[00:00:31] Speaker 03: Okay. [00:00:33] Speaker 03: The next argued case is number 16, 2736 in Raynambula. [00:00:38] Speaker 03: Mr. Mahmood. [00:00:44] Speaker 00: May I please the court? [00:00:46] Speaker 00: My name is Jindal Mahmood. [00:00:47] Speaker 00: I go by JD. [00:00:48] Speaker 00: Standing here speaking on behalf of my client for his invention, which is an appeal. [00:00:54] Speaker 01: In the blue brief at 12, [00:00:59] Speaker 01: You argue there's a difference between search queries and search results. [00:01:03] Speaker 01: Yes. [00:01:05] Speaker 01: Why is that material in our obviousness? [00:01:07] Speaker 00: It's very different. [00:01:09] Speaker 00: You're referring to 2023, Your Honor. [00:01:13] Speaker 00: Basically, if, for example, you're searching against something that is just a suggestion, your consideration is very different. [00:01:23] Speaker 00: For example, you may have a time constraint. [00:01:24] Speaker 00: You may want to display the results very quickly. [00:01:27] Speaker 00: But on the other hand, if you're searching against something that the user submitted, that's totally different. [00:01:33] Speaker 00: Given that you can have more resources to deal with, you don't have as much time constraint that you have, so you would most likely do a much better search. [00:01:44] Speaker 00: For Claim23... What evidence shows those differences? [00:01:48] Speaker 00: Well, I mean, that's... [00:01:50] Speaker 00: You know, I think that should be able to find in the prior and I can supply supplemental research for... I'm not asking for supplemental research. [00:02:00] Speaker 00: What evidence in the record? [00:02:02] Speaker 00: But anyway, they are just different subject matter because... No, no, no, no, no, no, no, no. [00:02:07] Speaker 01: You don't get to say to a judge, but anyway, when the judge is asking you for evidence in the record, you can say, there isn't any, or you can tell me where it is. [00:02:20] Speaker 00: Well, it's just something that those skills, I mean, I don't know, it's just something, you know, it's not in the record because... So a person of skill in the art would know it, so is there an affidavit to that effect? [00:02:35] Speaker 01: Well, not at this point. [00:02:38] Speaker 00: But can I make a point on this? [00:02:41] Speaker 00: You know, the reason that the search results in claim 23 is different from the search results that [00:02:49] Speaker 00: the appellee is referring to is different, is that that search results actually is search against the suggested query, so it's still displaying the vicinity of the suggestion list, which means that the user doesn't have to select it, so technically it's still a suggestion, not something that the user has submitted. [00:03:19] Speaker 02: Looking at, I'm going to call this reference Rack's Hit. [00:03:23] Speaker 02: OK. [00:03:24] Speaker 02: All right. [00:03:24] Speaker 02: So there's a figure five, box 504. [00:03:29] Speaker 02: And then in the spec of Rack's Hit, it says box 504 displays those websites 510 that have been highest ranked against the query suggestion. [00:03:42] Speaker 02: You're saying in your view, those websites 510 that are being displayed [00:03:48] Speaker 02: that are the highest ranked against the query suggestion, those are not search results in your view? [00:03:54] Speaker 00: Well, they're not the search results referred in the claim. [00:03:57] Speaker 00: The search results referred in the claim are search results against a query actually submitted by a user. [00:04:05] Speaker 00: So, you know, we've got to keep subtending meaning to the claim language. [00:04:12] Speaker 00: That's what I'm referring to. [00:04:13] Speaker 00: Essentially, the search results that you referred to [00:04:17] Speaker 00: with 113.504 is fundamentally distinct from the search results displayed as a result of the user submitting a search query. [00:04:49] Speaker 01: Is the creating limitation in claim 19 the essential step that you keep referring to? [00:04:56] Speaker 00: Yes, it is. [00:04:58] Speaker 00: And that's evident when the specification as a whole is viewed. [00:05:06] Speaker 00: I can also give an example as to why it's so essential. [00:05:10] Speaker 00: For example, in the specification it describes [00:05:13] Speaker 00: you know, a lot of the searches using conventional search query suggestions is not very relevant to that very user who's trying