CTNF 19/255,837 CTNF 82693 Notice of Pre-AIA or AIA Status 07-03-aia AIA 15-10-aia The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA. DETAILED ACTION 1. This Office Action is in response to the application filed on 06/30/2025. Claims 1-20 are pending. Priority 2. 19255837 filed 06/30/2025 is a Continuation of PCT/CN2023/142874 , filed 12/28/2023 claims foreign priority to 202211735651.6, filed 12/30/2022. Information Disclosure Statement 4. The information disclosure statement (IDS) filed on 11/13/2025 complies with the provisions of M.P.E.P. 609. The examiner has considered it. Claim Rejections - 35 USC § 101 07-04-01 AIA 07-04 5. 35 U.S.C. 101 reads as follows: Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title. 6. Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. At Step 1 : Independent claims 1, 10 and 19 is directed to a “method", a “device” and a “program product” and thus directed to a statutory category At Step 2A, Prong One : The claim recites the following limitations directed to an abstract idea: • " obtain … a search word entered by a user " as drafted this recites a mentally performable process as an evaluation or judgement. This is also consistent with the specification as in Fig. 1 and paragraphs 59 and 64 where one can mentally visualize receiving a search word from a user. • " sending … a data query message to a server … and obtaining a first search result and a second search result … " as drafted this recites a mentally performable process as an evaluation or judgement. This is also consistent with the specification as in Fig. 1 and paragraph 61 where one can mentally visualize sending a query to a server and obtaining search results from the server. • " retrieving …from data stored in the electronic device, a third search result … " as drafted this recites a mentally performable process as an evaluation or judgement. This is also consistent with the specification as in Fig. 1 and paragraph 61 where one can mentally visualize retrieving a search result from a computing device. • " displaying, by the electronic device, a search result page … " as drafted this recites a mentally performable process as an evaluation or judgement. This is also consistent with the specification as in Fig. 1 and paragraph 61 where one can mentally visualize grouping different types of search results. At Step 2A, Prong Two : • The claim recites no additional elements. At most one might consider that a " an electronic device " and “ a server” as claimed might be considered to represent a computer-implemented system and method consistent with Fig. 1 even though the claim does not recite any computer. At most this would be a high-level recitation of a generic computer components and represents mere instructions to apply the abstract idea on a computer as in MPEP 2106.05(f), which does not provide integration into a practical application. • Viewing the additional limitations together and the claim as a whole, nothing provides integration into a practical application. At Step 2B : • The conclusions for the mere implementation using a computer are carried over and does not provide significantly more. • Looking at the claim as a whole does not change this conclusion and the claim is ineligible. Dependent Claims 2-9, 11-18 and 20 The limitations as recited in dependent claims 2-5, 11-14 and 20 recite, “arranging the first area before the second area…” which further describes the concepts performed in the human mind including an observation, evaluation, judgment, and opinion, in step 2A prong one. The limitations as recited in dependent claims 6 and 15 recite, “the type of the first search result and the third search result is the first type…” which further describes the concepts performed in the human mind including an observation, evaluation, judgment, and opinion, in step 2A prong one. The limitations as recited in dependent claims 7 and 16 recite, “displaying, by the electronic device, the search result page…” which further describes the concepts performed in the human mind including an observation, evaluation, judgment, and opinion, in step 2A prong one. The limitations as recited in dependent claims 8 and 17 recite, “obtaining, by the electronic device, … the search results” which further describes the concepts performed in the human mind including an observation, evaluation, judgment, and opinion, in step 2A prong one. The limitations as recited in dependent claims 9 and 18 recite, “receiving … displaying … receiving …” which further describes the concepts performed in the human mind including an observation, evaluation, judgment, and opinion, in step 2A prong one. Claim Rejections - 35 USC § 101 07-04-01 AIA 07-04 7. 35 U.S.C. 101 reads as follows: Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title. 8. Claims 19-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. 