Prosecution Insights
Last updated: May 29, 2026
Application No. 19/065,789

CRAWL ALGORITHM

Final Rejection §103
Filed
Feb 27, 2025
Priority
Sep 29, 2022 — provisional 63/377,710 +1 more
Examiner
HALM, KWEKU WILLIAM
Art Unit
2166
Tech Center
2100 — Computer Architecture & Software
Assignee
Google LLC
OA Round
2 (Final)
80%
Grant Probability
Favorable
3-4
OA Rounds
1y 3m
Est. Remaining
93%
With Interview

Examiner Intelligence

Grants 80% — above average
80%
Career Allowance Rate
202 granted / 252 resolved
+25.2% vs TC avg
Moderate +13% lift
Without
With
+12.6%
Interview Lift
resolved cases with interview
Typical timeline
2y 6m
Avg Prosecution
33 currently pending
Career history
297
Total Applications
across all art units

Statute-Specific Performance

§101
0.7%
-39.3% vs TC avg
§103
91.1%
+51.1% vs TC avg
§102
4.3%
-35.7% vs TC avg
§112
1.0%
-39.0% vs TC avg
Black line = Tech Center average estimate • Based on career data from 252 resolved cases

Office Action

§103
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 . Response to Amendment 2. The Amendment filed on March 16th 2026 has been entered. Claims 1, 3, 7 – 11, 13 and 18 - 20 have been amended and claims 5, 6, 15 and 16 have been cancelled. Claims 1 – 4, 7 – 14 and 17 - 20 are currently pending. Response to Arguments Double Patenting 3. Applicant's arguments, see Remarks pp. 7 of 2, filed March 16th 2026, with respect to the rejections of claims 1-20 under Obvious -type Double Patenting have been fully considered. The Terminal Disclaimer as filed is duly noted. Applicant argues that the amendments find support in specific paragraphs Examiner respectfully agrees Upon further consideration new grounds of rejection have been necessitated due to Applicant's amendments and are made in view of Shivaswamy et al., (United States Patent Publication Number 2015/0161257) hereinafter Shivaswamy and Hellstrom et al. (United States Patent Number 2009/0204610 ), hereinafter referred to as Hellstrom. Claim Rejections – 35 U.S.C. §103 4. 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, 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 filing 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. 5. The factual inquiries set forth in Graham v John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows: a. Determining the scope and contents of the prior art b. Ascertaining the differences between the prior art and the claims at issue c. Resolving the level of ordinary skill in the pertinent art d. Considering objective evidence present in the application indicating obviousness or nonobviousness Claims 1 – 3, 7 – 13 and 17 - 20 are rejected under 35 U.S.C. 103 as being unpatentable over Shivaswamy et al., (United States Patent Publication Number 2015/0161257) hereinafter Shivaswamy, in view of Hellstrom et al. (United States Patent Number 2009/0204610 ), hereinafter referred to as Hellstrom. Regarding claim 1 Shivaswamy teaches a computer-implemented method (Fig. 6 method [0012]) comprising: obtaining a plurality of data sources for a crawler to process; (fetch URL crawl requests from various sources, as illustrated in FIG. 3. Source 1, Source 2 and Source 3 [0026] – [0027]) dividing (distribute [0036]) such as “dividing” the plurality of data sources (FIG. 3. Source 1, Source 2 and Source 3 [0026] – [0027]) into a plurality of shards (Fig. 3 Queue 1, (e.g. SLA), Queue 2 (e.g. NonSLA) and Queue 3 [0036]) such as “plurality of shards” determining an available resource capacity for the crawler; (According to various exemplary embodiments, the capacity analyzer module 206 is configured to estimate a capacity of a web crawler at a given time period ( e.g., a given hour of the day such as 4 PM-5 PM) [0033])and for each respective shard of the plurality of shards: (Fig. 3 Queue 1, (e.g. SLA), Queue 2 (e.g. NonSLA) and Queue 3 [0036]) such as “plurality of shards” receiving an update indicator (Fig. 4A, frequency for crawling (e.g., repeated every 8 hours, repeat daily, etc.). [0029]) such as “update indicator” associated with the respective shard; (each URL request in the request pool 310 may be associated with a priority level, and SLA-time, and a frequency.) [0032]) determining a respective crawl priority for the respective shard based on an update indicator; (each URL request in the request pool 310 may be associated with a priority level, and SLA-time, and a frequency.) [0032])determining that the respective crawl priority (priority level [0029]) satisfies a priority threshold; (preconfigured max threshold [0035]) and responsive to determining that the respective crawl priority (priority level [0029]) satisfies the priority threshold, (preconfigured max threshold [0035]) utilizing the available resource capacity (estimated capacity of crawler [0017], [0033]) Shivaswamy does not fully disclose updating data associated with each data source of the respective shard in a cache memory Hellstrom teaches updating data associated with each data source of the respective shard in a cache memory (If the URL is found in the cache, e.g., by the cache manager at 288, the content is located on the file system 122, the original HTTP transactional meta-data is restored and the content is delivered in response to the HTTP request [[0124]) It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Shivaswamy to incorporate the teachings of Hellstrom whereby updating data associated with each data source of the respective shard in a cache memory. By doing so dynamically updating the results of the mining process, e.g., as the information is captured, the user can thus interact with the results for exploration and analysis, even while the mining process continues to iterate, Hellstrom [0063] Claim 11 corresponds to claim 1 and is rejected accordingly Regarding claim 2 Shivaswamy in view of Hellstrom teaches the computer-implemented method of claim 1, Shivaswamy as modified further teaches wherein the plurality of data sources (FIG. 3. Source 1, Source 2 and Source 3 [0026] – [0027]) comprises a plurality of web pages. (In operation 801 in FIG. 8, the fetching module 202 fetches a plurality of URL crawl requests from one or more data sources, each of the URL crawl requests being associated with use case information [0049]) Claim 12 corresponds to claim 2 and is rejected accordingly Regarding claim 3 Shivaswamy in view of Hellstrom teaches the computer-implemented method of claim 1, Shivaswamy as modified further teaches wherein the respective crawl priority indicates (a priority level associated with the URL crawl request (e.g., low, medium, high, or Pl, P2, P3, etc [0029])a priority for the respective shard to be refreshed (a service level agreement (SLA) time or deadline for the crawling to be completed by (e.g., this URL needs to be crawled within 3 hour or 6 hours), and a frequency for crawling (e.g., repeated every 8 hours, repeat daily, etc.). [0029]) Claim 13 corresponds to claim 3 and is rejected accordingly Regarding claim 7 Shivaswamy in view of Hellstrom teaches the computer-implemented method of claim 1, Shivaswamy as modified further teaches wherein each respective shard (Fig. 3 Queue 1, (e.g. SLA), Queue 2 (e.g. NonSLA) and Queue 3 [0036]) such as “plurality of shards” is assigned a respective resource capacity comprising a portion (Fig. 7 (705) Assign a portion of the preconfigured daily estimate to the given time period [0048]) of the available resource capacity. (estimated capacity of crawler [0017], [0033]) Claim 17 corresponds to claim 7 and is rejected accordingly Regarding claim 8 Shivaswamy in view of Hellstrom teaches the computer-implemented method of claim 1, Shivaswamy as modified further teaches wherein the operations further comprise, for each respective shard of the plurality of shards: (Fig. 3 Queue 1, (e.g. SLA), Queue 2 (e.g. NonSLA) and Queue 3 [0036]) such as “plurality of shards” estimating an update time (a service level agreement (SLA) time or deadline for the crawling to be completed by (e.g., this URL needs to be crawled within 3 hour or 6 hours), and a frequency for crawling (e.g., repeated every 8 hours, repeat daily, etc.). For [0029]) for the respective crawl priority (priority level [0029])of the respective shard; and updating (a service level agreement (SLA) time or deadline for the crawling to be completed by (e.g., this URL needs to be crawled within 3 hour or 6 hours), and a frequency for crawling (e.g., repeated every 8 hours, repeat daily, etc.). For [0029]) the respective crawl priority (priority level [0029])of the respective shard(Fig. 3 Queue 1, (e.g. SLA), Queue 2 (e.g. NonSLA) and Queue 3 [0036]) such as “plurality of shards” at the estimated update time. ((e.g., repeated every 8 hours, repeat daily, etc.). [0029]) Claim 18 corresponds to claim 8 and is rejected accordingly Regarding claim 9 Shivaswamy in view of Hellstrom teaches the computer-implemented