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 Arguments
Applicant's arguments filed 07/17/26 have been fully considered but they are not persuasive.
Applicant argues that the prior art made of record does not teach generating the one or more topics by combining the plurality of extracted entity words, wherein the one or more topics each comprise K1 entity words (Amendment, pages 4, 5).
The examiner disagrees, since Stankiewicz et al. disclose “the weight on Topics B and D is greater than the weight on Topic E, the extraction unit 15 may retrieve the product profile indicating that the amount of words in each topic contained in the text information about products is the greatest in Topics B, D and E or Topics D, B and E in descending order… presentation of topics by the topic presentation unit 13 is described hereinafter with reference to FIG. 9. When selection of one or more topics with a predetermined amount or more of weights is received from the user terminal T by the receiving unit 14, the topic presentation unit 13 may present a plurality of sub-topics made up of a plurality of words formed by mechanically classifying a plurality of words contained in the topic to the user terminal T” (paragraphs 69 – 71).
Applicant argues that under either Steps 2A and 2B of the § 101 analysis, the amended independent claims are patent eligible. All of the dependent claims are patentable for at least similar reasons as those for the claims on which they depend are patentable (Amendment, pages 1 – 3).
The examiner disagrees, and points out the amended claims still recite an abstract idea, since nothing in the claims element precludes the steps from practically being performed in a human mind.
Claim Rejections - 35 USC § 101
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.
Claims 1, 3 – 9, 13– 18 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract without significantly more.
When considering subject matter eligibility under 35 USC 101, it must be determined whether the claim is directed to one of the four statutory categories of invention, i.e., process, machine, manufacture, or composition of matter.
Specifically, claims 1, 3 – 9, 13– 18 are directed to a method/system. They hereby fall under at least one of the four statutory classes of invention.
If the claim does not fall within one of the statutory categories, it must then be determined whether the claim is directed to a judicial exception (i.e., law of nature, natural phenomenon, and abstract idea).
Claims 1, 3 – 9, 13– 18 recite step of observation, evaluation, and judgement that can be practically performed by a human, either mentally or with the use of pen and paper.
The limitation of “generating the one or more topics by combining the plurality of extracted entity words, wherein the one or more topics each comprise K1 entity words ; and aggregating corresponding information related to the one or more topics based on the plurality of extracted entity words and the associated word that correspond to the one or more topics” in claims 1, 3 – 9, 13– 18, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind, but for the recitation of generic computer components. That is, other than reciting “a server”, nothing in the claim element precludes the steps from practically being performed in a human mind.
The mere nominal recitation of a server do not take the claim limitations out of the mental processes grouping.
If a claim limitation, under its broadest reasonable interpretation, covers mental processes but for the recitation of generic computer components, then it falls within the "Mental Processes" grouping of abstract ideas (concepts performed in the human mind including an observation, evaluation, judgement, and opinion). Accordingly, the claims recites an abstract idea.
This judicial exception is not integrated into a practical application. In particular, the claims recite the additional elements “receiving a K1 value that is input by a first end user device, wherein the K1 value specifies a quantity of entity words of one or more topics, and K1 is a positive integer greater than 1; extracting a plurality of entity words and an associated word associated with the plurality of entity words from original information content; generating the one or more topics by combining the plurality of extracted entity words, wherein the one or more topics each comprise K1 entity words”.
The limitation “receiving a K1 value that is input by a first end user device, wherein the K1 value specifies a quantity of entity words of one or more topics, and K1 is a positive integer greater than 1; extracting a plurality of entity words and an associated word associated with the plurality of entity words from original information content”, amount to data-gathering steps which is considered to be insignificant extra-solution activity, (See MPEP 2106.05(g)).
The limitation “generating the one or more topics by combining the plurality of extracted entity words, wherein the one or more topics each comprise K1 entity words”, represents an extra-solution activity because it is a mere nominal or tangential addition to the claim, a mere generic transmission and presentation of collected and analyzed data. (See MPEP 2106.05 (g)).
Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea, thus fail to integrate the abstract idea into a practical application. See MPEP 2106.05(g).
The insignificant extra-solution activities identified above, which include the data-gathering (extracting, generating, and aggregating) steps, are recognized by the courts as well-understood, routine, and conventional activities when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity (See MPEP 2106.05(d)(II) (i) Receiving or transmitting data over a network, e.g., using the Internet to gather data, buySAPE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPO2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network); (v) Presenting (displaying) offers and gathering statistics, OIP Techs., 788 F.3d at 1362-63, 115 USPO2d at 1092- 93). The claims are not patent eligible.
Claims 1, 3 – 9, 13– 18 do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of using a generic server to perform the extracting, generating, and aggregating steps amounts to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept.
Claims 1, 3 – 9, 13– 18 as a whole, do not amount to significantly more than the abstract idea itself. This is because the claims do not affect an improvement to the functioning of a computer itself; and the claims do not move beyond a general link of the use of an abstract idea to a particular technological environment.
Claims 19 – 24 are directed to patent eligible, since reciting additional elements of “ a device comprises a communication unit configured to receive one or more topics from a server”.
Claim Rejections - 35 USC § 103
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
Claims 1, 3 – 9, 13– 24 are rejected under 35 U.S.C. 103 as being unpatentable over Chu et al. (US Patent 10,108,707) in view of Stankiewicz et al. (US PAP 2015/0379610).
As per claim 1, 9, Chu et al. teach an information obtaining method, wherein the method comprises:
extracting a plurality of entity words and an associated word associated with the plurality of entity words from original information content (“the data source identifier may correspond to a trade name associated with a business entity that manages the news source server 420. The content extractor component 480 may also determine entities from the tagged text data output by the natural language component 260. For example, the content extractor component 480 may determine a name of an individual (e.g., a celebrity's name, a politician's name, etc.) referred to in the tagged text data. The content extraction component 480 may also determine the kind of event to which input data relates.”; col.9, line 61 – col.10, line 20);
aggregating corresponding information related to the one or more topics based on the plurality of extracted entity words and the associated word that correspond to the one or more topics (“an aggregation component 475 that groups data received from various content sources based on, for example, topic, entity (e.g., politician name or celebrity name), etc. The aggregation component 475 may determine how many sources publish, within a certain time period, articles or other data corresponding to a particular topic and may determine whether that number falls above or below a particular threshold.”; col.2, lines 17 – 3; col.8, line 66 -col.9, line 20).
However, Chu et al. do not specifically teach receiving a K1 value that is input by a first end user device, wherein the K1 value specifies a quantity of entity words of one or more topics, and K1 is a positive integer greater than 1; generating the one or more topics by combining the plurality of extracted entity words, wherein the one or more topics each comprise K1 entity words.
Stankiewicz et al. teach that the weight on Topics B and D is greater than the weight on Topic E, the extraction unit 15 may retrieve the product profile indicating that the amount of words in each topic contained in the text information about products is the greatest in Topics B, D and E or Topics D, B and E in descending order… presentation of topics by the topic presentation unit 13 is described hereinafter with reference to FIG. 9. When selection of one or more topics with a predetermined amount or more of weights is received from the user terminal T by the receiving unit 14, the topic presentation unit 13 may present a plurality of sub-topics made up of a plurality of words formed by mechanically classifying a plurality of words contained in the topic to the user terminal T…The sub-topics may be generated by, when the receiving unit 14 receives selection of a topic with a predetermined amount or more of weights… when the receiving unit 14 receives selection of a topic with a predetermined amount or more of weights from the user terminal T, the topic presentation unit 13 may extract a topic that is similar to the topic with a certain degree or higher from the topic storage unit and present them to the user terminal T… the topic presentation unit 13 may present a merged topic in which a plurality of topics other than the topic for which selection with a predetermined amount or more of weights is received among a plurality of topics presented to the user terminal T are merged to the user terminal T (paragraphs 69 – 77).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective date of the claimed invention to specify a quantity of entity words of the one or more topics as taught by Stankiewicz et al. in Chu et al., because that would help determine a rank score for the stored trending data associated with the topic or entity (Chu et al., col.11, lines 35 – 38).