9. Claims 19-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter because claim 15 directs to “computer-readable storing computer” in which, when using the broadest reasonable interpretation would include non-statutory subject matter. That is, language such as “physical”, “tangible” and “storage” do not make an otherwise non-statutory computer-readable medium claim statutory, since a data signal per se is considered a physical and tangible medium that temporarily stores data (it’s a transitory storage medium, but it’s still a storage medium). Examiner’s Note 10. What is a display style of a search result? (According to Google): “ A display style is the visual format and layout a search engine or website uses to present search results ”. What is convergence policy from the server? (According to Google): “ A "convergence policy" from a server typically refers to a network configuration or virtualization directive used to dictate how servers, routers, or virtual machines synchronize data, manage security, or transition states after an outage .” Yu et al, US 20230100501, [Yu: Paragraph 27 (“The extractor module 204 extracts search results of a topic or subtopic of interest from various entities and relationships, such as search engines, mail groups, communities, chatbots, hotlines, and so on”)] [Yu: Paragraph 28 (“As described herein, the knowledge graph system 200 clusters the search results of an identified topic via a clustering algorithm into a hierarchical knowledge tree.”)] [Yu: Paragraph 35 (“The search results may be received from internal data sources, for example, at the information repository 104 and/or from external data sources such as search engines, social media communities, and so on, but not limited thereto”)] . Burnett et al, US 20200104401, [Burnett: Paragraph 142 (“Each respective ERP process may include an interface application installed at a computer of the external result provider that ensures proper communication between the search support system and the external result provider. The ERP processes 410, 412 generate appropriate search requests in the protocol and syntax of the respective virtual indices 414, 416, each of which corresponds to the search request received by the search head 210. Upon receiving search results from their corresponding virtual indices, the respective ERP process passes the result to the search head 210, which may return or display the results or a processed set of results based on the returned results to the respective client device”)] [Burnett: Paragraph 148 (“The streaming mode results (e.g., the machine data obtained from the external data source) are provided to the search head, which can then process the results data (e.g., break the machine data into events, timestamp it, filter it, etc.) and integrate the results data with the results data from other external data sources, and/or from data stores of the search head. The search head performs such processing and can immediately start returning interim (streaming mode) results to the user at the requesting client device; simultaneously, the search head is waiting for the ERP process to process the data it is retrieving from the external data source as a result of the concurrently executing reporting mode.”)] . Sachindran et al, US 20240086489, [Sachindran: Paragraph 75 (“a front end interface, such as search system front end 114, generates a first partial input. For example, a user types the first couple of letters of a search term into a search input box”, i.e., ‘a search word entered by a user’)] [Sachindran: Paragraph 75 (“At 304a, a pre-fetcher, such as pre-fetcher 140, gathers session context data and determines whether the first partial input satisfies a pre-fetch threshold. If the first partial input satisfies the pre-fetch threshold, the pre-fetcher formulates a query and sends it to a back end, such as search system back end”, i.e., ‘send .. a data query message to a server’)] [Sachindran: Paragraphs 11 and 16 (“directed to pre-fetching search result subsets and pre-constructing pages containing the pre-fetched search result subsets based on a partial search input that does not include an initiate search signal”)] [Sachindran: Paragraph 21 (“if the search system has grouped search results into different entity type clusters, the ranking model ranks the entity type clusters based on the probability that each cluster corresponds to the intent data. For example, if the user's intent is determined to be a job search, the ranking model ranks a results cluster that includes job postings higher than, for example, other results clusters that do not include job postings, so that the job postings results cluster will be pre-fetched first, before other results clusters.”)] [Sachindran: Paragraph 22 (“At the user's device, implementations construct a page containing the pre-fetched first, highest probability subset stored locally at the user's device, for example during a rendering phase of a page load. Examples of pages include search results pages, landing pages, and other web-based or mobile app-based pages that can be displayed on a user interface of a computing device.”)] [Sachindran: Paragraphs 25 and 44 (“For example, the search system clusters search results into result subsets based on clustering criteria, e.g., a domain or a vertical, such as entity type. Examples of entity types are categories that can be used to group search results, such as jobs, companies, people, articles, recommendations, and locations”)] [Sachindran: Paragraph 26 (“In implementations that use a blended search results page, in which search results from multiple different entity types are displayed, the page pre-construction includes organizing the result subsets so that the user sees the highest-probability result subset first and other, lower-probability result subsets are displayed following the highest probability result subset”)] [Sachindran: Paragraph 46 (“For example, ranking model 138 generates and outputs a ranking score for each search result in a result set, where the ranking score represents a probability of the search result corresponding to the ranking criterion, and sorts the result set based on the ranking scores. Machine