Microsoft Technology Licensing, LLC

Other

John Anthony Taylor

Nicholas Alexander Allen

Kenneth David Wolf

Christopher Lee Mullins

Justin David Brown

Stefan R Batres

Steven Wayne Ickman

Kartik Paramasivam

Henrik Frystyk Nielsen

Robert Standefer, Iii

Thomas Matthew Laird-McConnell

Nathan Christopher Talbert

Leon Welicki

David Leon Stucki

Scott Jeff Gellock

Angshuman Sarkar

Edmund Pinto

Christopher Clayton McConnell

James Ernest Johnson

William L Portnoy

Edmund Samuel Victor Pinto

Karthik Raman

Igor Sedukhin

Vishwac Sena Kannan

Jean-Emile Elien

Shahin Shayandeh

Haoran Andy Wu

Sumit Mohanty

Clark Roberts

Bin Li

Michael Josef Krejcik

Gabriel Gilabert

Dharma Kiritkumar Shukla

Stephen James Millet

Richard Douglas Hill

Affan Arshad Dar

Alexander Evgenievich Nosov

Amol Kulkarni

Wei Zhong

Christopher Michael Whitten

Ramasubramaniam Poornalingam

Gilles C J A Zunino

Yishai Galatzer

Gruia Pitigoi-Aron

Edmund S V Pinto

Margaret J Lye

Stuart J Langley

Ronald D Heisler

Vikram Desai

Rick Heisler

Grzegorz Gogolowicz

Raul Guillermo Camacho

William Leo Oellermann, Jr

Timothy Glenn MacNary

Margaret J Drollinger

Alexandre Panov

Andrew L Luty

Thomas Matthew Laird-Mcconnell

Edmund Sv Pinto

Stefen R Batres

In non-limiting examples of the present disclosure, systems, methods and devices for enabling conversational bot communications are presented. A marketplace comprising an identity of a plurality of skills may be maintained, each of the plurality of skills associated with a manifest and a conversational bot. A request for execution of a specific skill may be received. A plurality of conversational bots may be identified, each of the plurality of conversational bots being associated with a manifest for executing the specific skill. The plurality of conversational bots may be ranked. The specific skill may be caused to be executed by the highest ranked conversational bot. In some examples, a plurality of highest ranked conversational bots may be surfaced and a bot that is selected may execute the specific skill.

Marketplace for conversational bot skills

The present disclosure relates to processing operations configured to generate and present a chat bot diagnostic visualization that provides real-time visual insights into operation of a chat bot for debugging assistance. A chat bot diagnostic tool is programmed to launch a graphical user interface that displays a visual representation of diagnostic data for debugging a chat bot in real-time. To enable conversational specific data to be reviewed, the present disclosure is configured to implement a middleware adapter within in a run-time stack of a chat bot that is configured to trace data traffic between a chat bot and a channel of an application/service. This enables the chat bot diagnostic tool to observe data traffic and filter the data traffic to identify relevant data for debugging a chat bot. A debugging data visualization of a chat bot interaction is emulated through a graphical user interface of the chat bot diagnostic tool.

Chat bot diagnostic visualization

A natural language model can be primed utilizing optimized examples generated from a labeled knowledge graph corresponding to an independently developed application program. Parsing of the labeled knowledge graph can include the identification of triples, comprising a source node, a destination node, and a link between them, each of which can be labeled. One or more natural language input examples can be generated from an individual triple by concatenating the natural language words or phrases utilized to label the source node in the link. Determinations that subsequently received natural language user input is similar to the generated examples can result in an identification of the triple, which can, in turn, trigger the performance of a function associated with the destination node of the triple. Labels can include preferred labels and alternative labels, and various permutations thereof can be concatenated to generate alternative natural language input examples.

Labeled knowledge graph based priming of a natural language model providing user access to programmatic functionality through natural language input

A chat bot computing system includes a bot controller and a natural language processor. The natural language processor receives a first textual input and identifies concepts represented by the first textual input. An indication of the concepts is output to the bot controller which generates a response to the first textual input. The concepts output by the natural language processor are also fed back into the input to the natural language processor, as context information, along with an expiration indicator when a second textual input is received. The natural language processor then identifies concepts represented in the second textual input, based on the second natural language, textual input and unexpired context information.

Contextual feedback, with expiration indicator, to a natural understanding system in a chat bot

Methods, systems, apparatuses, and computer program products are provided for merging the query results received for a query provided to multiple services. In one aspect, a query is transmitted to a plurality of search services. A plurality of query result sets is received from the search services in response to the query. A comparer function is generated by applying a ranking algorithm to the received query result sets that orders the query results of the query result sets without regard to a received order of the query results in the query result sets. The query result sets are merged into a merged query result set using the comparer function. In an aspect, the query result sets are merged in a manner that maintains an internal order of each received query result set in the merged query result set.

