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 Arguments
Applicant’s arguments, see remarks, filed 10/13/2025, with respect to 35 USC 101 have been fully considered and are persuasive. The rejection of claims 1,6-7,9,14-15,17-19 has been withdrawn.
Applicant’s arguments with respect to claim(s) 1,6-7,9,14-15,17-19 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Regarding claim 21, such claim is newly added. Please see the office action below.
Claim Rejections - 35 USC § 102
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 (i.e., changing from AIA to pre-AIA ) 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.
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 –
(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.
Claim(s) 1,6-7,914-15,17-19,21 is/are rejected under 35 U.S.C. 102a1 as being anticipated by Lev-Tov et al (US Publication No.: 20170116173).
Claim 1, Lev-Tov et al discloses
calculating, by a computer processor (Fig. 13a, label CPU), a distance (Paragraph 130 discloses "identifies a list of one or more probable clusters corresponding to the phrase (e.g., based on computing semantic distances between the input phrase and each of the clusters and identifying clusters having a semantic distance below a threshold).") between nodes for each of a plurality of pairs of nodes (Fig. 6, label C indicates the customer, A indicates the agent, each C, A indicates a node. Pairs of the nodes are CA connected via an edge.), the pairs comprising one or more of a plurality of entities and initial clusters (Fig. 2 shows a similar diagram as Fig. 6 with interactions. Fig. 2, label 222 shows agent with response to customer selection found in Layer 1, 212. The entities are words of the interactions associated with Agent and Client. The initial clusters are nodes initial interaction between the customer and agent, such as 202 and 212 as one cluster with final clusters such as label 222,232, labels 224,234.);
selecting, by the processor (Fig. 13a, label CPU), one or more of the pairs based on the calculated distances (Paragraph 74 discloses layers are numbered based on distance from the root of the tree. (Paragraph 130 discloses a list of one or more probable lusters corresponding to the received input phrase and identifying or selecting clusters based on the computer distance, where the clusters include pairs as shown in Fig .6.);
merging, by the processor (Fig. 13a, label CPU), one or more of the selected pairs including a common node into one or more final clusters (Fig. 6, label Layer 2, A2,A3 as merging of one or more pairs including a common node, C1, into one or more final clusters, A1,C1,A2,A3.);
automatically generating a taxonomy comprising one or more of the final clusters, the taxonomy organized in a hierarchical structure (Fig. 6 shows a taxonomy or graph or ontology organized in hierarchical structure comprising one or more final clusters.); and
routing, by a private branch exchange (PBX) (Paragraph 62 discloses switch 12 as a private branch exchange for routing the end user response to an agent.), one or more incoming interactions to one or more remote computers based on the automatically generated taxonomy (Paragraph 124 discloses routing the next dialogue based on the customer cluster determined via tree such as the tree shown in Fig. 6.), the remote computers connected by a network to a computer system comprising the computer processor (Fig. 1, label 10a-10c as end users, label 38a-38c as agents, label 20,22,45 as computer systems. Fig. 13a, label CPU as the processor.).
Claim 6, Lev-Tov et al discloses providing, by the processor, a plurality of search results for an input query based on the final clusters (Fig. 2, label 222,224 are results of a search or request input by the customer at label 212. Labels 222,224,226 along with 232,234 are considered final clusters.).
Claim 7, Lev-Tov et al discloses wherein one or more of the entities include one or more words extracted from one or more documents (Fig. 2, label 222,232 shows one or more words extracted from the interactions or documents between agent and customer.).
