Abstract: An augmented conversational understanding agent may be provided. Upon receiving, by an agent, at least one natural language phrase from a user, a context associated with the at least one natural language phrase may be identified. The natural language phrase may be associated, for example, with a conversation between the user and a second user. An agent action associated with the identified context may be performed according to the at least one natural language phrase and 201 a result associated with performing the action may be displayed.

Abstract: An assembly and a method of joining a first part with a second part at an attachment area that includes a localized area on the first part. The localized area is cleaned and activated by a plasma jet. An organosilicon composition is applied by plasma-enhanced chemical vapor deposition to the localized area. An adhesive is applied to the localized area and the second part is mechanically fastened to the first part in the localized area.

Abstract: Techniques are described related to turn-based reinforcement learning for dialog management. In various implementations, dialog states and corresponding responsive actions generated during a multi-turn human-to-computer dialog session may be obtained. A plurality of turn-level training instances may be generated, each including: a given dialog state of the plurality of dialog states at an outset of a given turn of the human-to-computer dialog session; and a given responsive action that was selected based on the given dialog state. One or more of the turn-level training instances may further include a turn-level feedback value that reflects on the given responsive action selected during the given turn. A reward value may be generated based on an outcome of the human-to-computer dialog session. The dialog management policy model may be trained based on turn-level feedback values of the turn-level training instance(s) and the reward value.

Abstract: Aspects of the present invention provide a technique to validate the transfer of intents or entities between existing natural language model domains (hereafter “domain” or “NLU”) using click logs, a knowledge graph, or both. At least two different types of transfers are possible. Intents from a first domain may be transferred to a second domain. Alternatively or additionally, entities from the second domain may be transferred to an existing intent in the first domain. Either way, additional intent/entity pairs can be generated and validated. Before the new intent/entity pair is added to a domain, aspects of the present invention validate that the intent or entity is transferable between domains. Validation techniques that are consistent with aspects of the invention can use a knowledge graph, search query click logs, or both to validate a transfer of intents or entities from one domain to another.

Abstract: A dialog system for use in a multi-user, multi-domain environment. The dialog system understands user requests when multiple users are interacting with each other as well as the dialog system. The dialog system uses multi-human conversational context to improve domain detection. Using interactions between multiple users allows the dialog system to better interpret machine directed conversational inputs in multi-user conversational systems. The dialog system employs topic segmentation to chunk conversations for determining context boundaries. Using general topic segmentation methods, as well as the specific domain detector trained with conversational inputs collected by a single user system, allows the dialog system to better determine the relevant context. The use of conversational context helps reduce the domain detection error rate, especially in certain domains, and allows for better interactions with users when the machine addressed turns are not recognized or are ambiguous.

Abstract: Natural language query translation may be provided. A statistical model may be trained to detect domains according to a plurality of query click log data. Upon receiving a natural language query, the statistical model may be used to translate the natural language query into an action. The action may then be performed and at least one result associated with performing the action may be provided.

Abstract: Methods and systems are disclosed for analyzing the adhesiveness of enamel frits using topography. One method includes analyzing a topography of a defined area of an enamel frit surface having a plurality of peaks and determining a topographical parameter of the defined area based on peak shape and/or density. The determined topographical parameter may be compared to a threshold value. The method may then include applying an adhesive to the enamel frit and bonding the enamel frit to a substrate if the determined topographical parameter is below the threshold value. The analysis of the topography may be performed using a non-contact profilometer, such as an optical profilometer. In one embodiment, the topographical parameter may be developed interfacial roughness (Sdr). The method may be integrated into a manufacturing/assembly line for vehicle glass components, such as windshields or side windows.

Abstract: Methods and systems are disclosed for analyzing the adhesiveness of enamel frits using topography. One method includes analyzing a topography of a defined area of an enamel frit surface having a plurality of peaks and determining a topographical parameter of the defined area based on peak shape and/or density. The determined topographical parameter may be compared to a threshold value. The method may then include applying an adhesive to the enamel frit and bonding the enamel frit to a substrate if the determined topographical parameter is below the threshold value. The analysis of the topography may be performed using a non-contact profilometer, such as an optical profilometer. In one embodiment, the topographical parameter may be developed interfacial roughness (Sdr). The method may be integrated into a manufacturing/assembly line for vehicle glass components, such as windshields or side windows.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for processing word sequences using neural networks. One of the methods includes receiving a first sequence of words arranged according to a first order; and for each word in the first sequence, beginning with a first word in the first order: determining a topic vector that is associated with the word; generating a combined input from the word and the topic vector, and processing the combined input through one or more sequence modeling layers to generate a sequence modeling output for the word; and processing one or more of the sequence modeling outputs through an output layer to generate a neural network output for the first sequence of words.

