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 .
Introductory Remarks
In response to communications filed on 26 March 2026, claims 1, 3, 10, 12, and 17 are amended per Applicant's request. No claims were cancelled. No claims were withdrawn. No new claims were added. Therefore, claims 1-20 are presently pending in the application, of which claims 1, 10, and 17 are presented in independent form.
The previously raised 103 rejection of the pending claims is withdrawn in view of the amendments to the claims. A new ground(s) of rejection has been issued.
Response to Arguments
Applicant’s arguments filed 26 March 2026 with respect to the rejection of the claims under 35 U.S.C. 103 have been fully considered but are moot because the arguments do not apply to the new references (and new combination of references) being used in the current rejection.
Claim Objections
Claims 2, 11, and 18 are objected to because of the following informalities: the claims recite “the set of classifications”. This should be “the set of classification[[s]] values”, to be consistent with their respective independent claims. Appropriate correction is required.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-20 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claims 1, 10, and 17 further recite “ranking…the subset of headnotes, wherein the ranking considers at least: the set of headnote scores; the set of classification values, and second metadata associated with the subset of headnotes, wherein the second metadata is different from the first metadata”.
It is unclear whether the “associated with the subset of headnotes” pertains to all of the “set of headnote scores”, “set of classification values”, and “second metadata”, or only pertains to the “second metadata” (as the set of classification values already was for a “subset of headnotes”, and the language “associated with the subset of headnotes”, appears in the line in which “second metadata” appears).
However, if the “subset of headnotes” was meant for the “second metadata”, then this would result in a difference in set sizes for the “set of headnote scores” (which was calculated for a plurality of headnotes”), and the set of classification values.
Thus, the claim language seems to allow for the possibility that for the ranking, every headnote score in the entire plurality of headnotes is considered, whereas the classification value was only for at least a subset of the headnotes. This means that the size of the set of data being considered for ranking is different with respect to the “headnote scores” and the “classification values” (resulting in, e.g., some headnote scores having an associated null/nonexistent classification value, as a classification value was never calculated for it). It is unclear whether Applicant intended for the set sizes of “headnote scores” and “classification values” to be different (in which case, it is unclear how this would operate within the context of the claimed invention with some missing classification values, which would make it impossible for the claimed ranking to be based at least on both headnote scores and null/nonexistent classification values, as the latter does not exist).
For purposes of examination, the interpretation that the system performs ranking on the subset of headnotes based on the headnote scores “associated with the subset of headnotes”, has been taken.
The rest of the dependent claims are rejected for at least by virtue of their dependency on their respective independent claims, and for failing to cure the deficiencies of their respective independent claims.
Claims 2-3, 11-12, and 18 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claims 2, 11, and 18 recite “wherein the subset of headnotes are ranked based at least in part on a set of ranking features”.
However, independent claims 1, 10, and 17, which claims 2, 11, and 18 depend upon, already recite “wherein the ranking considers at least: … second metadata associated with the subset of headnotes”.
Firstly, claims 2, 11, and 18 appear to replace the language of their respective independent claims in that it does not state that the ranking is “further” or “additionally” based at least in part on. Thus, it is unclear whether claims 2, 11, and 18 were meant to supplement or override the ranking features of their respective independent claims.
Secondly, it appears that the independent claims’ disclosure of metadata corresponds to the elements being claimed in claims 2, 11, and 18. See, e.g., Specification, [0021], where “metadata for a headnote may include or correspond to a topic, a narrow legal issue, a legal issue outcome, a narrow legal issue as paired with a legal issue outcome, one or more material facts, one or more fact patterns, a level of concreteness (e.g., concrete or abstract), one or more causes of action, one or more party types, one or more governing laws (e.g., a state law, a federal law, an administrative rule, and so on), one or more motion types (e.g., motion to dismiss, motion for summary judgment, motion to stay, motion for judgment as a matter of law, and so on), one or more motion outcomes, one or more motion types as paired with motion outcomes, one or more areas of law (e.g., contracts, torts, product liability, criminal law, cybersecurity, or any number of additional areas of law), a headnote number, or some combination thereof.”
