# US 11,908,179 B2 · Suggestions for fallback social contacts for assistant systems

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- Number: US 11,908,179 B2
- Document ID: US11908179B2
- Status: Granted
- Kind: B2
- Application number: 17/718,146
- Filed: 2022-04-11
- Published: 2022-09-08
- Granted: 2024-02-20
- Earliest claimed: 2018-04-20
- Assignees: Meta Platforms, Inc.
- Applicants: Meta Platforms, Inc.
- Inventors: Jason Schissel; Emmanouil Koukoumidis; Shane Haladuick; Nicholas Robin; Fuchun Peng; Aleksey Sergeyevich Fadeev
- Web page: https://patentgrep.com/patent/US11908179B2

## CPC

- G06Q 10/00: Administration; Management
- G06F 3/011: {Arrangements for interaction with the human body, e.g. for user immersion in virtual reality (blind teaching G09B21/00)}
- G06F 3/013: {Eye tracking input arrangements (G06F3/015 takes precedence)}
- G06F 3/017: {Gesture based interaction, e.g. based on a set of recognized hand gestures (interaction based on gestures traced on a digitiser G06F3/04883)}
- G06F 3/167: {Audio in a user interface, e.g. using voice commands for navigating, audio feedback}
- G06F 7/14: Merging, i.e. combining at least two sets of record carriers each arranged in the same ordered sequence to produce a single set having the same ordered sequence
- G06F 8/31: {Programming languages or programming paradigms}
- G06F 9/44505: {Configuring for program initiating, e.g. using registry, configuration files}
- G06F 9/4451: {User profiles; Roaming}
- G06F 9/453: {Help systems}
- G06F 16/176: Support for shared access to files; File sharing support
- G06F 16/2255: {Hash tables}
- G06F 16/2365: {Ensuring data consistency and integrity}
- G06F 16/243: {Natural language query formulation}
- G06F 16/24552: {Database cache management}
- G06F 16/24575: {using context}
- G06F 16/24578: {using ranking}
- G06F 16/248: Presentation of query results
- G06F 16/3322: {using system suggestions (G06F16/3325 takes precedence)}
- G06F 16/3323: {using document space presentation or visualization, e.g. category, hierarchy or range presentation and selection}
- G06F 16/3329: Natural language query formulation
- G06F 16/3344: {using natural language analysis}
- G06F 16/338: Presentation of query results
- G06F 16/90332: {Natural language query formulation or dialogue systems}
- G06F 16/90335: {Query processing}
- G06F 16/9038: Presentation of query results
- G06F 16/904: Browsing; Visualisation therefor (for navigating the web G06F16/954; browsing optimisation for the web G06F16/957)
- G06F 16/951: Indexing; Web crawling techniques
- G06F 16/9532: Query formulation
- G06F 16/9535: Search customisation based on user profiles and personalisation
- G06F 18/2411: based on the proximity to a decision surface, e.g. support vector machines
- G06F 21/6245: {Protecting personal data, e.g. for financial or medical purposes}
- G06F 40/205: Parsing
- G06F 40/274: Converting codes to words; Guess-ahead of partial word inputs
- G06F 40/295: Named entity recognition
- G06F 40/30: Semantic analysis
- G06F 40/40: Processing or translation of natural language (natural language analysis G06F40/20; semantic analysis G06F40/30)
- G06N 3/006: based on simulated virtual individual or collective life forms, e.g. social simulations or particle swarm optimisation [PSO]
- G06N 3/0442: characterised by memory or gating, e.g. long short-term memory [LSTM] or gated recurrent units [GRU]
- G06N 3/045: Combinations of networks
- G06N 3/0464: Convolutional networks [CNN, ConvNet]
- G06N 3/08: Learning methods
- G06N 3/09: Supervised learning
- G06N 5/022: Knowledge engineering; Knowledge acquisition
- G06N 5/027: {Frames}
- G06N 7/01: Probabilistic graphical models, e.g. probabilistic networks
- G06N 20/00: Machine learning
- G06Q 10/40: Business processes related to social networking or social networking services
- G06Q 10/42: Determination of affinities or common interests between users
- G06Q 10/48: using social graphs
- G06V 10/764: using classification, e.g. of video objects
- G06V 10/82: using neural networks
- G06V 20/10: Terrestrial scenes (scenes under surveillance with static cameras G06V20/52; scenes perceived from the exterior of a vehicle G06V20/56; scenes perceived from the interior of a vehicle G06V20/59)
- G06V 40/28: {Recognition of hand or arm movements, e.g. recognition of deaf sign language (static hand signs G06V40/113)}
- G10L 15/02: Feature extraction for speech recognition; Selection of recognition unit
- G10L 15/063: {Training}
- G10L 15/07: to the speaker
- G10L 15/16: using artificial neural networks
- G10L 15/1815: {Semantic context, e.g. disambiguation of the recognition hypotheses based on word meaning}
- G10L 15/1822: {Parsing for meaning understanding}
- G10L 15/183: using context dependencies, e.g. language models
- G10L 15/187: Phonemic context, e.g. pronunciation rules, phonotactical constraints or phoneme n-grams
- G10L 15/22: Procedures used during a speech recognition process, e.g. man-machine dialogue
- G10L 15/26: Speech to text systems (G10L15/08 takes precedence)
- G10L 17/06: Decision making techniques; Pattern matching strategies
- G10L 17/22: Interactive procedures; Man-machine interfaces
- H04L 5/02: Channels characterised by the type of signal
- H04L 12/2816: {Controlling appliance services of a home automation network by calling their functionalities (arrangements in telecontrol or telemetry systems for selectively calling a substation from a main station; in which substation desired apparatus is selected for applying a control signal thereto or for obtaining measured values therefrom H04Q9/00)}
- H04L 41/20: {Network management software packages}
- H04L 41/22: comprising specially adapted graphical user interfaces [GUI]
- H04L 43/0882: Utilisation of link capacity
- H04L 43/0894: Packet rate
- H04L 51/02: using automatic reactions or user delegation, e.g. automatic replies or chatbot-generated messages
- H04L 51/18: Commands or executable codes
- H04L 51/216: Handling conversation history, e.g. grouping of messages in sessions or threads
- H04L 51/52: for supporting social networking services
- H04L 63/102: {Entity profiles}
- H04L 67/306: User profiles
- H04L 67/535: {Tracking the activity of the user (network monitoring arrangements H04L43/00; recording of computer activity G06F11/34)}
- H04L 67/5651: Reducing the amount or size of exchanged application data
- H04L 67/75: Indicating network or usage conditions on the user display
- H04W 12/08: Access security
- G06F 2216/13: Prefetching
- G10L 13/00: Speech synthesis; Text to speech systems
- G10L 13/04: Details of speech synthesis systems, e.g. synthesiser structure or memory management
- G10L 17/00: Speaker identification or verification techniques
- G10L 2015/223: {Execution procedure of a spoken command}
- G10L 2015/225: {Feedback of the input speech}
- H04L 51/046: Interoperability with other network applications or services
- H04L 51/222: using geographical location information, e.g. messages transmitted or received in proximity of a certain spot or area
- H04L 67/10: in which an application is distributed across nodes in the network (software deployment G06F8/60; multiprogramming arrangements G06F9/46)
- H04L 67/53: using third party service providers
- G06Q: INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N)
- G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06V: IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G10L: SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
- H04L: TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION (arrangements common to telegraphic and telephonic communication H04M)
- H04W: WIRELESS COMMUNICATION NETWORKS (broadcast communication H04H; communication systems using wireless links for non-selective communication, e.g. wireless extensions H04M1/72)

