WO2013106467
"1. A method comprising:
receiving a plurality of story(記事)requests to generate a sponsored story unit(スポンサ記事ユニット), each story request specifying a type of interaction(対話)performed by a connection of a viewing(閲覧)user;
identifying(特定)a plurality of interactions, wherein each interaction is performed by a user having a connection to the viewing user;
selecting a story request from the plurality of story requests, wherein the selected story request specifies(指定)a type of interaction that corresponds to at least one interaction in the plurality of identified interactions;
identifying one or more posts, wherein each of the identified posts has a connection with a social networking object involved in the at least one identified interaction corresponding to the type of interaction specified in the selected story request;
selecting at least one post from the one or more posts;
generating a sponsored story unit that comprises (1) content(コンテンツ;*無冠詞)describing the at least one interaction and (2) content for the selected at least one post; and providing the sponsored story unit for display to the viewing user."
"[0001] This invention generally pertains to social networking, and more specifically to generating sponsored story units that include related posts and, optionally(任意の), input elements.
[0002] Social networks, or social utilities that track and enable connections between users (including people, businesses, and other entities), have become prevalent in recent years(近年広く行き渡って). In particular, social networking systems allow users to communicate information more efficiently. For example, a user may post contact information, background information, job information, hobbies, and/or other user-specific data to a location associated with the user on a social networking system. Other users can then review the posted data by browsing user profiles or searching for profiles including specific data. The social networking systems also allow users to associate themselves with other users, thus creating a web of connections among the users of the social networking system. These connections among the users can be exploited(活用)by the social networking system to offer more relevant information to each user in view of the users' own stated interests."
US2011022405
"1. A method of managing customer information comprising:
recording customer information and preferences(優先順位)for interacting with(対話を行う)a plurality of providers by a computer;
storing the customer information in a profile by the computer; and
using the customer information to facilitate(容易にする)interaction between provider computers and the customer by the computer."
WO2010011903
"1. A method that is implemented by a device for touch interaction(タッチ対話)with a curved(曲面)display, the method comprising acts of: monitoring (402) a curved display (102) to detect a touch input; if a touch input is detected (404) based on the act of monitoring, determining (406) one or more locations of the touch input; and implementing (408) at least one user interface (UI) feature responsive to(応答して)the determined one or more locations of the touch input."
WO2016109307
"9. A system comprising:
a speech recognition(音声認識)component for receiving a plurality of natural language expressions(自然言語表現), wherein the plurality of natural language expressions include at least one of words, terms(用語), and phrases of text; and
a dialog(対話;*会話、ダイアログ)component for:
creating a first fallback query from the plurality of natural language expressions, wherein creating the first fallback query comprises concatenating(連結)the plurality of natural language expressions; and
sending the at least one fallback query to a backend engine for generating search results from the at least one fallback query."
"[0001] Language understanding applications (e.g., digital assistant applications) require at least some contextual language understanding for interpreting spoken language input. In this regard, digital assistant applications may have experience interpreting spoken language inputs having a specific domain and/or task. For example, a digital assistant application may provide accurate results when interpreting a spoken language input related to a calendar event. However, in scenarios(シナリオ;*場面)where the digital assistant application does not know how to handle the spoken language input, a backend solution (e.g., the web) may be used to provide a user with results. It may be difficult to determine when to use the digital assistant application and when to use a backend solution for a given(所与)spoken language input. In some cases, deterministic hard-coded rules may be used to determine when to use the digital assistant application and when to use a backend solution to fulfill a user's request. The cost of crafting and implementing these rules, as well as evaluating their accuracy, is high. Additionally, hard-coded rules do not scale well(スケーリングしない)for locale expansion (e.g., interpreting new and/or different languages). Furthermore, when it is determined to use a backend solution, the spoken language input is sent to the backend solution "as is(そのまま)" and a result is provided based on the received spoken language input. Consequently, as commonly known to the community, the hard-coded rules are "coarse-grained(きめが粗い)" and the overall user experience suboptimal(準最適)."