However, as seen, claims 2, 11, and 18 refer to these as “ranking features”, which appears to mean the same element as “metadata”. However, the relationship between the ranking features of claims 2, 11, and 18 is unable to be reconciled with respect to the “second metadata” of claims 1, 10, and 17, for the reasons of (1) different language is used (the dependent claims use “ranking features”, whereas the independent claims use “metadata”); and (2) following from “metadata” being the claimed “ranking features”, the dependent claims do not indicate they are an extension to the independent claims, but rather appear to replace the independent claims’ features; however, it is unclear whether this is the case.
For purposes of examination, the interpretation that “metadata” corresponds to “ranking features”, and that the “ranking features” comprises the list of claims 2, 11, and 18, has been taken.
Claims 3 and 12 are rejected for at least by virtue of their dependency on their respective parent claims, and for failing to cure the deficiencies of their respective parent claims.
Claims 6 and 14 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
The claims recite “calculating a headnote score for each headnote of the plurality of headnotes based on the similarity, wherein the set of headnote scores includes the headnote score calculated for each headnote of the plurality of headnotes”. This is substantially similar to the independent claims’ language of “generating…a set of headnote scores for a plurality of headnotes, wherein individual headnote scores of the set of headnote scores correspond to a particular headnote of the plurality of headnotes and are based on a similarity comparison of text of a query and to text of the particular headnote” (note that the first portion of claims 6 and 14, in which the similarity is determined, is implied by the independent claims’ use of similarity for determining headnote scores). Thus, there seems to be, at the least, a lack of antecedent basis issue for the limitations of claims 6 and 14, and the relative differences/overlap in scope with the independent claims cannot be clearly ascertained.
For purposes of examination, the interpretation that claims 6 and 14 recipe the same scope as the independent claims has been taken.
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, 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.
Claims 1-2, 5-6, 10-11, 13-14, and 17-19 are rejected under 35 U.S.C. 103 as being unpatentable over Liu et al. (“Liu”) (US 2018/0276305 A1), in view of Kovacs et al. (“Kovacs”) (US 2019/0108276 A1).
Regarding claim 1: Liu teaches A method, comprising:
generating, by one or more processors, a set of headnote scores for a plurality of headnotes, wherein individual headnote scores of the set of headnote scores correspond to a particular headnote of the plurality of headnotes and are based on a similarity comparison of text of a query and to text of the particular headnote (Liu, [0098-0101], where a user uploads an input document or portion of input text. The system analyzes the text of the input, including citations and pinpoint citations, or “pincites”, which yield research recommendations. See Liu, [0112], where (potentially) relevant headnotes are identified for a given citation or pincite, i.e., from text of the input (Liu, [0107-0108]) (i.e., “text of a query”), and the headnotes may be scored based on comparing the text of the headnote to the context of the citation, by calculating a text similarity score. See Liu, [0141] and [0189], where the disclosed processes may be implemented by one or more processors);
applying, by the one or more processors, [calculations] to a dataset to generate a set of classification values, wherein the dataset comprises the query, at least a subset of headnotes of the plurality of headnotes, and first metadata of the subset of headnotes, wherein the set of classification values comprises individual classification values for individual headnotes of the subset of headnotes (Liu, [0105-0106], where each headnote is enriched with metadata such as topic and key-number assignments (i.e., “first metadata of the subset of headnotes”). See Liu, [0112-0113], where the topic (or key number) of the headnote may be compared to the topics of other headnotes cited in the input, and a topic similarity score of the headnote may be calculated based on the overlap of the topics. See Liu, [0125-0126], where several related scores may be computed for each headnote against the issue segment from the input (brief) (i.e., “the query”), including a cited-keyNumber score and cited-topic score (i.e., “individual classification values for individual headnotes”)) …;
ranking, by the one or more processors, the subset of headnotes, to produce a ranked set of headnotes quantifying a relevance of the individual headnotes to the query, and the ranking considers at least: the set of headnote scores; the set of classification values, and second metadata associated with the subset of headnotes, wherein the second metadata is different from the first metadata (Liu, [0112-0134], where the aforementioned scores are aggregated and used to compute an aggregated ranking for a recommended citation (Liu, [0134]), which in turn are used to output a list of ranked citations (Liu, [0134]; see also, e.g., Liu, [0073]). These one or more metrics (including relevance scores; see Liu, [0125]) are combined into a single score (Liu, [0113]) by taking into account, e.g., the text similarity score calculated for the headnote (Liu, [0113] and [0125]), the topic similarity score of the headnote / cited-topic score and cited-keyNumber score (i.e., “set of classification values”) (Liu, [0113] and [0125-0126]), whether the headnote comes from a pincite with page numbers and/or whether the headnote comes from a pincite whose context includes exact quotes (Liu, [0113]), jurisdiction score (Liu, [0128-0130], authority score (Liu, [0131]), recency score (Liu, [0132]), etc. (all of these scores, with the exception of those indicated as corresponding to the “set of classification values” above, corresponding to “second metadata associated with the subset of headnotes, wherein the second metadata is different from the first metadata”). See Liu, [0054], where the system identifies such information relevant to the user’s research and returns it to the user (i.e., thus, each of these aforementioned scores “quantifying a relevance of the individual headnotes to the query”)); and
outputting, by the one or more processors, at a graphical user interface (GUI), a highest ranked headnote based on the ranked set of headnotes as part of a display of at least a portion of the ranked set of headnotes (Liu, [0134], where the SVM ranker outputs a ranked list of results that are presented to the user, including, e.g., a top number of results (i.e., the top number including “a highest ranked headnote based on the ranked set of headnotes”). See, e.g., Liu, [0091], [0164], and [FIG. 13], where a user interface is used to provide a means for accessing and displaying information graphically to users, including recommendation results that are returned to the user via a user interface).