method of claim 1, Shivaswamy as modified further teaches wherein the operations further comprise, for each respective shard of the plurality of shards, (Fig. 3 Queue 1, (e.g. SLA), Queue 2 (e.g. NonSLA) and Queue 3 [0036]) such as “plurality of shards” updating (a service level agreement (SLA) time or deadline for the crawling to be completed by (e.g., this URL needs to be crawled within 3 hour or 6 hours), and a frequency for crawling [0029]) the respective crawl priority (priority level [0029])for the respective shard at every time step of a discrete time interval. (e.g., repeated every 8 hours, repeat daily, etc.). For [0029]) such as “discrete time interval” Claim 19 corresponds to claim 9 and is rejected accordingly Regarding claim 10 Shivaswamy in view of Hellstrom teaches the computer-implemented method of claim 1, Shivaswamy as modified further teaches wherein the respective crawl priority (priority level [0029])is based on a change indicating signal (the prioritization module 204 may prioritize each URL crawl request based on each of the aforementioned factors, either alone or in combination with other factors, in order to generate a prioritized request list 320 [0032]) received from at least one data source (FIG. 3. Source 1, Source 2 and Source 3 [0026] – [0027]) of the respective shard. (Fig. 3 Queue 1, (e.g. SLA), Queue 2 (e.g. NonSLA) and Queue 3 [0036]) Claim 20 corresponds to claim 10 and is rejected accordingly Claims 4 and 14 are rejected under 35 U.S.C. 103 as being unpatentable over Shivaswamy et al., (United States Patent Publication Number 2015/0161257) hereinafter Shivaswamy, in view of Hellstrom et al. (United States Patent Number 2009/0204610 ), hereinafter referred to as Hellstrom and in further view of Li (United States Patent Publication Number 20170147691) hereinafter Li Regarding claim 4 Shivaswamy in view of Hellstrom teaches the computer-implemented method of claim 1, Shivaswamy as modified does not fully disclose wherein determining the respective crawl priority comprises using a machine learning engine to determine the respective crawl priority. Li teaches wherein determining the respective crawl priority (importance level [0039]) such as “respective crawl priority” comprises using a machine learning engine to determine the respective crawl priority (the machine learning model to obtain the importance values of the word segments. [0039]) It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Shivaswamy in view of Hellstrom to incorporate the teachings of Li wherein determining the respective crawl priority comprises using a machine learning engine to determine the respective crawl priority. By doing so Li The machine learning model can calculate an importance value of the word segment according to the feature value of the word segment. As such, importance value of each word segment in the candidate topic sentences can be obtained. [0050] Claim 14 corresponds to claim 4 and is rejected accordingly Conclusion 6. Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a). A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any extension fee pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the date of this final action. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. 7. Any inquiry concerning this communication or earlier communications from the examiner should be directed to Kweku Halm whose telephone number is (469)295- 9144. The examiner can normally be reached on 9:00AM - 5:30PM Mon - Thur. If attempts to reach the examiner by telephone are unsuccessful, the examiner's supervisor, Sanjiv Shah can be reached on (571) 272 - 4098. 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, call 800-786- 9199 (IN USA OR CANADA) or 571-272-1000. /KWEKU WILLIAM HALM/Examiner, Art Unit 2166 /SANJIV SHAH/Supervisory Patent Examiner, Art Unit 2166
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Prosecution Timeline

Feb 27, 2025
Application Filed
Dec 31, 2025
Non-Final Rejection mailed — §103
Mar 16, 2026
Response Filed
Apr 29, 2026
Final Rejection mailed — §103 (current)

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Prosecution Projections

3-4
Expected OA Rounds
80%
Grant Probability
93%
With Interview (+12.6%)
2y 6m (~1y 3m remaining)
Median Time to Grant
Moderate
PTA Risk
Based on 252 resolved cases by this examiner. Grant probability derived from career allowance rate.

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