to make a search. [00:05:24] Speaker 00: One example is that without the technology, if the user type jobs, okay, so what happens is that the search engine will look for what maybe other people that submit the same word job may look for, right, so they will come up with a list of search query suggestions. [00:05:42] Speaker 00: But in this image, the extra step is that it goes to a social networking platform to exactly search for the social networking information of that user. [00:05:56] Speaker 00: For example, the friends of that user. [00:05:59] Speaker 00: Noting that companies usually always come very closely related to that certain jobs, so we will actually put the friends companies at the top of the search [00:06:11] Speaker 02: So the inventive concept here is the idea of supplementing a search engine with a user's social networking information in order to, I guess, improve search query suggestions. [00:06:32] Speaker 02: So you're supplementing based on, in part, a particular kind of information that's [00:06:39] Speaker 02: specific to the user. [00:06:40] Speaker 02: And it was already known in the art to use information specific to the user to supplement figuring out search queries because it was already known to use the location of a user's terminal to help figure out what would be a good set of search query suggestions. [00:07:03] Speaker 00: Is that right? [00:07:04] Speaker 00: Well, I don't know about that. [00:07:06] Speaker 00: Well, your specification says that. [00:07:09] Speaker 00: The specification says the location, but this is specifically about using, for example, the IP address. [00:07:18] Speaker 00: Is that the location you're referring to? [00:07:20] Speaker 00: Well, but that's not the social network information. [00:07:22] Speaker 02: Oh, I understand. [00:07:23] Speaker 02: It's different, but it's nevertheless information that's person-specific, computer terminal-specific. [00:07:30] Speaker 00: Well, that can increase the relevancy, but that wouldn't have the kind of relevancy that I'm referring to in connection with that search on the term jobs. [00:07:38] Speaker 00: Because, for example, in that search without my transformation, the friends companies will be actually at the top of the list of that search press suggestion list. [00:07:51] Speaker 00: But on the other hand, without this invention, the conventional search would have been just looking for what other people may search for jobs, and they would just come up with something that lists in that area. [00:08:02] Speaker 02: I guess I'm trying to figure out just [00:08:06] Speaker 02: Whether this is really a non-obvious advance in light of Rackset, given that Rackset already has the insight to combine a search engine server with a social networking server and then applying a user's social networking information in order to figure out what would be, to provide a user [00:08:36] Speaker 02: ideal search query suggestions. [00:08:38] Speaker 02: I understand there's a difference between the reference and what your invention is, but already we're getting into the territory of relying in part on users' social networking information to help guide the user in trying to choose ideal search query suggestions for that user. [00:09:00] Speaker 00: Yes, it's a big distinction. [00:09:03] Speaker 00: The social network information we're using is exclusively used to decorate or provide additional information for a search query suggestion that's already created. [00:09:12] Speaker 00: It's not involving the creation process. [00:09:15] Speaker 02: But in the end, both your invention, your client's invention, and Rackset, what are they trying to do? [00:09:21] Speaker 02: What is the ultimate goal? [00:09:22] Speaker 02: The ultimate goal is to try to help a user along with offering search query suggestions that the user is hopefully [00:09:32] Speaker 02: going to like. [00:09:33] Speaker 02: And both use social networking information in a way to help guide the user. [00:09:40] Speaker 02: I know you're saying that's too broad, but we have to start somewhere. [00:09:44] Speaker 02: And that seems like a decent enough starting step before we drill down. [00:09:48] Speaker 00: Well, that's not such a matter of the plane. [00:09:52] Speaker 00: The purpose of the plane is specifically to increase the relevancy of that query text. [00:09:59] Speaker 00: For example, try to use an impression of some kind of feedback on a search