As per claims 3, 13, Chu et al. in view Stankiewicz et al. further disclose sending the one or more topics to a second end user device, wherein the one or more topics
comprise a first topic; and in response to a selection request of the second end user device for the first topic, sending, to the second end user device, one or more pieces of information overview content corresponding to the first topic (Stankiewicz et al. paragraphs 69 – 77).
As per claims 4, 14, Chu et al. in view Stankiewicz et al. further disclose sending, based on the selection request, an information link corresponding to the first topic to the second end user device, wherein the information link associates one or
more original information content pages corresponding to the one or more pieces of information overview content (Chu et al. col.12, lines 7 – 27; Stankiewicz et al. paragraphs 69 – 77).
As per claims 5, 15, Chu et al. in view Stankiewicz et al. further disclose receiving a K2 value that is input by the first end user device, wherein K2 is a positive integer greater than 1, and K2 # K1; and the generating one or more topics by combining the plurality of extracted entity words further comprises: generating the one or more topics by combining the plurality of extracted entity words, wherein the one or more topics each comprise K2 entity words (“the weight on Topics B and D is greater than the weight on Topic E, the extraction unit 15 may retrieve the product profile indicating that the amount of words in each topic contained in the text information about products is the greatest in Topics B, D and E or Topics D, B and E in descending order…The sub-topics may be generated by, when the receiving unit 14 receives selection of a topic with a predetermined amount or more of weights… when the receiving unit 14 receives selection of a topic with a predetermined amount or more of weights from the user terminal T, the topic presentation unit 13 may extract a topic that is similar to the topic with a certain degree or higher from the topic storage unit and present them to the user terminal T”; Stankiewicz et al. paragraphs 69 – 77).
As per claims 6, 16, Chu et al. in view Stankiewicz et al. further disclose the extracting a plurality of entity words and an associated word from the original information content comprises: extracting the plurality of entity words and the associated word from the original information content by using a language model, wherein the language model comprises a semantic vector model, an entity word recognition model, and an associated word recognition model (The speech recognition component 250 interprets the spoken utterance based on a similarity between the spoken utterance and pre-established language models. For example, the speech recognition component 250 may compare the audio data 211 with models for sounds (e.g., subword units or phonemes) and sequences of sounds to identify words that match the sequence of sounds spoken in the utterance represented in the audio data…The natural language component 260 attempts to make a semantic interpretation of the phrases or statements represented in the text data input therein.”; Chu et al. col.5, lines 15 – 52).
As per claims 7, 17, Chu et al. in view Stankiewicz et al. further disclose obtaining original information from one or more channels based on a crawler information
obtaining technology, wherein the original information comprises the original information
content and a corresponding information link (Chu et al. col.5, lines 15 – 52).
As per claims 8, 18, Chu et al. in view Stankiewicz et al. further disclose the method for obtaining news information, the original information content is original news content, and the first topic is a news topic words (“user commands relating to trending topics (e.g., real-time news questions, trending questions, sports questions, game questions, politic questions, etc.). A topic may be considered “trending” if content corresponding to the topic is widely published or discussed on the Internet or in other content distribution modalities (e.g., television news, radio news, etc.) during a recent time period.”; Chu et al. col.2, lines 17 – 37).