learning implementations of ranking model 138 are trained on, for example, training data that includes combinations of intent data, search results, and ground-truth similarity scores”)] [Sachindran: Paragraph 69 (“Still before the user has provided initiate search signal 206, front end 114 pre-constructs a page 224 to display the high probability result subset 222. The page 224 is populated with result set 222 retrieved from pre-fetch data store 116 when the initiate search signal 206 is received. If the user's search session ends, or a period of time after which the page 224 is determined to be stale has elapsed, page 224 is not populated with result set 222. At 226, pre-fetcher 140 receives the initiate search signal 206, determines that a query confidence value based on a combination of the initiate search signal 206 and the intent data satisfies a query confidence threshold associated with the search query, and initiates loading of the page 224 including result set 222 into the user interface by search system front end”, i.e., ‘third search result’)] [Sachindran: Paragraphs 67-68 (“Search system back end 132 retrieves result subsets 220 that correspond to the search query from clusters 182 and provides the result subsets to ranking model 138. Ranking model 138 ranks the result subsets 220 based on the intent data 214 and provides a first highest probability result subset 222 to pre-fetcher 140”, i.e., ‘first search result’ and ‘second search result’)] . Liu et al, US 20150302066, [Liu: Paragraphs 32 and 65 (“the first search result and the second search result may be displayed in different areas”)] [Liu: Paragraph 26 (“if a user would like to keep a dog and focus on an intelligence quotient (IQ) of the dog, the search word input by the user may include “Samoyed IQ””, i.e., ‘a search word entered by a user’)] [Liu: Paragraphs 39 and 47 (“the search engine sends the search word to a server”)] [Liu: Paragraph 27 (“the search engine obtains a first search result and a second search result according to the search word, in which the first search result includes information of an entity corresponding to the search word”, i.e., ‘send .. a data query message to a server’)] [Liu: Paragraphs 69-70 (“the obtaining module 62 is configured to obtain information of an entity corresponding to the search word from a pre-established database and to determine the information of the entity corresponding to the search word as a first search result”, i.e., ‘third search result’)] . Claim Rejections - 35 USC § 102 07-06 AIA 15-10-15 11. In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status. 07-07-aia AIA 07-07 12. The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action: A person shall be entitled to a patent unless – 07-12-aia AIA (a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention. 07-15-03-aia AIA 13. Claim s 1-20 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Sachindran et al (US 20240086489) . Claim 1 : Sachindran suggests a display method, comprising: obtaining, by an electronic device, a search word enter by a user [Sachindran: Paragraph 75 (“a front end interface, such as search system front end 114, generates a first partial input. For example, a user types the first couple of letters of a search term into a search input box”, i.e., ‘a search word entered by a user’)] . Sachindran suggests sending, by the electronic device, a data query message to a server, the data query message comprising the search word [Sachindran: Paragraph 75 (“At 304a, a pre-fetcher, such as pre-fetcher 140, gathers session context data and determines whether the first partial input satisfies a pre-fetch threshold. If the first partial input satisfies the pre-fetch threshold, the pre-fetcher formulates a query and sends it to a back end, such as search system back end”, i.e., ‘send .. a data query message to a server’)] , and obtaining a first search result and a second search result from the server as a result of sending the data query message [Sachindran: Paragraphs 67-68 (“Search system back end 132 retrieves result subsets 220 that correspond to the search query from clusters 182 and provides the result subsets to ranking model 138. Ranking model 138 ranks the result subsets 220 based on the intent data 214 and provides a first highest probability result subset 222 to pre-fetcher 140”, i.e., ‘first search result’ and ‘second search result’)] . Sachindran suggests retrieving, by the electronic device based on the search word, from the data stored in the electronic device, a third search result [Sachindran: Paragraph 69 (“Still before the user has provided initiate search signal 206, front end 114 pre-constructs a page 224 to display the high probability result subset 222. The page 224 is populated with result set 222 retrieved from pre-fetch data store 116 when the initiate search signal 206 is received. If the user's search session ends, or a period of time after which the page 224 is determined to be stale has elapsed, page 224 is not populated with result set 222. At 226, pre-fetcher 140 receives the initiate search signal 206, determines that a query confidence value based on a combination of the initiate search signal 206 and the intent data satisfies a query confidence threshold associated with the search query, and initiates loading of the page 224 including result set 222 into the user interface by search system front end”, i.e., ‘third search result’)] , the first search result and the third search result belonging to a same type, and the