Abstract: A relation detection model training solution. The relation detection model training solution mines freely available resources from the World Wide Web to train a relationship detection model for use during linguistic processing. The relation detection model training system searches the web for pairs of entities extracted from a knowledge graph that are connected by a specific relation. Performance is enhanced by clipping search snippets to extract patterns that connect the two entities in a dependency tree and refining the annotations of the relations according to other related entities in the knowledge graph. The relation detection model training solution scales to other domains and languages, pushing the burden from natural language semantic parsing to knowledge base population. The relation detection model training solution exhibits performance comparable to supervised solutions, which require design, collection, and manual labeling of natural language data.

Abstract: Natural language query translation may be provided. A statistical model may be trained to detect domains according to a plurality of query click log data. Upon receiving a natural language query, the statistical model may be used to translate the natural language query into an action. The action may then be performed and at least one result associated with performing the action may be provided.

Abstract: A method is described for processing keyed data items that are each associated with a value of a key, the keyed data items being from a plurality of distinct data streams, the processing including collecting the keyed data items, determining, based on contents of at least one of the keyed data items, satisfaction of one or more specified conditions for execution of one or more actions and causing execution of at least one of the one or more actions responsive to the determining.

Abstract: Location-based conversational understanding may be provided. Upon receiving a query from a user, an environmental context associated with the query may be generated. The query may be interpreted according to the environmental context. The interpreted query may be executed and at least one result associated with the query may be provided to the user.

Abstract: An augmented conversational understanding agent may be provided. Upon receiving, by an agent, at least one natural language phrase from a user, a context associated with the at least one natural language phrase may be identified. The natural language phrase may be associated, for example, with a conversation between the user and a second user. An agent action associated with the identified context may be performed according to the at least one natural language phrase and 201 a result associated with performing the action may be displayed.

Abstract: A nickel-based alloy, consisting of (in mass %) 1.5-3.0% Si, 1.5-3.0% Al, and >0.1-3.0% Cr, where Al+Si+Cr is ?4.0 and ?8.0 for the contents of Si, Al, and Cr in %; 0.005-0.20% Fe, 0.01-0.20% Y, and <0.001-0.20% of one or more the elements Hf, Zr, La, Ce, Ti, where Y+0.5*Hf+Zr+1.8*Ti+0.6*(La+Ce) is ?0.02 and ?0.30 for the contents of Y, Hf, Zr, La, Ce, and Ti in %; 0.001-0.10% C; 0.0005-0.10% N; 0.001-0.20% Mn; 0.0001-0.08% Mg; 0.0001-0.010% O; max. 0.015% S; max. 0.80% Cu; Ni remainder; and the usual production-related impurities.

Abstract: Identification of user intents may be provided. A plurality of network applications may be identified, and an ontology associated with each of the plurality of applications may be defined. If a phrase received from a user is associated with at least one of the defined ontologies, an action associated with the network application may be executed.

Abstract: Personalization of user interactions may be provided. Upon receiving a phrase from a user, a plurality of semantic concepts associated with the user may be loaded. If the phrase is determined to comprise at least one of the plurality of semantic concepts associated with the user, a first action may be performed according to the phrase. If the phrase is determined not to comprise at least one of the plurality of semantic concepts associated with the user, a second action may be performed according to the phrase.

Abstract: Identification of user intents may be provided. A plurality of network applications may be identified, and an ontology associated with each of the plurality of applications may be defined. If a phrase received from a user is associated with at least one of the defined ontologies, an action associated with the network application may be executed.

Abstract: An augmented conversational understanding agent may be provided. Upon receiving, by an agent, at least one natural language phrase from a user, a context associated with the at least one natural language phrase may be identified. The natural language phrase may be associated, for example, with a conversation between the user and a second user. An agent action associated with the identified context may be performed according to the at least one natural language phrase and a result associated with performing the action may be displayed, wherein the agent action comprises providing a list of movies, a list of night clubs, a search for restaurants, or other action suggestions.

Abstract: Techniques are described herein that are capable of suggesting intent frame(s) for user request(s). For instance, the intent frame(s) may be suggested to elicit a request from a user. An intent frame is a natural language phrase (e.g., a sentence) that includes at least one carrier phrase and at least one slot. A slot in an intent frame is a placeholder that is identified as being replaceable by one or more words that identify an entity and/or an action to indicate an intent of the user. A carrier phrase in an intent frame includes one or more words that suggest a type of entity and/or action that is to be identified by the one or more words that may replace the corresponding slot. In accordance with these techniques, the intent frame(s) are suggested in response to determining that natural language functionality of a processing system is activated.