As per claim 19, Chu et al. teach a device, wherein the device comprises:
a communication interface, configured to receive one or more topics from a server, where the one or more topics each comprise at least two entity words (“The server(s) 120 may group (132) at least a portion of the data based on topic or entity.”; col.3, lines 22 – 67); and
a display, configured to display the one or more topics (“The device 110 may alternatively or also be configured to display text. If the content data or the portion of the trending data is audio data, the server(s) 120 may perform speech recognition on the audio data to generate text data displayable by the device 110.”; col. 14, lines 50 – 56),
wherein the communication interface is further configured to: in response to a selection operation of a user on a first topic in the one or more topics, send a request message to the server to request one or more pieces of information overview content corresponding to the first topic (“the server(s) 120 may determine whether entities tagged in text data output by the natural language processing correspond to entities represented in the trending storage 265. For further example, the server(s) 120 may determine whether a topic tagged in text data output by the natural language processing corresponds to a topic represented in the trending storage 265. If the server(s) 120 determines the trending storage 265 does not include data responsive to the command, the server(s) 120 determines (612) content data responsive to the command from a source other than the trending storage 265.”; col.13, lines 51 – 63; col.14, lines 35 – 56); and
receive the one or more pieces of information overview content corresponding to the first topic from the server (“the server(s) 120 may determine whether a topic tagged in text data output by the natural language processing corresponds to a topic represented in the trending storage 265. If the server(s) 120 determines the trending storage 265 does not include data responsive to the command, the server(s) 120 determines (612) content data responsive to the command from a source other than the trending storage 265.”; col.13, lines 51 – 63).
However, Chu et al. do not specifically teach that the one or more topics are generated by combining entity words among a plurality of extracted entity words.
Stankiewicz et al. teach that the weight on Topics B and D is greater than the weight on Topic E, the extraction unit 15 may retrieve the product profile indicating that the amount of words in each topic contained in the text information about products is the greatest in Topics B, D and E or Topics D, B and E in descending order… presentation of topics by the topic presentation unit 13 is described hereinafter with reference to FIG. 9. When selection of one or more topics with a predetermined amount or more of weights is received from the user terminal T by the receiving unit 14, the topic presentation unit 13 may present a plurality of sub-topics made up of a plurality of words formed by mechanically classifying a plurality of words contained in the topic to the user terminal T (paragraphs 69 – 71).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective date of the claimed invention to specify a quantity of entity words of the one or more topics as taught by Stankiewicz et al. in Chu et al., because that would help determine a rank score for the stored trending data associated with the topic or entity (Chu et al., col.11, lines 35 – 38).
As per claim 20, Chu et al. in view of Stankiewicz et al. further disclose the display unit is further configured to: display an information overview content list, wherein the information overview content list comprises the one or more pieces of information overview content corresponding to the first topic (Chu et al. col.5, lines 15 – 52; col.12, lines 7 – 27; col. 14, lines 50 – 56).
As per claim 21, Chu et al. in view of Stankiewicz et al. further disclose the request message further requests an information link corresponding to the first topic, and wherein the information link associates an original information content page corresponding to the one or more pieces of information overview content(Chu et al. col.5, lines 15 – 52; col.12, lines 7 – 27; col. 14, lines 50 – 56).
As per claim 22, Chu et al. in view of Stankiewicz et al. further disclose the display unit is further configured
to: in response to an operation of selecting a first piece of information overview content in the information overview content list by the user, display a corresponding original information content page by using an information link corresponding to the first piece of information overview content (Chu et al. col.5, lines 15 – 52; col.12, lines 7 – 27; col. 14, lines 50 – 56).
As per claim 23, Chu et al. in view of Stankiewicz et al. further disclose the first topic is a news topic (“trending topics (e.g., real-time news questions, trending questions, sports questions, game questions, politic questions, etc.). A topic may be considered “trending” if content corresponding to the topic is widely published or discussed on the Internet or in other content distribution modalities (e.g., television news, radio news, etc.)”; Chu et al., col.2, lines 17 – 25).
As per claim 24, Chu et al. in view of Stankiewicz et al. further disclose each of the one or more pieces of information overview content in the information overview content list comprises an information title and a content overview (Chu et al., col.2, lines 17 – 25).
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 LEONARD SAINT-CYR whose telephone number is (571)272-4247. The examiner can normally be reached Monday- Friday.
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, Richemond Dorvil can be reached at (571)272-7602. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/LEONARD SAINT-CYR/Primary Examiner, Art Unit 2658
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