query suggestion that's already created. [00:10:08] Speaker 00: So that's the key to distinction. [00:10:10] Speaker 00: For example, using Rackshut's scheme, its creation of the search query text suggestion is still exactly the same as the conventional. [00:10:22] Speaker 00: So in this jobs case that I just described to you, under Rackshut's scheme, there's still going to be jobs [00:10:28] Speaker 00: blah, blah, blah, based on some other people preferred search query. [00:10:35] Speaker 00: That's gleaned from the public. [00:10:40] Speaker 00: But it is not something that's very personal, for example, to the user. [00:10:45] Speaker 00: For example, like the user's friends' companies where they work for, which will be here at the top. [00:10:50] Speaker 00: So that's a key distinction. [00:10:52] Speaker 00: And that applies to the secondary reference, Williams as well. [00:11:05] Speaker 03: Okay. [00:11:06] Speaker 03: Alright, let's hear from the office and we'll save the rest of your time. [00:11:15] Speaker 03: Ms. [00:11:15] Speaker 03: Rasheed? [00:11:16] Speaker 04: May I please report? [00:11:17] Speaker 04: There is no real daylight between all of the claims here that are so general and the prior Rasheed reference. [00:11:26] Speaker 04: Rasheed clearly teaches using retrieved search query suggestions from the user's social network, social contacts of the user. [00:11:33] Speaker 01: Mr. [00:11:35] Speaker 01: Namila contends that the prior art doesn't teach the ranking limitation. [00:11:42] Speaker 01: What part of the prior art teaches ranking search results rather than queries? [00:11:47] Speaker 01: And does it matter? [00:11:50] Speaker 04: Well, yeah. [00:11:51] Speaker 04: In view of the general nature of the way results is described and is used in the claims and then described in the specification, there is no real difference. [00:12:01] Speaker 04: And Rachid specifically teaches in paragraph 26 ranking [00:12:05] Speaker 04: websites that the user's social contacts visited after recommending those websites. [00:12:10] Speaker 04: So those are results of the search suggestions. [00:12:19] Speaker 04: Ultimately here, the claims are just broadly directed to using social network information to create search query suggestions. [00:12:28] Speaker 04: Racksheep alone pretty much teaches the claim limitations here. [00:12:34] Speaker 04: the motivation to combine or to motivation to actually do an alterer actually that's just based on KSRs. [00:12:42] Speaker 04: Determination that familiar elements that are combined in known ways to use predictable results are obvious and that's exactly what is going on here. [00:12:53] Speaker 04: To the extent that creating UK-19 means something more in terms of creating a new suggested search query that is different from a previously retrieved search query [00:13:04] Speaker 04: OEMs teach us using an N-gram language model to create new search queries. [00:13:09] Speaker 01: What was the evidence upon which the board relied for a motivation to combine? [00:13:17] Speaker 04: I think on the motivation to combine, the board on page 6 of its decision noted that simply applying a social networking filter [00:13:32] Speaker 04: to spreadsheet the system to provide only search query suggestions that have recommendations and websites associated with them would have been obvious. [00:13:42] Speaker 04: And the board relies on KSR for that. [00:13:44] Speaker 04: To the extent that creating requires something more in terms of creating a new search query that's different from a past search query, the board relies on Williams's teaching itself, which says that creating a new search query would provide for more dynamic [00:14:01] Speaker 04: search suggestions, and that naturally suggests its combination with our sheet. [00:14:07] Speaker 02: Does Williams also teach the idea of searching a social networking database? [00:14:13] Speaker 02: He does. [00:14:14] Speaker 04: He does, Your Honor. [00:14:15] Speaker 04: It specifically talks about indexed networked data that could be social network data, including Facebook and Twitter as possible sources of that information. [00:14:25] Speaker 04: The claims are pretty much just this concept of searching social network information and just using a different database. [00:14:33] Speaker 04: And William seems to do exactly that as well. [00:14:38] Speaker 02: The board adopted the examiner's final office action, advisory