second search result and the first search result belonging to different types [Sachindran: Paragraph 21 (“if the search system has grouped search results into different entity type clusters, the ranking model ranks the entity type clusters based on the probability that each cluster corresponds to the intent data. For example, if the user's intent is determined to be a job search, the ranking model ranks a results cluster that includes job postings higher than, for example, other results clusters that do not include job postings, so that the job postings results cluster will be pre-fetched first, before other results clusters.”)] [Sachindran: Paragraphs 25 and 44 (“For example, the search system clusters search results into result subsets based on clustering criteria, e.g., a domain or a vertical, such as entity type. Examples of entity types are categories that can be used to group search results, such as jobs, companies, people, articles, recommendations, and locations”)] . Sachindran suggests displaying, by the electronic device, a search result page, the search result page comprising a first area and a second area, the first area displaying the first search result and the third search result, and the second area displaying the second search result [Sachindran: Paragraph 22 (“At the user's device, implementations construct a page containing the pre-fetched first, highest probability subset stored locally at the user's device, for example during a rendering phase of a page load. Examples of pages include search results pages, landing pages, and other web-based or mobile app-based pages that can be displayed on a user interface of a computing device.”)] [Sachindran: Paragraph 26 (“In implementations that use a blended search results page, in which search results from multiple different entity types are displayed, the page pre-construction includes organizing the result subsets so that the user sees the highest-probability result subset first and other, lower-probability result subsets are displayed following the highest probability result subset”)] [Sachindran: Paragraph 46 (“For example, ranking model 138 generates and outputs a ranking score for each search result in a result set, where the ranking score represents a probability of the search result corresponding to the ranking criterion, and sorts the result set based on the ranking scores. Machine learning implementations of ranking model 138 are trained on, for example, training data that includes combinations of intent data, search results, and ground-truth similarity scores”)] . Claim 2 : Sachindran suggests arranging the first area before the second area when the electronic device is in a first time period, wherein one or both of a first search result weight of the first search result or a third search result weight of the third search result in the first time period are greater than a second search result weight of the second search result in the first time period [Sachindran: Paragraphs 25 and 46 (“Implementations determine the user's intent and use that intent data to determine the highest-ranking result subset to be pre-fetched first. For example, the search system clusters search results into result subsets based on clustering criteria, e.g., a domain or a vertical, such as entity type. Examples of entity types are categories that can be used to group search results, such as jobs, companies, people, articles, recommendations, and locations”)] [Sachindran: Paragraphs 61 and 69 (“search system front end 114 provides partial search inputs 202 and ranked typeahead suggestions 204b to pre-fetcher 140 if threshold conditions for pre-fetch, described in more detail below, are met. For example, front end 114 provides the typeahead suggestions 204b displayed in the top n positions to pre-fetcher 140, where n is a positive integer greater than zero. Front end 114 also gathers context data 212 associated with the partial search inputs 202. Context data 212 includes, for example, the top-ranked typeahead suggestions 204, query length, debouncing period, and/or portions of user activity data 208.”)] . Claim 3 : Sachindran suggests arranging the first search result before the third search result when the electronic device is in a first time period, wherein a first search result weight of the first search result in the first time period is greater than a third search result weight of the third search result in the first time period [Sachindran: Paragraphs 25 and 46 (“Implementations determine the user's intent and use that intent data to determine the highest-ranking result subset to be pre-fetched first. For example, the search system clusters search results into result subsets based on clustering criteria, e.g., a domain or a vertical, such as entity type. Examples of entity types are categories that can be used to group search results, such as jobs, companies, people, articles, recommendations, and locations”)] [Sachindran: Paragraphs 61 and 69 (“search system front end 114 provides partial search inputs 202 and ranked typeahead suggestions 204b to pre-fetcher 140 if threshold conditions for pre-fetch, described in more detail below, are met. For example, front end 114 provides the typeahead suggestions 204b displayed in the top n positions to pre-fetcher 140, where n is a positive integer greater than zero. Front end 114 also gathers context data 212 associated with the partial search inputs 202. Context data 212 includes, for example, the top-ranked typeahead suggestions 204, query length, debouncing