Claim 9, Lev-Tov et al discloses
a memory (Fig. 13a,13b, label 1522), and a computer processor (Fig. 13a,b, label 1521) configured to:
calculate a distance (Paragraph 130 discloses "identifies a list of one or more probable clusters corresponding to the phrase (e.g., based on computing semantic distances between the input phrase and each of the clusters and identifying clusters having a semantic distance below a threshold).") between nodes for each of a plurality of pairs of nodes (Fig. 6, label C indicates the customer, A indicates the agent, each C, A indicates a node. Pairs of the nodes are CA connected via an edge.), the pairs comprising one or more of a plurality of entities and initial clusters (Fig. 2 shows a similar diagram as Fig. 6 with interactions. Fig. 2, label 222 shows agent with response to customer selection found in Layer 1, 212. The entities are words of the interactions associated with Agent and Client. The initial clusters are nodes initial interaction between the customer and agent, such as 202 and 212 as one cluster with final clusters such as label 222,232, labels 224,234.);
select one or more of the pairs based on the calculated distances (Paragraph 74 discloses layers are numbered based on distance from the root of the tree. (Paragraph 130 discloses a list of one or more probable lusters corresponding to the received input phrase and identifying or selecting clusters based on the computer distance, where the clusters include pairs as shown in Fig .6.);
merge one or more of the selected pairs including a common node into one or more final clusters (Fig. 6, label Layer 2, A2,A3 as merging of one or more pairs including a common node, C1, into one or more final clusters, A1,C1,A2,A3.);
automatically generating a taxonomy comprising one or more of the final clusters, the taxonomy organized in a hierarchical structure (Fig. 6 shows a taxonomy or graph or ontology organized in hierarchical structure comprising one or more final clusters.); and
route, by a private branch exchange (PBX) (Paragraph 62 discloses switch 12 as a private branch exchange for routing the end user response to an agent.), one or more incoming interactions to one or more remote computers based on the automatically generated taxonomy (Paragraph 124 discloses routing the next dialogue based on the customer cluster determined via tree such as the tree shown in Fig. 6.), the remote computers connected by a network to a computer system comprising the computer processor (Fig. 1, label 10a-10c as end users, label 38a-38c as agents, label 20,22,45 as computer systems. Fig. 13a, label CPU as the processor.).
Claim 14, Lev-Tov et al discloses providing, by the processor, a plurality of search results for an input query based on the final clusters (Fig. 2, label 222,224 are results of a search or request input by the customer at label 212. Labels 222,224,226 along with 232,234 are considered final clusters.).
Claim 15, Lev-Tov et al discloses wherein one or more of the entities include one or more words extracted from one or more documents (Fig. 2, label 222,232 shows one or more words extracted from the interactions or documents between agent and customer.).
Claim 17, Lev-Tov et al discloses
in a computerized system (Fig. 13a,b) comprising a processor (Fig. 13a,b, label 1521) and a memory (Fig. 13a,b, label 1522), and connected by a network to one or more remote computers (Fig. 1 shows connections via network of one or more remote computers.):
extracting, by the processor (Fig. 13a,b, label 1521), a plurality of words from one or more documents (Fig. 2, label Agent, Customer shows interactions between agent and customer with extracted words from interactions or documents.);
calculating, by the processor (Fig. 13a,b, label 1521), a distance (Paragraph 130 discloses "identifies a list of one or more probable clusters corresponding to the phrase (e.g., based on computing semantic distances between the input phrase and each of the clusters and identifying clusters having a semantic distance below a threshold).") between nodes for each of a plurality of pairs of nodes (Fig. 6, label C indicates the customer, A indicates the agent, each C, A indicates a node. Pairs of the nodes are CA connected via an edge.), the pairs comprising one or more of a plurality of entities and initial clusters (Fig. 2 shows a similar diagram as Fig. 6 with interactions. Fig. 2, label 222 shows agent with response to customer selection found in Layer 1, 212. The entities are words of the interactions associated with Agent and Client. The initial clusters are nodes initial interaction between the customer and agent, such as 202 and 212 as one cluster with final clusters such as label 222,232, labels 224,234.);
selecting, by the processor (Fig. 13a,13b label 1521), one or more of the pairs based on the calculated distances (Paragraph 74 discloses layers are numbered based on distance from the root of the tree. Paragraph 130 discloses a list of one or more probable clusters corresponding to the received input phrase and identifying or selecting clusters based on the computer distance, where the clusters include pairs as shown in Fig .6.);
merging, by the processor (Fig. 13a,13b label 1521), one or more of the selected pairs including a common node into one or more final clusters (Fig. 6, label Layer 2, A2,A3 as merging of one or more pairs including a common node, C1, into one or more final clusters, A1,C1,A2,A3.);
ranking, by the processor, one or more nodes within one or more of the final clusters (Fig. 6, label layer 1, layer 2 indicates the ranking of one or more nodes within the one or more final clusters. Fig. 2, label layer 2,3 indicates ranking of one or more nodes within the final clusters.);
selecting, by the processor (Fig. 13a,b, label 1521), one or more of the ranked nodes as cluster titles (Paragraph 87 discloses each cluster includes a unique identifier such as some clusters may be associated with greetings or particular responses, etc. Such cluster id is corresponds to a particular concept within an interaction. Fig. 6, labels a1,c1,a2,a2 can be considered a cluster with cluster title associated with concept of the interaction associated with such nodes in the cluster. For example, Fig. 2, label 202,212,222,232 as a cluster with title associated with the concept of such cluster.);