Liu does not appear to explicitly state that a classifier is applied to generate the calculations; [and] wherein the classifier is a machine learning model that is trained using a training dataset comprising query features and headnote features
Kovacs teaches a classifier that is applied to generate the calculations; [and] wherein the classifier is a machine learning model that is trained using a training dataset comprising query features and headnote features (Kovacs, [0108], where the trained classifier component is used to classify selected documents by relevance using their document features, where classified documents are then ordered based on the relevance values produced by the classifier component. See Kovacs, [0086], where the classifier component is trained with training features generated based on query features and a set of document features (see, e.g., Kovacs, [0076-0084] for more detail), after which documents may be classified. See, e.g., Kovacs, [0083-0084], where the classifier component is trained to learn relevant and non-relevant features corresponding to, e.g., queries, from the training dataset, implying that the disclosed classifier is a “machine learning model” as claimed. See Liu above with respect to the document pertaining to a “headnote”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have combined the teachings of Liu and Kovacs (hereinafter “Liu as modified”) by applying a classifier in order to further improve the relevance of the results set with respect to the text-based content searched (see, e.g., Kovacs, [0121]).
Regarding claim 2: Liu as modified teaches The method of claim 1, wherein the subset of headnotes are ranked based at least in part on a set of ranking features, wherein the set of ranking features comprises the set of headnote scores, the set of classifications, a narrow legal issue feature, an outcome feature, a material fact feature, a fact pattern feature, a cause of action feature, a concreteness metric, a party type feature, a governing law feature, a motion type feature, an area of law feature, a count of matching attributes, a count of matching terms from material facts, a headnote number, a grade, or a combination thereof (Liu, [0122], where the ranking module extracts heterogeneous metadata associated with the recommendation candidates, transforms those metadata into feature vectors, feeds a trained learning-to-rank model with those feature vectors, and outputs a list of ranked authorities (documents) (Liu, [0052]). See Liu, [0052], where these candidates are ranked according to, e.g., how relevant they are to a legal issue in the input, how relevant their jurisdiction is to an input issue, and/or how authoritative and/or recent they are. See also, e.g., Liu, [0124-0133] with respect to the list of various features that are used by the SVM ranker to evaluate and rank the documents including, e.g., a headnote document’s keyNumber, issues, topics, etc.).
Regarding claim 5: Liu as modified teaches The method of claim 2, further comprising, prior to generating the set of headnote scores, receiving one or more first inputs identifying one or more attributes of interest, wherein the query is generated based on the one or more first inputs, and wherein the one or more first inputs are received via selectable elements of the graphical user interface (Liu, [0097-0101] and [FIG. 19], where the system analyzes an input draft document or portion of a document (i.e., “receiving one or more first inputs identifying one or more attributes of interest”), which includes citations, a document structure or formatting, to identify issues that may be relevant to the input. The input text may also be analyzed to extract citations. Based on the issues identified in the input (i.e., “wherein the query is generated based on the one or more inputs”), documents are searched for, ranked, and presented to the user to assist the user in further drafting of the input document. A user interface allows a user to upload an input document or portion of input text via, e.g., dragging and dropping a document or selecting the “Browse” button in the graphical user interface).