period, and/or portions of user activity data 208.”)] [Sachindran: Paragraph 19 (“Examples of context data include typeahead suggestions, entity types associated with typeahead suggestions, the user's search history, the user's previous activity within the same online session or across previous sessions, the user's profile data (e.g., job title, geographic location, etc.), the number of characters in the partial search input (e.g., the number of characters already typed, also referred to as query length), click position of a typeahead suggestion or previously-presented search result (e.g., did the user click on the top-ranked typeahead suggestion or the nth-ranked typeahead suggestion, where n>1?), and the amount of time elapsed between user actions (e.g., how long did the user pause after entering an input, also referred to as a debouncing period)”)] . Claim 4 : Sachindran suggests wherein the method further comprises: arranging the first area before the second area when the electronic device is located at a first position, wherein one or both of a first search result weight of the first search result or a third search result weight of the third search result at the first position are greater than a second search result weight of the second search result at the first position [Sachindran: Paragraph 19 (“Examples of context data include typeahead suggestions, entity types associated with typeahead suggestions, the user's search history, the user's previous activity within the same online session or across previous sessions, the user's profile data (e.g., job title, geographic location, etc.), the number of characters in the partial search input (e.g., the number of characters already typed, also referred to as query length), click position of a typeahead suggestion or previously-presented search result (e.g., did the user click on the top-ranked typeahead suggestion or the nth-ranked typeahead suggestion, where n>1?), and the amount of time elapsed between user actions (e.g., how long did the user pause after entering an input, also referred to as a debouncing period)”)] [Sachindran: Paragraph 25 (“Examples of entity types are categories that can be used to group search results, such as jobs, companies, people, articles, recommendations, and locations. For instance, the search system groups search results into a jobs cluster that contains job postings, a people cluster that contains user profiles, and an article cluster that contains articles.”)] [Sachindran: Paragraph 61 (“For example, front end 114 provides the typeahead suggestions 204b displayed in the top n positions to pre-fetcher 140, where n is a positive integer greater than zero. Front end 114 also gathers context data 212 associated with the partial search inputs 202. Context data 212 includes, for example, the top-ranked typeahead suggestions 204, query length, debouncing period, and/or portions of user activity data 208. User activity data 208 is generated by user interface 112”)] . Claim 5 : Sachindran suggests wherein the method further comprises: arranging the first search result before the third search result when the electronic device is located at the first position, wherein a first search result weight of the first search result at the first position is greater than a third search result weight of the third search result at the first position [Sachindran: Paragraph 19 (“Examples of context data include typeahead suggestions, entity types associated with typeahead suggestions, the user's search history, the user's previous activity within the same online session or across previous sessions, the user's profile data (e.g., job title, geographic location, etc.), the number of characters in the partial search input (e.g., the number of characters already typed, also referred to as query length), click position of a typeahead suggestion or previously-presented search result (e.g., did the user click on the top-ranked typeahead suggestion or the nth-ranked typeahead suggestion, where n>1?), and the amount of time elapsed between user actions (e.g., how long did the user pause after entering an input, also referred to as a debouncing period)”)] [Sachindran: Paragraph 25 (“Examples of entity types are categories that can be used to group search results, such as jobs, companies, people, articles, recommendations, and locations. For instance, the search system groups search results into a jobs cluster that contains job postings, a people cluster that contains user profiles, and an article cluster that contains articles.”)] [Sachindran: Paragraph 61 (“For example, front end 114 provides the typeahead suggestions 204b displayed in the top n positions to pre-fetcher 140, where n is a positive integer greater than zero. Front end 114 also gathers context data 212 associated with the partial search inputs 202. Context data 212 includes, for example, the top-ranked typeahead suggestions 204, query length, debouncing period, and/or portions of user activity data 208. User activity data 208 is generated by user interface 112”)] . Claim 6 : Sachindran suggests wherein the method further comprises: the type of the first search result and the third search result is the first type, the first area is located before the second area, and a weight of the type corresponding to the first search result and the third search result is greater than a weight of a type corresponding to the second search result [Sachindran: Paragraphs 25 and 46 (“Implementations determine the user's intent and use that intent data