action, and examiner's answer? [00:14:44] Speaker 04: It did on page four of the board's decision. [00:14:48] Speaker 04: And then only addressed whatever arguments that an omulet raised in its appeal brief. [00:14:56] Speaker 04: If there are no further questions, I see the rest of my time. [00:14:58] Speaker 03: Any more questions? [00:15:00] Speaker 03: Thank you, Ms. [00:15:01] Speaker 03: Rashi. [00:15:02] Speaker 03: Thank you. [00:15:07] Speaker 03: Mr. Ma? [00:15:10] Speaker 00: Hi, Your Honor. [00:15:15] Speaker 00: I want to use this opportunity to address the question you just asked me about the affidavit. [00:15:19] Speaker 00: Actually, the burnings on the appellee when, for example, two subject matter are distinct. [00:15:26] Speaker 00: to prove that these two distinct subjects are actually obvious with respect to each other. [00:15:31] Speaker 00: The burden actually is unlikely on that panel, and I plead to deny proof of that. [00:15:36] Speaker 00: In other words, they basically just conclusively conclude the search results referred to in the Claim 23 is nondistinguishable from the search results in that 504, in that figure 5. [00:15:53] Speaker 00: So, given that the athlete hasn't discharged his duty, you know, in this case, this claim, God should be ruling in favor of my client. [00:16:05] Speaker 00: And also, I want to address the Williams case. [00:16:09] Speaker 00: The key is actually for this case, right, the key for this event is not really whether social networking website as a whole was used in some kind of search engine. [00:16:19] Speaker 00: with respect to whether the social network information of that very user who entered that query, who wanted to enter that query, was taken into consideration when dividing a search results for that user so that the user can see a list of relatively very relevant search query suggestions below that search box as he's typing or she's typing. [00:16:45] Speaker 00: So that's the key. [00:16:47] Speaker 00: the social network in general. [00:16:49] Speaker 00: I noticed that, you know, in the police briefs, right, it's almost like put up a lot of smokescreen as to try to carve out or extrapolate something out of Raksha as if something is relevant, but it's not. [00:17:03] Speaker 00: For example, it says that somehow something can be readily extrapolated from Raksha's teaching that the idea of applying a social network as part of the initial query creation process, but that's way too broad. [00:17:16] Speaker 00: We're talking about a specific step of creating using something that's very specific to that. [00:17:23] Speaker 02: The claim doesn't say very much. [00:17:25] Speaker 02: Nor does the specification about this overall broad concept of somehow using the notion of the user's social networking information. [00:17:35] Speaker 02: You then work its way into search query suggestions. [00:17:42] Speaker 02: Describe that result, that desire to do that, but then there aren't any details on how to go about and actually do it. [00:17:48] Speaker 00: Well, actually, first, the claim is very specific with respect to the social network information that we're using. [00:17:55] Speaker 00: In fact, it's actually verbatim in the claim language. [00:17:58] Speaker 00: And second, with respect to give an example, the jobs example that I just gave, specifically show how using the specific [00:18:10] Speaker 00: the social networking information of that user can actually increase the relevance. [00:18:14] Speaker 00: For example, without using that information, you would have just been listing query suggestions like jobs in blah blah blah, jobs in this blah blah blah. [00:18:27] Speaker 00: But using, for example, the social networking information of that very user, you will actually put his or her friends' companies at the top of the list. [00:18:36] Speaker 00: And that in itself shows [00:18:40] Speaker 00: the relevance, they increase the relevancy in terms of providing the effective search query suggestion list. [00:18:52] Speaker 00: The example actually, in my opinion, is very specific as to the advantage of this essential step. [00:19:03] Speaker 03: Any more questions for Mr. Ma? [00:19:05] Speaker 03: More questions? [00:19:07] Speaker 03: Thank you. [00:19:07] Speaker 03: Thank you both. [00:19:08] Speaker 03: The case is taken under submission. [00:19:10] Speaker 03: And that concludes this panel's augur cases for this morning.