## Abstract

In one embodiment, a method includes, by a client system, receiving a user input from the first user of an online social network, where the user input is associated with a subject and an intent, determining whether one or more agents associated with the intent are able to resolve the user input, identifying, responsive to determining that the one or more agents are not able to resolve the user input, one or more entities related to the subject, where each identified entity is connected to the first user via the online social network, and presenting, at the client system, one or more recommendations to the first user corresponding to the one or more entities.

## Claims

### Claim 1

A method comprising, by a client system:
receiving, by the client system, a user input from the first user of an online social network, wherein the user input is associated with a subject and an intent;
determining whether one or more agents associated with the intent are able to resolve the user input;
identifying, responsive to determining that the one or more agents are not able to resolve the user input, one or more entities related to the subject, each identified entity being connected to the first user via the online social network; and
presenting, at the client system, one or more recommendations to the first user corresponding to the one or more entities.

### Claim 2 (depends on 1)

The method of claim 1, wherein the user input is received as one or more of a text input or an audio input.

### Claim 3 (depends on 1)

The method of claim 1, wherein determining whether the one or more agents associated with the intent are able to resolve the user input comprises, for each of the one or more agents:
submitting a query comprising the identified subject and intent to the agent; and
determining that the agent is not able to resolve the user input after failing to receive a response to the query from the agent after a predetermine time interval.