to determine the highest-ranking result subset to be pre-fetched first. For example, the search system clusters search results into result subsets based on clustering criteria, e.g., a domain or a vertical, such as entity type. Examples of entity types are categories that can be used to group search results, such as jobs, companies, people, articles, recommendations, and locations”)] [Sachindran: Paragraphs 61 and 69 (“search system front end 114 provides partial search inputs 202 and ranked typeahead suggestions 204b to pre-fetcher 140 if threshold conditions for pre-fetch, described in more detail below, are met. For example, front end 114 provides the typeahead suggestions 204b displayed in the top n positions to pre-fetcher 140, where n is a positive integer greater than zero. Front end 114 also gathers context data 212 associated with the partial search inputs 202. Context data 212 includes, for example, the top-ranked typeahead suggestions 204, query length, debouncing period, and/or portions of user activity data 208.”)] [Sachindran: Paragraph 19 (“Examples of context data include typeahead suggestions, entity types associated with typeahead suggestions, the user's search history, the user's previous activity within the same online session or across previous sessions, the user's profile data (e.g., job title, geographic location, etc.), the number of characters in the partial search input (e.g., the number of characters already typed, also referred to as query length), click position of a typeahead suggestion or previously-presented search result (e.g., did the user click on the top-ranked typeahead suggestion or the nth-ranked typeahead suggestion, where n>1?), and the amount of time elapsed between user actions (e.g., how long did the user pause after entering an input, also referred to as a debouncing period)”)] . Claim 7 : Sachindran suggests wherein the first search result comprises a display style of the first search result, and the displaying, by the electronic device, the search result page comprises: displaying, by the electronic device, the search result page according to the display style of the first search result [Sachindran: Paragraph 19 (“the amount of available memory at the user's device, and the size of the display screen at the user's device”)] [Sachindran: Paragraph 22 (“for example during a rendering phase of a page load. Examples of pages include search results pages, landing pages, and other web-based or mobile app-based pages that can be displayed on a user interface of a computing device. Other examples of pages are audio-based versions of visual results pages, generated using, e.g., a text-to-speech (TTS) generator.”)] [Sachindran: Paragraph 26 (“For instance, in a small form-factor implementation such as a mobile device, the highest-probability result subset is displayed at the beginning of a scrollable list, i.e., above the fold, so that the user can see the highest-probability results quickly, without having to scroll through the entire list of results.”)] . Claim 8 : Sachindran suggests obtaining, by the electronic device, a device-cloud convergence policy from the server, wherein the device-cloud convergence policy indicates the electronic device converge the search results based on the types corresponding to the search results [Sachindran: Paragraph 25 (“The search back-end system then ranks the result subsets based on how well each result subset matches the user's intent data.”)] [Sachindran: Paragraph 29 (“a set of search results is already available for instant rendering on the client by streaming the pre-fetched subset from a back end of the search system into the pre-constructed results page. The pre-constructed pages for different entity types have different configurations”)] [Sachindran: Paragraph 36 (“Search system back end 132 uses a ranking model to rank, sort, filter, or group search results”)] [Sachindran: Paragraph 104 (“The machine can operate in the capacity of a server or a client machine in a client-server network environment, as a peer machine in a peer-to-peer (or distributed) network environment, or as a server or a client machine in a cloud computing infrastructure or environment.”)] [Sachindran: Paragraph 123 (“where pre-fetching the first subset of search results based on the search query includes: opening a persistent connection with a server; subscribing to an event log on the server that corresponds to the search query; listening for search results published by the server on the event log;”)] . Claim 9 : Sachindran suggests wherein before the receiving, by the electronic device, the search word entered by the user, the method further comprises: receiving, by the electronic device, a first operation; in response to the first operation [Sachindran: Paragraph 12 (“An example of a user starting to enter a search term is a user typing the first few characters of a word into a text input box of a search interface. Examples of actions a user might take to explicitly initiate a search include issuing an enter command, a selection of a search element, a click, or a selection of an auto-generated search suggestion, also referred to as a typeahead suggestion”)] [Sachindran: Paragraph 60 (“a user operating a user system 110 provides one or more partial search inputs 202 to search system front end 114 via a search input box of user interface 112. Search system front end 114 receives one or more typeahead suggestions 204a that have been generated and ranked by, for example, a typeahead service of