WO2014210368
(Ab)
"Systems, methods and aspects, and embodiments thereof relate to unsupervised(教師なし)or semi-supervised(半教師あり)features learning using a quantum processor. To achieve unsupervised or semi-supervised features learning, the quantum processor is programmed to achieve Hierarchal Deep Learning (referred to as HDL) over one or more data sets. Systems and methods search for, parse, and detect maximally repeating patterns in one or more data sets or across data or data sets. Embodiments and aspects regard using sparse coding to detect maximally repeating patterns in or across data. Examples of sparse coding include L0 and L1 sparse coding. Some implementations may involve appending, incorporating or attaching labels to dictionary elements, or constituent elements of one or more dictionaries. There may be a logical association between label and the element labeled such that the process of unsupervised or semi-supervised feature learning spans both the elements and the incorporated, attached or appended label."
US2017039039
"1. A method for model-based design of safety-critical software, the method comprising:
receiving natural-language software requirements(要件);
developing a software specification(仕様)model in a structured natural language by implementing at least one of semantic modeling and graphical modeling of the natural-language software requirements;
applying formal requirement analysis(解析)of the software specification model;
automatically generating requirements based and robustness test cases from the software specification model;
developing a software design model based on the specification model;
applying automatically generated requirements based and robustness test cases to the software design model;
conducting formal analysis of the software design model;
auto-generating source code using the software design model;
verifying coverage and behavior of the source code by applying automatically generated test cases and static analysis technology;
compiling executable object code from the verified source code; and
verifying coverage and behavior of the executable object code by applying automatically generated test cases."
WO2016025128
"1. A system comprising:
one or more server computers;
one or more server applications that have been selected and enabled by a user for execution on the one or more server computers, wherein the one or more selected and enabled server applications operate in conjunction with a speech(音声)interface device located in premises(敷地)of the user to provide services for the user;
a speech processing component configured to receive first and second utterances(発話)from the speech interface device, wherein the first and second utterances express(表現)first and second user intents(インテント;*意図), respectively, the speech processing component being further configured to perform automatic speech recognition and natural language understanding on the first and second utterances to determine the first and second user intents;
an intent router configured to perform acts comprising:
identifying a server application of the one or more server applications corresponding to the first user intent;
invoking the identified server application to perform a first action corresponding to the first user intent; and
providing an indication of the second user intent to the speech interface device, wherein the speech interface device is responsive to the second user intent to perform a second action corresponding to the second user intent."
"11. The method of claim 6, further comprising conducting natural language dialogs(対話)with a user to receive the first and second user speech."
"[0035] As mentioned above with reference to FIG. 1, the control service 108 may have an automatic speech recognition (ASR) component 204 and a natural language understanding (NLU) component 206. The dialog management component 132 is configured to coordinate dialogs(対話)or interactions(インタラクション)with the user 106 based on speech as recognized by the speech recognition component 204 and/or understood by the natural language understanding component 206. The control service 108 may also have a text- to-speech component 208 that is responsive to the dialog management component 132 to generate speech for playback(再生)to the user 106 on the speech interface device 102."
WO2012138587
"1. A method executed at least in part in a computing device for facilitating audio- interactive(音声対話型)message exchange, the method comprising:
receiving an indication(指示)from a user to send a message;
enabling the user to provide a recipient of the message and an audio content of the message through audio input;
performing speech recognition on the received audio input; determining the recipient from the speech recognized audio input; and transmitting the speech recognized content of the message to the recipient as a text-based message."
"[0033] The interactions(対話)in operation flows 200 and 300 may be completely automated allowing the user to provide audio input through natural language or prompted (e.g. the device providing audio prompts at various stages). Moreover, physical interaction (pressing of physical or virtual buttons, text prompts, etc.(等)) may also be employed at different stages of the interaction. Furthermore, users may be provided with the option of editing outgoing messages upon recording of those (following optional playback)."
US2003225825
"1. A method of generating an application accessible by a user in accordance with a dialog(ダイアログ;*対話、会話)system, the method comprising the steps of:
representing interactions(対話;*インタラクション)that the user may have with the dialog system as a data model and one or more user interaction elements that populate(移植;*構成する?)an application state of the data model and that are bound thereto, such that a dialog that the user has with the dialog system may be a mixed-initiative dialog;
wherein at least a portion of the one or more user interaction elements can be transformed or associated to one or more modality-specific renderings(形態特有のレンダリング)of the application which are presentable to the user and are one of selected and generated by a dialog manager algorithm."
"19. The method of claim 1, wherein the one or more user interaction elements represent conversational(会話型)gestures."