Regarding claim 6: Liu as modified teaches The method of claim 1, wherein generating the set of headnote scores comprises:
determining a similarity between the query and each headnote of the plurality of headnotes; and calculating a headnote score for each headnote of the plurality of headnotes based on the similarity, wherein the set of headnote scores includes the headnote score calculated for each headnote of the plurality of headnotes (Liu, [0098-0101], where a user uploads an input document or portion of input text. The system analyzes the text of the input, including citations and pinpoint citations, or “pincites”, which yield research recommendations. See Liu, [0112], where (potentially) relevant headnotes are identified for a given citation or pincite, i.e., from text of the input (Liu, [0107-0108]) (i.e., “text of a query”), and the headnotes may be scored based on comparing the text of the headnote to the context of the citation, by calculating a text similarity score).
Regarding claim 10: Claim 10 recites substantially the same claim limitations as claim 1, and is rejected for the same reasons.
Note that Liu teaches A system, comprising: a memory; and one or more processors, the one or more processors configured to perform steps comprising [the claimed steps] (Liu, [0141], [0146], and [0158], and where the disclosed steps may be implemented as a system, e.g., computers, comprising one or more processors 503 (CPU) that process instructions stored in memory 529).
Regarding claim 11: Claim 11 recites substantially the same claim limitations as claim 2, and is rejected for the same reasons.
Regarding claim 13: Claim 13 recites substantially the same claim limitations as claim 5, and is rejected for the same reasons.
Regarding claim 14: Claim 14 recites substantially the same claim limitations as claim 6, and is rejected for the same reasons.
Regarding claim 17: Claim 17 recites substantially the same claim limitations as claim 1, and is rejected for the same reasons.
Note that Liu teaches A computer program product, comprising: a non-transitory computer readable medium comprising code for performing steps comprising [the claimed steps] (Liu, [0189], where the disclosed steps may be implemented as computer software stored on a machine readable medium as part of a computer program product, and loaded into a computer system or other device, the computer readable medium including, e.g., read only memory (ROM), magnetic or optical disc, flash memory device, hard disk, etc. (i.e., “non-transitory”)).
Regarding claim 18: Claim 18 recites substantially the same claim limitations as claim 2, and is rejected for the same reasons.
Regarding claim 19: Claim 19 recites substantially the same claim limitations as claim 5, and is rejected for the same reasons.
Claims 3-4 and 12 are rejected under 35 U.S.C. 103 as being unpatentable over Liu et al. (“Liu”) (US 2018/0276305 A1), in view of Kovacs et al. (“Kovacs”) (US 2019/0108276 A1), in further view of Tabin (“Tabin”) (US 2008/0016441 A1).
Regarding claim 3: Liu as modified teaches The method of claim 2, but does not appear to explicitly teach further comprising: modifying, by the one or more processors, an order of the ranked set of headnotes to produce a modified ranked set of headnotes in response to one or more inputs received via the GUI, wherein the one or more inputs received via the GUI identify attributes of interest, and wherein a weight of one or more ranking features of the set of ranking features is modified based on the attributes of interest identified by the one or more inputs received via the GUI.
Tabin teaches modifying, by the one or more processors, an order of the ranked set of headnotes to produce a modified ranked set of headnotes in response to one or more inputs received via the GUI, wherein the one or more inputs received via the GUI identify attributes of interest, and wherein a weight of one or more ranking features of the set of ranking features is modified based on the attributes of interest identified by the one or more inputs received via the GUI (Tabin, [0025], where the system provides a plurality of user-alterable graphical user interface elements, which corresponds to at least one of the plurality of search criteria (i.e., “attributes of interest”), which illustrate current weighting values corresponding to the search criteria as are applied when determining a presentation order for the search results. See Tabin, [0030], where the system detects when user alteration of a given one of the user-alterable graphical user interface elements occurs, which causes a change in the weighting value that corresponds to the given one of the user-alterable graphic user interface elements (i.e., “wherein a weight of one or more of the ranking features is modified based on the attributes of interest identified by the one or more inputs”). When such an event occurs, the system automatically alters the presentation order for the search results (i.e., “outputting…a display of at least a portion of the modified ranked set of headnotes”) (see Tabin, [0038], with respect to how search results are displayed via display 200 (i.e., “GUI”)). The system thus determines a presentation order for the search results that takes into account the user-based re-weighting of the user-alterable graphic user interface element.