search system back end”)] , displaying, by the electronic device, a search box and sending a policy request message to the server, wherein the search box is used to enter the search word, and the policy request message indicates the server send a device-cloud convergence policy to the electronic device; and receiving, by the electronic device, the device-cloud convergence policy, wherein the device- cloud convergence policy indicates the electronic device converge the search results based on the types corresponding to the search results [Sachindran: Paragraph 25 (“The search back-end system then ranks the result subsets based on how well each result subset matches the user's intent data.”)] [Sachindran: Paragraph 29 (“a set of search results is already available for instant rendering on the client by streaming the pre-fetched subset from a back end of the search system into the pre-constructed results page. The pre-constructed pages for different entity types have different configurations”)] [Sachindran: Paragraph 36 (“Search system back end 132 uses a ranking model to rank, sort, filter, or group search results”)] [Sachindran: Paragraph 104 (“The machine can operate in the capacity of a server or a client machine in a client-server network environment, as a peer machine in a peer-to-peer (or distributed) network environment, or as a server or a client machine in a cloud computing infrastructure or environment.”)] [Sachindran: Paragraph 123 (“where pre-fetching the first subset of search results based on the search query includes: opening a persistent connection with a server; subscribing to an event log on the server that corresponds to the search query; listening for search results published by the server on the event log;”)] . Claim 10 : Claim 10 is essentially the same as claim 1 except that it sets forth the claimed invention as a device rather than a method and rejected under the same reasons as applied above. Claim 11 : Claim 11 is essentially the same as claim 2 except that it sets forth the claimed invention as a device rather than a method and rejected under the same reasons as applied above. Claim 12 : Claim 12 is essentially the same as claim 3 except that it sets forth the claimed invention as a device rather than a method and rejected under the same reasons as applied above. Claim 13 : Claim 13 is essentially the same as claim 4 except that it sets forth the claimed invention as a device rather than a method and rejected under the same reasons as applied above. Claim 14 : Claim 14 is essentially the same as claim 5 except that it sets forth the claimed invention as a device rather than a method and rejected under the same reasons as applied above. Claim 15 : Claim 15 is essentially the same as claim 6 except that it sets forth the claimed invention as a device rather than a method and rejected under the same reasons as applied above. Claim 16 : Claim 16 is essentially the same as claim 7 except that it sets forth the claimed invention as a device rather than a method and rejected under the same reasons as applied above. Claim 17 : Claim 17 is essentially the same as claim 8 except that it sets forth the claimed invention as a device rather than a method and rejected under the same reasons as applied above. Claim 18 : Claim 18 is essentially the same as claim 9 except that it sets forth the claimed invention as a device rather than a method and rejected under the same reasons as applied above. Claim 19 : Claim 19 is essentially the same as claim 1 except that it sets forth the claimed invention as a program product rather than a method and rejected under the same reasons as applied above. Claim 20 : Claim 20 is essentially the same as claim 2 except that it sets forth the claimed invention as a program product rather than a method and rejected under the same reasons as applied above . Claim Rejections - 35 USC § 102 07-06 AIA 15-10-15 14. In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status. 07-07-aia AIA 07-07 15. The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action: A person shall be entitled to a patent unless – 07-08-aia AIA (a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale or otherwise available to the public before the effective filing date of the claimed invention. 07-15-03-aia AIA 16. Claim s 1, 10 and 19 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Liu et al (US 20150302066) . Claim 1 : Liu suggests a display method, comprising: obtaining, by an electronic device, a search word enter by a user [Liu: Paragraph 26 (“if a user would like to keep a dog and focus on an intelligence quotient (IQ) of the dog, the search word input by the user may include “Samoyed IQ””, i.e., ‘a search word entered by a user’)] . Liu suggests sending, by the electronic device, a data query message to a server [Liu: Paragraphs 39 and 47 (“the search engine sends the search word to a server”)] , the data query message comprising the search word [Liu: Paragraph 27 (“the search engine obtains a first search result and a second search result according to the search word, in which the first search result includes information of an entity corresponding to the search word”, i.e., ‘send .. a data query message to a server’)] , and obtaining a first search result and a second search result from the server as a result of sending the data query message [Liu: Paragraphs 27, 41 and 42043 (“the search engine obtains a first search result and a second search result according to the search word, in which the first search result includes