about user clicking behavior:
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wherein t represents a stay time, and T is a threshold obtained based on statistics of a large quantity of data. When t≧T, this indicates that the user has stayed on the page long enough, and really browses the promotion information presented on the page, or otherwise, the promotion information presented on the page is not really exposed. For example, when the user quickly drags a scroll bar of a search result page from the top to the bottom, the promotion information presented in the middle is not browsed by the user, and is not counted as a real exposure” Huo teaches the intention information (the promotion information) is not browsed by the user in response to the threshold T obtained based on statistics of a large quantity of data less than a first number threshold t<T and the intention information presented on the page to user based on statistics of a large quantity of data greater than or equal to a first number threshold ti =>T,
selecting one or more intention information from all intention information according to priorities of the intention dimensions, and determining the selected one or more intention information as the descriptive keywords (Huo, [0165] “the keyword is assumed to “battery of Nokia phone”, the title of promotion information A is assumed to “2014 best-selling battery for Nokia phone, the lowest price”. Using the intention match feature, the relevance between the keyword and promotion information A is measured to be higher than the relevance between the keyword and promotion information B, that is, the quality of promotion information A is better than the quality of promotion information B” Huo teaches selecting an intention information (intention match feature) according to priorities of the intention dimension (best-selling battery of Nokia phone) and determining the selected descriptive keywords (battery of Nokia phone), or
determining the one or more intention information and the title information as the descriptive keywords.
O’Donoghue, Canada and Huo are combinable because they are from the same field of endeavor, system and method for image processing and try to solve similar problems. It would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention was made for modifying the method of O’Donoghue to combine with selecting one or more intention information (as taught by Huo) in order to select one intention information according to priorities of intention because Hue can provide selecting an intention information (intention match feature) according to priorities of the intention dimension (best-selling battery of Nokia phone) and determining the selected descriptive keywords (battery of Nokia phone) (Huo, [0165]). Doing so, it may provide the reliability of acquiring the intention match feature between the promotion information and the keyword can be effectively improved, thereby improving the accuracy of the PS calculation (Huo, [0210]).
Conclusion
The prior arts made of record and not relied upon are considered pertinent to applicant's disclosure Minami et al. (U.S. 2024/0095985 A1) and Weight et al. (U.S. 9,881,009 B1).
Any inquiry concerning this communication or earlier communications from the examiner should be directed to KHOA VU whose telephone number is (571)272-5994. The examiner can normally be reached 8:00- 4:00.
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/KHOA VU/Examiner, Art Unit 2611
/KEE M TUNG/Supervisory Patent Examiner, Art Unit 2611
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