See Tabin, [0038] and [FIG. 2], where the system causes display 200 to present a plurality of search results as corresponding to a general search that was conducted using a plurality of search criteria. The system may also cause display 200 to present the user-alterable graphic user interface elements that determine the current weighting values as corresponding to the search criteria, and are applied when determining a presentation order for those search results (i.e., “in response to one or more inputs received via the GUI…”)).
It would have been obvious to one of ordinary skill in the art at the time of the claimed invention to have combined the teachings of Liu as modified and Tabin (hereinafter “Liu as modified”) with the motivation of potentially improving the confidence/relevance of search results by allowing users to manually configure/adjust the weights of certain characteristics associated with those search results (i.e., because users are able to configure such weights, they are allowed to be the judge of whether certain characteristics should be emphasized due to being more relevant to them, more accurate to them, etc.).
Regarding claim 4: Liu as modified teaches The method of claim 3, further comprising modifying an order of the modified ranked set of headnotes in response to an additional input received via the graphical user interface (Tabin, [0025], where the system provides a plurality of user-alterable graphical user interface elements, which corresponds to at least one of the plurality of search criteria (i.e., “attributes of interest”), which illustrate current weighting values corresponding to the search criteria as are applied when determining a presentation order for the search results. See Tabin, [0030], where the system detects when user alteration of a given one of the user-alterable graphical user interface elements occurs, which causes a change in the weighting value that corresponds to the given one of the user-alterable graphic user interface elements (i.e., “wherein a weight of one or more of the ranking features is modified based on the attributes of interest identified by the one or more inputs”). When such an event occurs, the system automatically alters the presentation order for the search results (see Tabin, [0038], with respect to how search results are displayed via display 200 (i.e., “GUI”). The system thus determines a presentation order for the search results that takes into account the user-based re-weighting of the user-alterable graphic user interface element).
Although Tabin does not appear to explicitly state an additional iteration of the aforementioned steps, one of ordinary skill in the art would have found it obvious to have modified Tabin to have as many iterations of the aforementioned steps as needed during a user’s search session with the motivation of (1) enabling users to continually refine the (same) search for greater convenience, flexibility, and relevance of search results, and (2) mere duplication of parts (i.e., the same and expected result is produced, which is that searches are refined for greater relevance).
Regarding claim 12: Claim 12 recites substantially the same claim limitations as claim 3, and is rejected for the same reasons.
Claims 7 and 15 are rejected under 35 U.S.C. 103 as being unpatentable over Liu et al. (“Liu”) (US 2018/0276305 A1), in view of Kovacs et al. (“Kovacs”) (US 2019/0108276 A1), in further view of McElvain et al. (“McElvain”) (US 2019/0340172 A1).
Regarding claim 7: Liu as modified teaches The method of claim 6, but does not appear to explicitly teach further comprising: generating a first set of embeddings based on the query; and generating a second set of embeddings corresponding to each headnote, wherein the similarity is determined for each headnote of the plurality of headnotes based on the first set of embeddings and the second set of embeddings.
McElvain teaches generating a first set of embeddings based on the query; and generating a second set of embeddings corresponding to each headnote (McElvain, [0060], where the embeddings generator 204 may generate embeddings for questions/headnotes (i.e., the “questions” corresponding to the claimed “query”)), wherein the similarity is determined for each headnote of the plurality of headnotes based on the first set of embeddings and the second set of embeddings (McElvain, [0060], where embeddings generator provides modeling of the semantic space of a particular document and/or headnotes. By modelling the semantic space of a document/headnote, the system may identify what components or elements of questions and answers are most similar in this semantic space. The output may include vectors (i.e., “embeddings”) used to determine the similarity of a candidate answer to the question (i.e., “based on the first set of embeddings and the second set of embeddings”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have combined the teachings of Liu as modified and McElvain with the motivation of understanding meaning/context rather than simply keywords, thereby providing more relevant search results.
Regarding claim 15: Claim 15 recites substantially the same claim limitations as claim 7, and is rejected for the same reasons.