information of an entity corresponding to the search word”, i.e., ‘send .. a data query message to a server’)] . Liu suggests retrieving, by the electronic device based on the search word, from the data stored in the electronic device, a third search result [Liu: Paragraphs 41 and 69-70 (“the obtaining module 62 is configured to obtain information of an entity corresponding to the search word from a pre-established database and to determine the information of the entity corresponding to the search word as a first search result”, i.e., ‘third search result’)] , the first search result and the third search result belonging to a same type, and the second search result and the first search result belonging to different types [Liu: Paragraphs 41 and 69-70 (“the obtaining module 62 is configured to obtain information of an entity corresponding to the search word from a pre-established database and to determine the information of the entity corresponding to the search word as a first search result”, i.e., ‘third search result’)] . Liu suggests displaying, by the electronic device, a search result page, the search result page comprising a first area and a second area, the first area displaying the first search result and the third search result, and the second area displaying the second search result [Liu: Paragraph 45 (“For example, a field to which Samoyed belongs may be further obtained according to entity information of Samoyed, i.e. Husky is one species of dog. In addition, IQ is one attribution of a single pet entity, which is a horizontal attribution of an entity in the pet field. In order to display more information to the user, IQ attribution information that the user would like to know may be extended horizontally, and therefore IQ attribution data of all dog species may be obtained. The picture information and title information of all dog entities may be obtained, and may be integrated and sequenced according to IQ, thus showing the user with systematic and complete information, such as structured information of IQ rank of all dog species. In this way, a searching experience of the user may be improved”)] [Liu: Paragraph 50 (“in addition to displaying the first search result and the second search result, a sequencing basis may be displayed. For example, as shown in FIG. 3, in addition to the first search result and the second search result, a rank feature, a dog IQ ranking standard and the like are shown. In some embodiments, a uniform resource locator (URL) link indicating a source of the rank basis may be stored in the attribution of the entity in the data base, thus facilitating the view of the user. IQ of dogs have a rank, for example, dogs ranked in top 10 of the IQ rank may have certain features in memory and obedience, and these features may be represented by ranking features. In some embodiments, related recommendations may be shown, such as IQ rank of dogs, dog species of the all, etc”)] . Claim 10 : Claim 10 is essentially the same as claim 1 except that it sets forth the claimed invention as a device rather than a method and rejected under the same reasons as applied above. Claim 19 : Claim 19 is essentially the same as claim 1 except that it sets forth the claimed invention as a program product rather than a method and rejected under the same reasons as applied above. 17. Any inquiry concerning this communication or earlier communications from the examiner should be directed to [Hung D. Le], whose telephone number is [571-270-1404]. The examiner can normally be communicated on [Monday to Friday: 9:00 A.M. to 5:00 P.M.]. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Apu Mofiz can be reached on [571-272-4080]. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only. For more information about the PAIR system, see http://pair-direct.uspto.gov. Should you have questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative or access to the automated information system, contact [800-786-9199 (IN USA OR CANADA) or 571-272-1000]. Hung Le 05/21/2026 /HUNG D LE/Primary Examiner, Art Unit 2161 Application/Control Number: 19/255,837 Page 2 Art Unit: 2161 Application/Control Number: 19/255,837 Page 3 Art Unit: 2161 Application/Control Number: 19/255,837 Page 4 Art Unit: 2161 Application/Control Number: 19/255,837 Page 5 Art Unit: 2161 Application/Control Number: 19/255,837 Page 6 Art Unit: 2161 Application/Control Number: 19/255,837 Page 7 Art Unit: 2161 Application/Control Number: 19/255,837 Page 8 Art Unit: 2161 Application/Control Number: 19/255,837 Page 9 Art Unit: 2161 Application/Control Number: 19/255,837 Page 10 Art Unit: 2161 Application/Control Number: 19/255,837 Page 11 Art Unit: 2161 Application/Control Number: 19/255,837 Page 12 Art Unit: 2161 Application/Control Number: 19/255,837 Page 13 Art Unit: 2161 Application/Control Number: 19/255,837 Page 14 Art Unit: 2161 Application/Control Number: 19/255,837 Page 15 Art Unit: 2161 Application/Control Number: 19/255,837 Page 16 Art Unit: 2161 Application/Control Number: 19/255,837 Page 17 Art Unit: 2161 Application/Control Number: 19/255,837 Page 18 Art Unit: 2161 Application/Control Number: 19/255,837 Page 19 Art Unit: 2161 Application/Control Number: 19/255,837 Page 20 Art Unit: 2161 Application/Control Number: 19/255,837 Page 21 Art Unit: 2161 Application/Control Number: 19/255,837 Page 22 Art Unit: 2161 Application/Control Number: 19/255,837 Page 23 Art Unit: 2161 Application/Control Number: 19/255,837 Page 24 Art Unit: 2161
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