### Claim 4 (depends on 1)

The method of claim 1, wherein determining whether the one or more agents associated with the intent are able to resolve the user input comprises:
determining that the user input is a request for more information related to the subject received responsive to resolving a prior user input related to the subject.

### Claim 5 (depends on 1)

The method of claim 1, wherein determining whether the one or more agents associated with the intent are able to resolve the user input comprises:
identifying the one or more agents to call based on the intent;
submitting a query comprising the subject and the intent to each of the one or more agents;
receiving a response from one or more of the agents indicating a failure of resolving the query; and
submitting a request to a social-fallback agent to resolve the user input.

### Claim 6 (depends on 1)

The method of claim 1, wherein the social-fallback agent identifies the one or more entities related to the subject of the user input.

### Claim 7 (depends on 1)

The method of claim 1, wherein the one or more entities comprise one or more of: a second user, a group, or a business.

### Claim 8 (depends on 1)

The method of claim 1, wherein the one or more entities are connected to the first user in a social graph of the online social network within a threshold degree of separation.

### Claim 9 (depends on 1)

The method of claim 1, further comprising:
calculating a subject-association score for each of the one or more entities, wherein the subject-association score for each entity is based on one or more content objects associated with the entity that are relevant to the subject of the user input; and
ranking the one or more entities based on their respective subject-association scores, wherein the presentation of the one or more recommendations is based on a rank of the respective one or more entities.

### Claim 10 (depends on 9)

The method of claim 9, further comprising:
searching for one or more content objects within a social graph that are relevant to the subject, wherein each of the one or more content objects are associated with a respective entity of the one or more entities, and wherein each of the one or more content objects contribute to the subject-association score for the respective entity of the one or more entities.

### Claim 11 (depends on 10)

The method of claim 10, wherein content objects that are older than a threshold time period are excluded from contributing to the subject-association score for the respective entity.

### Claim 12 (depends on 10)

The method of claim 10, wherein calculating the subject-association score comprises, for each of the one or more entities:
accessing an interest score for the entity, wherein the interest score is based on interactions of the entity with the one or more content objects;
accessing an authority score for the entity, wherein the authority score is based on interactions of the entity with one or more content objects that have been identified as an authoritative source on the identified subject; and
calculating the subject-association score for the entity based on the accessed interest and authority scores.

### Claim 13 (depends on 12)

The method of claim 12, wherein a first weight is assigned to the interest score and a second weight is assigned to the authority score in the calculation of the subject-association score.

### Claim 14 (depends on 1)

The method of claim 1, wherein one or more of the recommendations comprise a snippet of one of the content objects associated with the corresponding entity.

### Claim 15 (depends on 1)

The method of claim 1, further comprising, for each of the one or more entities:
calculating, by the one or more computing systems, a social-connection score for the entity based on social signals between the entity and the first user.

### Claim 16 (depends on 15)

The method of claim 15, further comprising ranking the one or more entities based on their respective social-connection scores, wherein the presentation of the one or more recommendations is based on a rank of the respective one or more entities.

### Claim 17 (depends on 1)

The method of claim 1, wherein one or more of the one or more recommendations comprises an activatable link to open a message thread with the entity corresponding to the recommendation.

### Claim 18 (depends on 1)

The method of claim 1, further comprising:
receiving, from the client system, feedback from the first user responsive to the one or more recommendations; and
adjusting subject-association scores for one or more of the entities based on the feedback.

### Claim 19

One or more computer-readable non-transitory storage media embodying software that is operable when executed to:
receive, by the client system, a user input from the first user of an online social network, wherein the user input is associated with a subject and an intent;
determine whether one or more agents associated with the intent are able to resolve the user input;
identify, responsive to determining that the one or more agents are not able to resolve the user input, one or more entities related to the subject, each identified entity being connected to the first user via the online social network; and
present, at the client system, one or more recommendations to the first user corresponding to the one or more entities.

### Claim 20

A system comprising: one or more processors; and a non-transitory memory coupled to the processors comprising instructions executable by the processors, the processors operable when executing the instructions to:
receive, by the client system, a user input from the first user of an online social network, wherein the user input is associated with a subject and an intent;
determine whether one or more agents associated with the intent are able to resolve the user input;
identify, responsive to determining that the one or more agents are not able to resolve the user input, one or more entities related to the subject, each identified entity being connected to the first user via the online social network; and
present, at the client system, one or more recommendations to the first user corresponding to the one or more entities.