Claims 8-9, 16, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Liu et al. (“Liu”) (US 2018/0276305 A1), in view of Kovacs et al. (“Kovacs”) (US 2019/0108276 A1), in further view of McElvain et al. (“McElvain”) (US 2019/0340172 A1), in further view of Upstill et al. (“Upstill”) (US 9,659,064 B1).
Regarding claim 8: Liu as modified teaches The method of claim 1, but does not appear to explicitly teach further comprising, in response to a second input to the graphical user interface, retrieving additional headnotes, each headnote of the additional headnotes having a headnote score satisfying a threshold similarity to the headnote score of the highest ranked headnote.
McElvain teaches in response to a second input to the graphical user interface, retrieving additional headnotes (McElvain, [0089], where a “more-like-this” search query may include a search query in which a candidate answer may be used as the query. In this manner, a “more-like-this” search may be used to increase the pool of potential answers after the initial set of candidate answers has been scored) … .
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have combined the teachings of Liu as modified and McElvain (hereinafter “Liu as modified”) with the motivation of retrieving additional search results using the same search query, i.e., without requiring the user to input a different search query, while allowing the user to explore additional results.
Liu as modified does not appear to explicitly teach each headnote of the additional headnotes having a headnote score satisfying a threshold similarity to the headnote score of the highest ranked headnote.
Upstill teaches each headnote of the additional headnotes having a headnote score satisfying a threshold similarity to the headnote score of the highest ranked headnote (Upstill, [2:51-67]-[3:1-9], where based on the query, the search results, or both, the search system can provide an additional search result by determining a second search query 106 and obtain search results responsive to the second search query. The search system can then provide the additional search result along with search results obtained for the original query, where generally, the search system will assign a score to the additional search result so that the additional search result will be ranked among a number of highest-ranked search results obtained for the original query 105. The additional search result 126 may be illustrated as being inserted into the search results at the highest-ranked position. See also Upstill, [7:1-15], where the system generates a ranking of the first search result and the one or more authoritative search results (from the additional search). The system adds the one or more authoritative search results to the set of first search results and ranks the one or more authoritative search results and first search results so that at least some of the additional authoritative search results are likely to be within a number of the highest-ranked search results. In some other implementations, the system uses the IR score of an authoritative search result for the second search query to rank the authoritative search result with the first search results. In some other implementations, the system selects an authoritative search result and ranks the authoritative search result as the highest-ranked search result among the first search results. See Upstill, [6:13-20], where the system determines to obtain an authoritative search result for the first query based on the information scores (IRs) of a number of the highest-ranked first search results.
See, e.g., Liu in claim 1 above and McElvain, [0030], [0065] and [0071], where the answers/search results pertain to “headnotes”, as claimed. See also McElvain, [0068], where a “more-like-this” search may be used to search for headnotes that closely match high scoring answers from outside the user’s jurisdiction (i.e., “highest-ranked headnote”)).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have combined the teachings of Liu as modified and Upstill (hereinafter “Liu as modified”) with the motivation of enabling users to find potentially more relevant/better search results based on a top-ranking previous search result, as such a previous top-ranking search result may better match the underlying semantics of the user’s intended question (see, e.g., McElvain, [0070]).
Regarding claim 9: Liu as modified teaches The method of claim 8, further comprising ranking the additional headnotes (Upstill, [7:1-15], where the system generates a ranking of the first search result and the one or more authoritative search results (from the additional search). The system adds the one or more authoritative search results to the set of first search results and ranks the one or more authoritative search results and first search results so that at least some of the additional authoritative search results are likely to be within a number of the highest-ranked search results.
See Liu in claim 1 above, and, e.g., McElvain, [0030], [0065] and [0071], where the answers/search results pertain to “headnotes”, as claimed).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have combined the teachings of Liu as modified and Upstill with the motivation of updating the user display to show the user those search results that are potentially more pertinent/relevant to them in order of pertinence/relevance.
Regarding claim 16: Claim 16 recites substantially the same claim limitations as claims 8-9, and is rejected for the same reasons.
Regarding claim 20: Claim 20 recites substantially the same claim limitations as claims 8-9, and is rejected for the same reasons.
Conclusion
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 nonprovisional extension fee (37 CFR 1.17(a)) 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 mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to IRENE BAKER whose telephone number is (408)918-7601. The examiner can normally be reached M-F 8-5PM PT.
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Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/IRENE BAKER/Primary Examiner, Art Unit 2154
30 June 2026
Prosecution Insights