Combining catalog search results from multiple package repositories

The present disclosure relates to systems and methods of overlaying a plurality of isolated collections to generate an overlaid isolated collection. In an example, a first and second isolated collection having at least one common resource may be overlaid. A first and second inference ruleset may be extracted from the first and second isolated collection, respectively. Based on the first and second inference ruleset, one or more suggestions may be generated relating to conflicting inference rules. A suggestion may comprise selecting a subset of the conflicting inference rules (e.g., none, some, or all of the rules) for inclusion in the overlay isolated collection. Another suggestion may comprise generating a new inference rule based on the conflicting inference rules. An indication relating to the suggestions may be received. The indication may be used to generate a third isolated collection and a third inference ruleset.

Contextual analysis of isolated collections based on differential ontologies

A chat bot computing system includes a bot controller and a natural language processor. The natural language processor receives a first textual input and identifies concepts represented by the first textual input. An indication of the concepts is output to the bot controller which generates a response to the first textual input. The concepts output by the natural language processor are also fed back into the input to the natural language processor, as context information, when a second textual input is received. The natural language processor then identifies concepts represented in the second textual input, based on the second natural language, textual input and the context information.

Contextual feedback to a natural understanding system in a chat bot

In non-limiting examples of the present disclosure, systems, methods and devices for enabling conversational bot communications are presented. A natural language input may be received by a first conversational bot. A skill needed to fulfill a request in the natural language input may be identified. A determination may be made that the skill is not executable by the first conversational bot. A determination may be made that the skill is executable by a second conversational bot. A request for execution of the skill may be sent from the first conversational bot to the second conversational bot. A request for information needed for the second conversational bot to execute the skill may be received by the first conversational bot from the second conversational bot. The information may be sent from the first conversational bot to the second conversational bot. The skill may be executed.

Conversational manifests for enabling complex bot communications

Systems and methods are provided for storing and retrieving data using a linked data model having a tree format. Instead of using a traditional relational database, a linked data model can be used with links between data items that reflect the underlying business logic. To facilitate retrieval of data, the data items stored using the linked data model can be individually addressable.

Linked data processor for database storage

A system and method of automating data profile updating and querying includes building bots using standard schema having predefined data types for collecting data relating to a user or object. A bot stores the collected data in a data profile for the user or object in a graph data store that is queried by that bot or another bot to extract data relating to the user or object. The data relating to the user or object may be collected from two or more data channels including, for example, a channel of spoken data and a channel of typed data. The collected data is selectively processed by a bot to establish context for the collected data and is inserted into a knowledge graph that may be joined to another knowledge graph for querying. The bots automate the collection and sharing of collected profile data with other bots in an application ecosystem.

Profile data store automation via bots

At least some embodiments described herein relate to computer-assisted conversation. The set of available conversation segments is updated by addressing conversation segments at the granularity of a conversation segment or a group of conversation segments. For instance, an entire class of conversation segments may be addressed to add, delete, turn on, or turn off, the class of conversation segments. Groups of class of conversation segments may also be similarly addressed. Thus, as the scope of a conversation changes, the available set of conversation segments may likewise change with fine-grained control. Accordingly, rather than pre-plan every set of possible conversations, the context and direction of the conversation may be evaluated by code to thereby determine what new sets of conversation segments should be added, deleted, turned on, or turned off. New conversation segments may even be generated dynamically, taking into account the values of parameters that then exist.

Computer-assisted conversation using addressible conversation segments

Methods, systems, and computer program products for dispatching an incoming event are described. A scoring stack is accessed, the scoring stack comprising an identity of one or more tasks, each task corresponding to one or more scorable functions. A scorable tree is generated based on the one or more scorable functions corresponding to the one or more tasks of the scoring stack and the incoming event is processed using the scorable tree to generate one or more scores. One or more actions identified in the scorable tree are performed based on the one or more scores.

Dynamic event processing

Systems and methods that provide for shared processing of rulesets against one or more isolated collections representing resources and relationships between those resources. Asserted resources may be added to an isolated collection and a ruleset may be accessed or received. The ruleset may be executed against the corresponding isolated collection to generated inferred data, such as inferred relationships between the asserted resources in the isolated collection. Transmitting the isolated collection to a client may depend on the type of client and on the network connection to the client. The isolated collection may be transmitted with just the asserted data and the ruleset, but not the inferred data. The client is able to locally process the rules against the asserted data to locally generate inferred data to create a locally generated enriched isolated collection. The locally generated enriched isolated collection may then be queried locally.

Shared processing of rulesets for isolated collections of resources and relationships

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Bellevue, WA, United States of America

John Anthony Taylor