iteratively repeating the extracting of a plurality of words (Paragraph 83 discloses a collection of recorded interactions between customers and human agents collected and analyzed. This indicates clustering of each interaction. Paragraph 87-88 discloses clustering each interaction. In order to cluster each interaction, words or dialogue is extracted.),
the calculating of a distance between nodes (Paragraph 74 discloses layers are numbered based on distance from the root of the tree. Paragraph 130 discloses a list of one or more probable clusters corresponding to the received input phrase and identifying or selecting clusters based on the computer distance, where the clusters include pairs as shown in Fig .6. To generate the tree or diagram as shown in Fig. 6 for the collection of interactions, the generation includes calculating distance between nodes.),
the selecting one or more of the pairs (Paragraph 74 discloses layers are numbered based on distance from the root of the tree. Paragraph 130 discloses a list of one or more probable clusters corresponding to the received input phrase and identifying or selecting clusters based on the computer distance, where the clusters include pairs as shown in Fig .6. In order to generate the tree or diagram as shown in Fig. 6 for the collection of interactions as per paragraph 83, selection of one or more pairs is performed.),
the merging of one or more of the selected pairs (Fig. 6, label Layer 2, A2,A3 as merging of one or more pairs including a common node, C1, into one or more final clusters, A1,C1,A2,A3.),
the ranking of one or more nodes (Fig. 6, label layer 1, layer 2 indicates the ranking of one or more nodes within the one or more final clusters. Fig. 2, label layer 2,3 indicates ranking of one or more nodes within the final clusters.), and
the selecting of one or more of the ranked notes (Paragraph 87 discloses each cluster includes a unique identifier such as some clusters may be associated with greetings or particular responses, etc. Such cluster id corresponds to a particular concept within an interaction. This indicates depending on the nodes within the final clusters, the title is associated with the concept of the interactions associated with the nodes within the final clusters. Such is repetitively determined as clusters and nodes are determined for interactions within the collection.),
until one or more convergence criteria are met (Paragraphs 108-16,119 discloses code for generation of diagram or tree as shown in Fig. 6, where iteration occurs till a threshold, k.), wherein the criteria based on at least one of: a maximum cluster size, and a maximum number of pairs including a common node (Paragraph 104 discloses k corresponds to the concept that, in the output dialogue tree T, every path from the root to the leaves has support >= k. For example, every sequence of clusters found along path from the root to the leaves of the tree, “there are at least k instances of sequence in the collection of recorded interactions…”. This indicates the criteria is based on a maximum cluster size (every sequence of clusters found along path from root to leaves of tree) and a maximum number of pairs including a common node (every sequence of clusters found along path from root to leaves of tree which includes pairs including a common node such as Fig. 6, layer 2, A2,A3).);
automatically generating a taxonomy comprising one or more of the final clusters, the taxonomy organized in a hierarchical structure (Fig. 6 shows a taxonomy or graph or ontology organized in hierarchical structure comprising one or more final clusters.); and
routing, by a private branch exchange (PBX) (Paragraph 62 discloses switch 12 as a private branch exchange for routing the end user response to an agent.), one or more incoming interactions to one or more remote computers based on the automatically generated taxonomy (Paragraph 124 discloses routing the next dialogue based on the customer cluster determined via tree such as the tree shown in Fig. 6.), the remote computers connected by a network to a computer system comprising the computer processor (Fig. 1, label 10a-10c as end users, label 38a-38c as agents, label 20,22,45 as computer systems. Fig. 13a, label CPU as the processor.).
Claim 18, Lev-Tov et al discloses providing a plurality of search results for an input query based on the final clusters (Fig. 2, label 222,224 are results of a search or request input by the customer at label 212. Labels 222,224,226 along with 232,234 are considered final clusters.).
Claim 19, Lev-Tov et al discloses one or more of the documents describe one or more interactions (Fig. 2, label 222,232 text or document of interactions. For example, “What is your destination?” and optional destinations are text or document of interaction or communication between agent and customer. Such texts or documents of interactions describes the one or more interactions.),
the interactions routed using a private branch exchange to one or more of the remote computers (Fig. 1, label 12, end users and agent devices are one or more remote computers.).
Claim 21, Lev-Tov et al discloses each of the one or more routed incoming interactions comprise an audio conversation (Paragraph 3 discloses interactions between agents and customers may be conducted via speech or audio, video, text, etc.).
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 LINDA WONG whose telephone number is (571)272-6044. The examiner can normally be reached 9-5.
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.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Andrew C Flanders can be reached at 571-272-7516. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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.
/LINDA WONG/Primary Examiner, Art Unit 2655